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  • 1.
    Bissell, Malenka M.
    et al.
    Univ Leeds, England.
    Raimondi, Francesca
    Univ Florence, Italy.
    Ait Ali, Lamia
    Inst Clin Physiol CNR, Italy; Fdn CNR Tuscany Reg G Monasterio, Italy.
    Allen, Bradley D.
    Northwestern Univ, IL USA.
    Barker, Alex J.
    Univ Colorado, CO USA.
    Bolger, Ann F
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Univ Calif San Francisco, CA USA.
    Burris, Nicholas
    Univ Michigan, MI USA.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Collins, Jeremy D.
    Fdn CNR Tuscany Reg G Monasterio, Italy.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Francois, Christopher J.
    Mayo Clin Rochester, MN USA.
    Frydrychowicz, Alex
    Univ Hosp Schleswig Holstein, Germany; Univ Lubeck, Germany.
    Garg, Pankaj
    Univ East Anglia, England.
    Geiger, Julia
    Univ Childrens Hosp, Switzerland; Univ Childrens Hosp Zurich, Switzerland.
    Ha, Hojin
    Kangwon Natl Univ, South Korea.
    Hennemuth, Anja
    Charite, Germany; German Ctr Cardiovasc Res DZHK, Germany; Univ Med Ctr Hamburg Eppendorf, Germany.
    Hope, Michael D.
    Univ Calif San Francisco, CA USA.
    Hsiao, Albert
    Univ Calif San Diego, CA USA.
    Johnson, Kevin
    Univ Wisconsin, WI USA.
    Kozerke, Sebastian
    Univ & ETH Zurich, Switzerland.
    Ma, Liliana E.
    Northwestern Univ, IL USA.
    Markl, Michael
    Northwestern Univ, IL USA.
    Martins, Duarte
    Hosp Santa Cruz, Portugal.
    Messina, Marci
    Northwestern Med, IL USA.
    Oechtering, Thekla H.
    Mayo Clin Rochester, MN USA; Univ Hosp Schleswig Holstein, Germany; Univ Wisconsin, WI USA.
    van Ooij, Pim
    Univ Amsterdam, Netherlands; Univ Med Ctr Utrecht, Netherlands.
    Rigsby, Cynthia
    Northwestern Univ, IL USA; Ann & Robert H Lurie Childrens Hosp Chicago, IL USA.
    Rodriguez-Palomares, Jose
    Univ Autonoma Barcelona, Spain; CIBER CV, Spain.
    Roest, Arno A. W.
    Leiden Univ, Netherlands; Ctr Congenital Heart Defects Amsterdam Leiden, Netherlands.
    Roldan-Alzate, Alejandro
    Univ Wisconsin, WI USA.
    Schnell, Susanne
    Northwestern Univ, IL USA; Univ Greifswald, Germany.
    Sotelo, Julio
    Univ Valparaiso, Chile; Pontificia Univ Catolica Chile, Chile; Millennium Inst Intelligent Healthcare Engn iHEAL, Chile.
    Stuber, Matthias
    CHU Vaudois, Switzerland.
    Syed, Ali B.
    Stanford Univ, CA USA.
    Toeger, Johannes
    Lund Univ, Sweden.
    van der Geest, Rob
    Leiden Univ, Netherlands.
    Westenberg, Jos
    Leiden Univ, Netherlands.
    Zhong, Liang
    Natl Univ Singapore, Singapore.
    Zhong, Yumin
    Shanghai Jiao Tong Univ, Peoples R China.
    Wieben, Oliver
    Univ Wisconsin, WI USA.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    4D Flow cardiovascular magnetic resonance consensus statement: 2023 update2023In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 25, no 1, article id 40Article, review/survey (Refereed)
    Abstract [en]

    Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 4D Flow CMR Consensus Statement. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

  • 2.
    Bäck, Sophia
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Henriksson, Lilian
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Bolger, Ann F
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Univ Calif San Francisco, CA USA.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Persson, Anders
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Assessment of transmitral and left atrial appendage flow rate from cardiac 4D-CT2023In: Communications Medicine, E-ISSN 2730-664X, Vol. 3, no 1, article id 22Article in journal (Refereed)
    Abstract [en]

    Plain language summaryAssessing the blood flow inside the heart is important in diagnosis and treatment of various cardiovascular diseases, such as atrial fibrillation or heart failure. We developed a method to accurately track the motion of the heart walls over the course of a heartbeat in three-dimensional Computed Tomography (CT) images. Based on the motion, we calculated the amount of blood passing through the mitral valve and the left atrial appendage orifice, which are markers used in the diagnostic of heart failure and assessment of stroke risk in atrial fibrillation. The results agreed well with measurements from 4D flow MRI, an imaging technique that measures blood velocities. Our method could broaden the use of CT and make additional exams redundant. It can even be used to calculate the blood flow inside the heart. BackgroundCardiac time-resolved CT (4D-CT) acquisitions provide high quality anatomical images of the heart. However, some cardiac diseases require assessment of blood flow in the heart. Diastolic dysfunction, for instance, is diagnosed by measuring the flow through the mitral valve (MV), while in atrial fibrillation, the flow through the left atrial appendage (LAA) indicates the risk for thrombus formation. Accurate validated techniques to extract this information from 4D-CT have been lacking, however.MethodsTo measure the flow rate though the MV and the LAA from 4D-CT, we developed a motion tracking algorithm that performs a nonrigid deformation of the surface separating the blood pool from the myocardium. To improve the tracking of the LAA, this region was deformed separately from the left atrium and left ventricle. We compared the CT based flow with 4D flow and short axis MRI data from the same individual in 9 patients.ResultsFor the mitral valve flow, good agreement was found for the time span between the early and late diastolic peak flow (bias: <0.1 s). The ventricular stroke volume is similar compared to short-axis MRI (bias 3 ml). There are larger differences in the diastolic peak flow rates, with a larger bias for the early flow rate than the late flow rate. The peak LAA outflow rate measured with both modalities matches well (bias: -6 ml/s).ConclusionsOverall, the developed algorithm provides accurate tracking of dynamic cardiac geometries resulting in similar flow rates at the MV and LAA compared to 4D flow MRI. Back et al. describe a motion tracking algorithm to measure the flow rate through the mitral valve (MV) and the left atrial appendage (LAA) from 4D-CT data. The developed algorithm provided accurate tracking of dynamic cardiac geometries resulting in similar flow rates at the MV and LAA to those measured by 4D flow MRI.

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  • 3.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning2023In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 57, no 1, p. 191-203Article in journal (Refereed)
    Abstract [en]

    Background Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue.

    Purpose To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI.

    Study Type Retrospective.

    Subjects A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets.

    Field Strength/Sequence A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI).

    Assessment A 3D neural network based on the U-net architecture was trained to segment the four cardiac chambers, aorta, and pulmonary artery. The segmentations generated were compared to manually corrected atlas-based segmentations. End-diastolic (ED) and end-systolic (ES) volumes of the four cardiac chambers were calculated for both segmentations.

    Statistical tests Dice score, Hausdorff distance, average surface distance, sensitivity, precision, and miss rate were used to measure segmentation accuracy. Bland-Altman analysis was used to evaluate agreement between volumetric parameters.

    Results The following evaluation metrics were computed: mean Dice score (0.908 +/- 0.023) (mean +/- SD), Hausdorff distance (1.253 +/- 0.293 mm), average surface distance (0.466 +/- 0.136 mm), sensitivity (0.907 +/- 0.032), precision (0.913 +/- 0.028), and miss rate (0.093 +/- 0.032). Bland-Altman analyses showed good agreement between volumetric parameters for all chambers. Limits of agreement as percentage of mean chamber volume (LoA%), left ventricular: 9.3%, 13.5%, left atrial: 12.4%, 16.9%, right ventricular: 9.9%, 15.6%, and right atrial: 18.7%, 14.4%; for ED and ES, respectively.

    Data conclusion The addition of this technique to the 4D flow MRI assessment pipeline could expedite and improve the utility of this type of acquisition in the clinical setting.

    Evidence Level 4

    Technical Efficacy Stage 1

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  • 4.
    El-Saadi, Walid
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Ryhov Cty Hosp, Sweden.
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Alfredsson, Joakim
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Karlsson, Jan-Erik
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Ryhov Cty Hosp, Sweden.
    Martins, Marcelo
    Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Sederholm Lawesson, Sofia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Zaman, Shaikh Faisal
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Correction: A head-to-head comparison of myocardial strain by fast-strain encoding and feature tracking imaging in acute myocardial infarction (vol 9, 949440, 2022)2023In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 10, article id 1140214Article in journal (Other academic)
  • 5.
    Bäck, Sophia
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Skoda, Iulia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Lantz, Jonas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Henriksson, Lilian
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Lars
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Persson, Anders
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Elevated atrial blood stasis in paroxysmal atrial fibrillation during sinus rhythm: a patient-specific computational fluid dynamics study2023In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 10, article id 1219021Article in journal (Refereed)
    Abstract [en]

    Introduction: Atrial fibrillation (AF) is associated with an increased risk of stroke, often caused by thrombi that form in the left atrium (LA), and especially in the left atrial appendage (LAA). The underlying mechanism is not fully understood but is thought to be related to stagnant blood flow, which might be present despite sinus rhythm. However, measuring blood flow and stasis in the LAA is challenging due to its small size and low velocities. We aimed to compare the blood flow and stasis in the left atrium of paroxysmal AF patients with controls using computational fluid dynamics (CFD) simulations.Methods : The CFD simulations were based on time-resolved computed tomography including the patient-specific cardiac motion. The pipeline allowed for analysis of 21 patients with paroxysmal AF and 8 controls. Stasis was estimated by computing the blood residence time.Results and Discussion: Residence time was elevated in the AF group (p < 0.001). Linear regression analysis revealed that stasis was strongest associated with LA ejection ratio (p < 0.001, R-2 = 0.68) and the ratio of LA volume and left ventricular stroke volume (p < 0.001, R-2 = 0.81). Stroke risk due to LA thrombi could already be elevated in AF patients during sinus rhythm. In the future, patient specific CFD simulations may add to the assessment of this risk and support diagnosis and treatment.

  • 6.
    Ohlsson, Linus
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Neurobiology. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Da Luz Moreira, André
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bäck, Sophia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lantz, Jonas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Persson, Anders
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Hedman, Kristofer
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Chew, Michelle
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Clinical Chemistry and Pharmacology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, ANOPIVA US.
    Dahlström, Nils
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Enhancing students understanding of cardiac physiology by using 4D visualization2023In: Clinical anatomy (New York, N.Y. Print), ISSN 0897-3806, E-ISSN 1098-2353, Vol. 36, no 3, p. 542-549Article in journal (Refereed)
    Abstract [en]

    Difficulties in achieving knowledge about physiology and anatomy of the beating heart highlight the challenges with more traditional pedagogical methods. Recent research regarding anatomy education has mainly focused on digital three-dimensional models. However, these pedagogical improvements may not be entirely applicable to cardiac anatomy and physiology due to the multidimensional complexity with moving anatomy and complex blood flow. The aim of this study was therefore to evaluate whether high quality time-resolved anatomical images combined with realistic blood flow simulations improve the understanding of cardiac structures and function. Three time-resolved datasets were acquired using time-resolved computed tomography and blood flow was computed using Computational Fluid Dynamics. The anatomical and blood flow information was combined and interactively visualized using volume rendering on an advanced stereo projection system. The setup was tested in interactive lectures for medical students. Ninety-seven students participated. Summative assessment of examinations showed significantly improved mean score (18.1 +/- 4.5 vs 20.3 +/- 4.9, p = 0.002). This improvement was driven by knowledge regarding myocardial hypertrophy and pressure-velocity differences over a stenotic valve. Additionally, a supplementary formative assessment showed significantly more agreeing answers than disagreeing answers (p < 0.001) when the participants subjectively evaluated the contribution of the visualizations to their education and knowledge. In conclusion, the use of simultaneous visualization of time-resolved anatomy data and simulated blood flow improved medical students results, with a particular effect on understanding of cardiac physiology and these simulations may be useful educational tools for teaching complex anatomical and physiological concepts.

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  • 7.
    Tunedal, Kajsa
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Casas Garcia, Belén
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Bolger, Ann
    Univ Calif San Francisco, CA USA.
    Nyström, Fredrik H
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Cityhälsan Centrum.
    Östgren, Carl Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Ekholmen. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Lundberg, Peter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Haemodynamic effects of hypertension and type 2 diabetes: Insights from a 4D flow MRI-based personalized cardiovascular mathematical model2023In: Journal of Physiology, ISSN 0022-3751, E-ISSN 1469-7793Article in journal (Refereed)
    Abstract [en]

    Type 2 diabetes (T2D) and hypertension increase the risk of cardiovascular diseases mediated by whole-body changes to metabolism, cardiovascular structure and haemodynamics. The haemodynamic changes related to hypertension and T2D are complex and subject-specific, however, and not fully understood. We aimed to investigate the haemodynamic mechanisms in T2D and hypertension by comparing the haemodynamics between healthy controls and subjects with T2D, hypertension, or both. For all subjects, we combined 4D flow magnetic resonance imaging data, brachial blood pressure and a cardiovascular mathematical model to create a comprehensive subject-specific analysis of central haemodynamics. When comparing the subject-specific haemodynamic parameters between the four groups, the predominant haemodynamic difference is impaired left ventricular relaxation in subjects with both T2D and hypertension compared to subjects with only T2D, only hypertension and controls. The impaired relaxation indicates that, in this cohort, the long-term changes in haemodynamic load of co-existing T2D and hypertension cause diastolic dysfunction demonstrable at rest, whereas either disease on its own does not. However, through subject-specific predictions of impaired relaxation, we show that altered relaxation alone is not enough to explain the subject-specific and group-related differences; instead, a combination of parameters is affected in T2D and hypertension. These results confirm previous studies that reported more adverse effects from the combination of T2D and hypertension compared to either disease on its own. Furthermore, this shows the potential of personalized cardiovascular models in providing haemodynamic mechanistic insights and subject-specific predictions that could aid in the understanding and treatment planning of patients with T2D and hypertension.

  • 8.
    Riva, Alessandra
    et al.
    Politecn Milan, Italy; Policlin San Donato, Italy.
    Eriksson, Jonatan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Medical radiation physics.
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Sturla, Francesco
    Politecn Milan, Italy; Policlin San Donato, Italy.
    Votta, Emiliano
    Politecn Milan, Italy; Policlin San Donato, Italy.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Impact of dobutamine stress on diastolic energetic efficiency of healthy left ventricle: an in vivo kinetic energy analysis2023In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 10, article id 1103751Article in journal (Refereed)
    Abstract [en]

    The total kinetic energy (KE) of blood can be decomposed into mean KE (MKE) and turbulent KE (TKE), which are associated with the phase-averaged fluid velocity field and the instantaneous velocity fluctuations, respectively. The aim of this study was to explore the effects of pharmacologically induced stress on MKE and TKE in the left ventricle (LV) in a cohort of healthy volunteers. 4D Flow MRI data were acquired in eleven subjects at rest and after dobutamine infusion, at a heart rate that was similar to 60% higher than the one in rest conditions. MKE and TKE were computed as volume integrals over the whole LV and as data mapped to functional LV flow components, i.e., direct flow, retained inflow, delayed ejection flow and residual volume. Diastolic MKE and TKE increased under stress, in particular at peak early filling and peak atrial contraction. Augmented LV inotropy and cardiac frequency also caused an increase in direct flow and retained inflow MKE and TKE. However, the TKE/KE ratio remained comparable between rest and stress conditions, suggesting that LV intracavitary fluid dynamics can adapt to stress conditions without altering the TKE to KE balance of the normal left ventricle at rest.

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  • 9.
    Fernandes, Joao Filipe
    et al.
    Kings Coll London, England.
    Gill, Harminder
    Kings Coll London, England.
    Nio, Amanda
    Kings Coll London, England.
    Faraci, Alessandro
    Kings Coll London, England.
    Galli, Valeria
    FEops NV, Belgium.
    Marlevi, David
    Karolinska Inst, Sweden; MIT, MA USA.
    Bissell, Malenka
    Univ Leeds, England.
    Ha, Hojin
    Kangwon Natl Univ, South Korea.
    Rajani, Ronak
    Kings Coll London, England; Guys & St Thomas NHS Fdn Trust, England.
    Mortier, Peter
    FEops NV, Belgium.
    Myerson, Saul G.
    Univ Oxford, England.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Nordsletten, David A.
    Kings Coll London, England; Univ Michigan, MI USA.
    Lamata, Pablo
    Kings Coll London, England.
    Non-invasive cardiovascular magnetic resonance assessment of pressure recovery distance after aortic valve stenosis2023In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 25, no 1, article id 5Article in journal (Refereed)
    Abstract [en]

    BackgroundDecisions in the management of aortic stenosis are based on the peak pressure drop, captured by Doppler echocardiography, whereas gold standard catheterization measurements assess the net pressure drop but are limited by associated risks. The relationship between these two measurements, peak and net pressure drop, is dictated by the pressure recovery along the ascending aorta which is mainly caused by turbulence energy dissipation. Currently, pressure recovery is considered to occur within the first 40-50 mm distally from the aortic valve, albeit there is inconsistency across interventionist centers on where/how to position the catheter to capture the net pressure drop.MethodsWe developed a non-invasive method to assess the pressure recovery distance based on blood flow momentum via 4D Flow cardiovascular magnetic resonance (CMR). Multi-center acquisitions included physical flow phantoms with different stenotic valve configurations to validate this method, first against reference measurements and then against turbulent energy dissipation (respectively n = 8 and n = 28 acquisitions) and to investigate the relationship between peak and net pressure drops. Finally, we explored the potential errors of cardiac catheterisation pressure recordings as a result of neglecting the pressure recovery distance in a clinical bicuspid aortic valve (BAV) cohort of n = 32 patients.ResultsIn-vitro assessment of pressure recovery distance based on flow momentum achieved an average error of 1.8 +/- 8.4 mm when compared to reference pressure sensors in the first phantom workbench. The momentum pressure recovery distance and the turbulent energy dissipation distance showed no statistical difference (mean difference of 2.8 +/- 5.4 mm, R-2 = 0.93) in the second phantom workbench. A linear correlation was observed between peak and net pressure drops, however, with strong dependences on the valvular morphology. Finally, in the BAV cohort the pressure recovery distance was 78.8 +/- 34.3 mm from vena contracta, which is significantly longer than currently accepted in clinical practise (40-50 mm), and 37.5% of patients displayed a pressure recovery distance beyond the end of the ascending aorta.ConclusionThe non-invasive assessment of the distance to pressure recovery is possible by tracking momentum via 4D Flow CMR. Recovery is not always complete at the ascending aorta, and catheterised recordings will overestimate the net pressure drop in those situations. There is a need to re-evaluate the methods that characterise the haemodynamic burden caused by aortic stenosis as currently clinically accepted pressure recovery distance is an underestimation.

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  • 10.
    Ashkir, Z.
    et al.
    Univ Oxford, England.
    Johnson, S.
    Univ Oxford, England.
    Lewandowski, A. J.
    Univ Oxford, England.
    Hess, A.
    Univ Oxford, England.
    Wicks, E.
    Univ Oxford, England; Oxford Univ Hosp NHS Fdn Trust, England; Univ Oxford, England.
    Mahmod, M.
    Univ Oxford, England.
    Myerson, S.
    Univ Oxford, England.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Watkins, H.
    Univ Oxford, England.
    Neubauer, S.
    Univ Oxford, England.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Raman, B.
    Univ Oxford, England.
    Novel insights into diminished cardiac reserve in non-obstructive hypertrophic cardiomyopathy from four-dimensional flow cardiac magnetic resonance component analysis2023In: European Heart Journal Cardiovascular Imaging, ISSN 2047-2404, E-ISSN 2047-2412Article in journal (Refereed)
    Abstract [en]

    Aims Hypertrophic cardiomyopathy (HCM) is characterized by hypercontractility and diastolic dysfunction, which alter blood flow haemodynamics and are linked with increased risk of adverse clinical events. Four-dimensional flow cardiac magnetic resonance (4D-flow CMR) enables comprehensive characterization of ventricular blood flow patterns. We characterized flow component changes in non-obstructive HCM and assessed their relationship with phenotypic severity and sudden cardiac death (SCD) risk. Methods and results Fifty-one participants (37 non-obstructive HCM and 14 matched controls) underwent 4D-flow CMR. Left-ventricular (LV) end-diastolic volume was separated into four components: direct flow (blood transiting the ventricle within one cycle), retained inflow (blood entering the ventricle and retained for one cycle), delayed ejection flow (retained ventricular blood ejected during systole), and residual volume (ventricular blood retained for >two cycles). Flow component distribution and component end-diastolic kinetic energy/mL were estimated. HCM patients demonstrated greater direct flow proportions compared with controls (47.9 +/- 9% vs. 39.4 +/- 6%, P = 0.002), with reduction in other components. Direct flow proportions correlated with LV mass index (r = 0.40, P = 0.004), end-diastolic volume index (r = -0.40, P = 0.017), and SCD risk (r = 0.34, P = 0.039). In contrast to controls, in HCM, stroke volume decreased with increasing direct flow proportions, indicating diminished volumetric reserve. There was no difference in component end-diastolic kinetic energy/mL. Conclusion Non-obstructive HCM possesses a distinctive flow component distribution pattern characterised by greater direct flow proportions, and direct flow-stroke volume uncoupling indicative of diminished cardiac reserve. The correlation of direct flow proportion with phenotypic severity and SCD risk highlight its potential as a novel and sensitive haemodynamic measure of cardiovascular risk in HCM.

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  • 11.
    El-Saadi, Walid
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Ryhov Cty Hosp, Sweden.
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Alfredsson, Joakim
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Karlsson, Jan-Erik
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Ryhov Cty Hosp, Sweden.
    Martins, Marcelo
    Linköping University, Department of Health, Medicine and Caring Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Sederholm Lawesson, Sofia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Faisal Zaman, Shaikh
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    A head-to-head comparison of myocardial strain by fast-strain encoding and feature tracking imaging in acute myocardial infarction2022In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 9Article in journal (Refereed)
    Abstract [en]

    BackgroundMyocardial infarction (MI) is a major cause of heart failure. Left ventricular adverse remodeling is common post-MI. Several studies have demonstrated a correlation between reduced myocardial strain and the development of adverse remodeling. Cardiac magnetic resonance (CMR) with fast-strain encoding (fast-SENC) or feature tracking (FT) enables rapid assessment of myocardial deformation. The aim of this study was to establish a head-to-head comparison of fast-SENC and FT in post-ST-elevated myocardial infarction (STEMI) patients, with clinical 2D speckle tracking echocardiography (2DEcho) as a reference. MethodsThirty patients treated with primary percutaneous coronary intervention for STEMI were investigated. All participants underwent CMR examination with late gadolinium enhancement, cine-loop steady-state free precession, and fast-SENC imaging using a 1.5T scanner as well as a 2DEcho. Global longitudinal strain (GLS), segmental longitudinal strain (SLS), global circumferential strain (GCS), and segmental circumferential strain (SCS) were assessed along with the MI scar extent. ResultsThe GCS measurements from fast-SENC and FT were nearly identical: the mean difference was 0.01 (2.5)% (95% CI - 0.92 to 0.95). For GLS, fast-SENC values were higher than FT, with a mean difference of 1.8 (1.4)% (95% CI 1.31-2.35). Tests of significance for GLS did not show any differences between the MR methods and 2DEcho. Average strain in the infarct-related artery (IRA) segments compared to the remote myocardium was significantly lower for the left anterior descending artery and right coronary artery culprits but not for the left circumflex artery culprits. Fast-SENC displayed a higher area under the curve for detecting infarcted segments than FT for both SCS and SLS. ConclusionGLS and GCS did not significantly differ between fast-SENC and FT. Both showed acceptable agreement with 2DEcho for longitudinal strain. Segments perfused by the IRA showed significantly reduced strain values compared to the remote myocardium. Fast-SENC presented a higher sensitivity and specificity for detecting infarcted segments than FT.

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  • 12.
    Postigo, Andrea
    et al.
    Univ Complutense Madrid, Spain.
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Chazo, Christian
    Univ Complutense Madrid, Spain.
    Martinez-legazpi, Pablo
    Univ Nacl Educaciona Distancia, Spain.
    Gonzalez-mansilla, Ana
    Univ Complutense Madrid, Spain.
    Rodriguez-gonzalez, Elena
    Univ Complutense Madrid, Spain.
    Fernandez-aviles, Francisco
    Univ Complutense Madrid, Spain.
    Alamo, Juan c del
    Univ Washington, WA USA.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bermejo, Javier
    Univ Complutense Madrid, Spain; Hosp Gen Univ Gregorio Maranon, Spain.
    Assessment Of Blood Flow Transport In The Left Ventricle Using Ultrasound. Validation Against 4-D Flow Cardiac Magnetic Resonance2022In: Ultrasound in Medicine and Biology, ISSN 0301-5629, E-ISSN 1879-291X, Vol. 48, no 9, p. 1822-1832Article in journal (Refereed)
    Abstract [en]

    Four-dimensional flow cardiac magnetic resonance (CMR) is the reference technique for analyzing blood transport in the left ventricle (LV), but similar information can be obtained from ultrasound. We aimed to validate ultrasound-derived transport in a head-to-head comparison against 4D flow CMR. In five patients and two healthy volunteers, we obtained 2D + t and 3D + t (4D) flow fields in the LV using transthoracic echocardiog-raphy and CMR, respectively. We compartmentalized intraventricular blood flow into four fractions of end -dia-stolic volume: direct flow (DF), retained inflow (RI), delayed ejection flow (DEF) and residual volume (RV). Using ultrasound we also computed the properties of LV filling waves (percentage of LV penetration and percent-age of LV volume carried by E/A waves) to determine their relationships with CMR transport. Agreement between both techniques for quantifying transport fractions was good for DF and RV (Ric [95% confidence inter-val]: 0.82 [0.33, 0.97] and 0.85 [0.41, 0.97], respectively) and moderate for RI and DEF (Ric= 0.47 [-0.29, 0.88] and 0.55 [-0.20, 0.90], respectively). Agreement between techniques to measure kinetic energy was variable. The amount of blood carried by the E-wave correlated with DF and RV (R = 0.75 and R = 0.63, respectively). There-fore, ultrasound is a suitable method for expanding the analysis of intraventricular flow transport in the clinical setting. (E-mail: javier.bermejo@salud.madrid.org) (c) 2022 The Author(s). Published by Elsevier Inc. on behalf of World Federation for Ultrasound in Medicine & Biology.

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  • 13.
    Edin, Carl
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Ekstedt, Mattias
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken. Linköping University, Department of Biomedical and Clinical Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Scheffel, Tobias
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Markus
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Medical radiation physics. AMRA Medical AB, Sweden.
    Swahn, Eva
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Östgren, Carl Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Primary Care Center, Primary Health Care Center Ekholmen.
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV). AMRA Medical AB, Sweden.
    Lundberg, Peter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carl-Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ectopic fat is associated with cardiac remodeling - A comprehensive assessment of regional fat depots in type 2 diabetes using multi-parametric MRI.2022In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 9, article id 813427Article in journal (Refereed)
    Abstract [en]

    Background: Different regional depots of fat have distinct metabolic properties and may relate differently to adverse cardiac remodeling. We sought to quantify regional depots of body fat and to investigate their relationship to cardiac structure and function in Type 2 Diabetes (T2D) and controls.

    Methods: From the SCAPIS cohort in Linköping, Sweden, we recruited 92 subjects (35% female, mean age 59.5 ± 4.6 years): 46 with T2D and 46 matched controls. In addition to the core SCAPIS data collection, participants underwent a comprehensive magnetic resonance imaging examination at 1.5 T for assessment of left ventricular (LV) structure and function (end-diastolic volume, mass, concentricity, ejection fraction), as well as regional body composition (liver proton density fat fraction, visceral adipose tissue, abdominal subcutaneous adipose tissue, thigh muscle fat infiltration, fat tissue-free thigh muscle volume and epicardial adipose tissue).

    Results: Compared to the control group, the T2D group had increased: visceral adipose tissue volume index (P < 0.001), liver fat percentage (P < 0.001), thigh muscle fat infiltration percentage (P = 0.02), LV concentricity (P < 0.001) and LV E/e'-ratio (P < 0.001). In a multiple linear regression analysis, a negative association between liver fat percentage and LV mass (St Beta -0.23, P < 0.05) as well as LV end-diastolic volume (St Beta -0.27, P < 0.05) was found. Epicardial adipose tissue volume and abdominal subcutaneous adipose tissue volume index were the only parameters of fat associated with LV diastolic dysfunction (E/e'-ratio) (St Beta 0.24, P < 0.05; St Beta 0.34, P < 0.01, respectively). In a multivariate logistic regression analysis, only visceral adipose tissue volume index was significantly associated with T2D, with an odds ratio for T2D of 3.01 (95% CI 1.28-7.05, P < 0.05) per L/m2 increase in visceral adipose tissue volume.

    Conclusions: Ectopic fat is predominantly associated with cardiac remodeling, independently of type 2 diabetes. Intriguingly, liver fat appears to be related to LV structure independently of VAT, while epicardial fat is linked to impaired LV diastolic function. Visceral fat is associated with T2D independently of liver fat and abdominal subcutaneous adipose tissue.

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  • 14.
    Ashkir, Zakariye
    et al.
    Univ Oxford, England.
    Myerson, Saul
    Univ Oxford, England.
    Neubauer, Stefan
    Univ Oxford, England.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Raman, Betty
    Univ Oxford, England.
    Four-dimensional flow cardiac magnetic resonance assessment of left ventricular diastolic function2022In: Frontiers in Cardiovascular Medicine, E-ISSN 2297-055X, Vol. 9, article id 866131Article, review/survey (Refereed)
    Abstract [en]

    Left ventricular diastolic dysfunction is a major cause of heart failure and carries a poor prognosis. Assessment of left ventricular diastolic function however remains challenging for both echocardiography and conventional phase contrast cardiac magnetic resonance. Amongst other limitations, both are restricted to measuring velocity in a single direction or plane, thereby compromising their ability to capture complex diastolic hemodynamics in health and disease. Time-resolved three-dimensional phase contrast cardiac magnetic resonance imaging with three-directional velocity encoding known as 4D flow CMR is an emerging technology which allows retrospective measurement of velocity and by extension flow at any point in the acquired 3D data volume. With 4D flow CMR, complex aspects of blood flow and ventricular function can be studied throughout the cardiac cycle. 4D flow CMR can facilitate the visualization of functional blood flow components and flow vortices as well as the quantification of novel hemodynamic and functional parameters such as kinetic energy, relative pressure, energy loss and vorticity. In this review, we examine key concepts and novel markers of diastolic function obtained by flow pattern analysis using 4D flow CMR. We consolidate the existing evidence base to highlight the strengths and limitations of 4D flow CMR techniques in the surveillance and diagnosis of left ventricular diastolic dysfunction.

  • 15.
    Henningsson, Markus
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Non-contrast myocardial perfusion in rest and exercise stress using systolic flow-sensitive alternating inversion recovery2022In: Magnetic Resonance Materials in Physics, Biology and Medicine, ISSN 0968-5243, E-ISSN 1352-8661, Vol. 35, no 5, p. 711-718Article in journal (Refereed)
    Abstract [en]

    Objective To evaluate systolic flow-sensitive alternating inversion recovery (FAIR) during rest and exercise stress using 2RR (two cardiac cycles) or 1RR intervals between inversion pulse and imaging. Materials and methods 1RR and 2RR FAIR was implemented on a 3T scanner. Ten healthy subjects were scanned during rest and stress. Stress was performed using an in-bore ergometer. Heart rate, mean myocardial blood flow (MBF) and temporal signal-to-noise ratio (TSNR) were compared using paired t tests. Results Mean heart rate during stress was higher than rest for 1RR FAIR (85.8 +/- 13.7 bpm vs 63.3 +/- 11.1 bpm; p &lt; 0.01) and 2RR FAIR (83.8 +/- 14.2 bpm vs 63.1 +/- 10.6 bpm; p &lt; 0.01). Mean stress MBF was higher than rest for 1RR FAIR (2.97 +/- 0.76 ml/g/min vs 1.43 +/- 0.6 ml/g/min; p &lt; 0.01) and 2RR FAIR (2.8 +/- 0.96 ml/g/min vs 1.22 +/- 0.59 ml/g/min; p &lt; 0.01). Resting mean MBF was higher for 1RR FAIR than 2RR FAIR (p &lt; 0.05), but not during stress. TSNR was lower for stress compared to rest for 1RR FAIR (4.52 +/- 2.54 vs 10.12 +/- 3.69; p &lt; 0.01) and 2RR FAIR (7.36 +/- 3.78 vs 12.41 +/- 5.12; p &lt; 0.01). 2RR FAIR TSNR was higher than 1RR FAIR for rest (p &lt; 0.05) and stress (p &lt; 0.001). Discussion We have demonstrated feasibility of systolic FAIR in rest and exercise stress. 2RR delay systolic FAIR enables non-contrast perfusion assessment during stress with relatively high TSNR.

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  • 16.
    Kvernby, Sofia
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Department of Health, Medicine and Caring Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics.
    Flejmer, Anna M.
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. The Scandion Clinic, Uppsala, Sweden.
    Dasu, Alexandru
    Uppsala University, Uppsala, Sweden; Medical Radiation Sciences, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
    Bolger, Ann F.
    Department of Medicine, University of California, San Francisco, US.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    T1 and T2 Mapping for Early Detection of Treatment-Related Myocardial Changes in Breast Cancer Patients2022In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 55, no 2, p. 620-622Article in journal (Refereed)
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  • 17.
    Sundin, Jonathan
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Bustamante, Mariana
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Turbulent Intensity of Blood Flow in the Healthy Aorta Increases With Dobutamine Stress and is Related to Cardiac Output2022In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 13, article id 869701Article in journal (Refereed)
    Abstract [en]

    Introduction: The blood flow in the normal cardiovascular system is predominately laminar but operates close to the threshold to turbulence. Morphological distortions such as vascular and valvular stenosis can cause transition into turbulent blood flow, which in turn may cause damage to tissues in the cardiovascular system. A growing number of studies have used magnetic resonance imaging (MRI) to estimate the extent and degree of turbulent flow in different cardiovascular diseases. However, the way in which heart rate and inotropy affect turbulent flow has not been investigated. In this study we hypothesized that dobutamine stress would result in higher turbulence intensity in the healthy thoracic aorta.Method: 4D flow MRI data were acquired in twelve healthy subjects at rest and with dobutamine, which was infused until the heart rate increased by 60% when compared to rest. A semi-automatic segmentation method was used to segment the thoracic aorta in the 4D flow MR images. Subsequently, flow velocity and several turbulent kinetic energy (TKE) parameters were calculated in the ascending aorta, aortic arch, descending aorta and whole thoracic aorta.Results: With dobutamine infusion there was an increase in heart rate (66 +/- 9 vs. 108 +/- 13 bpm, p < 0.001) and stroke volume (88 +/- 13 vs. 102 +/- 25 ml, p < 0.01). Additionally, there was an increase in Peak Average velocity (0.7 +/- 0.1 vs. 1.2 +/- 0.2 m/s, p < 0.001, Peak Max velocity (1.3 +/- 0.1 vs. 2.0 +/- 0.2 m/s, p < 0.001), Peak Total TKE (2.9 +/- 0.7 vs. 8.0 +/- 2.2 mJ, p < 0.001), Peak Median TKE (36 +/- 7 vs. 93 +/- 24 J/m3, p = 0.002) and Peak Max TKE (176 +/- 33 vs. 334 +/- 69 J/m3, p < 0.001). The relation between cardiac output and Peak Total TKE in the whole thoracic aorta was very strong (R-2 = 0.90, p < 0.001).Conclusion: TKE of blood flow in the healthy thoracic aorta increases with dobutamine stress and is strongly related to cardiac output. Quantification of such turbulence intensity parameters with cardiac stress may serve as a risk assessment of aortic disease development.

  • 18.
    Trenti, Chiara
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ziegler, Magnus
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bjarnegård, Niclas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lindenberger, Marcus
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Wall shear stress and relative residence time as potential risk factors for abdominal aortic aneurysms in males: a 4D flow cardiovascular magnetic resonance case-control study2022In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 24, no 1, article id 18Article in journal (Refereed)
    Abstract [en]

    Background Abdominal aortic aneurysms (AAA) can lead to catastrophic events such as dissection or rupture, and are an expression of general aortic disease. Low wall shear stress (WSS), high oscillatory shear index (OSI), and high relative residence time (RRT) have been correlated against increased uptake of inflammatory markers in the vessel wall and may improve risk stratification of AAA. We sought to obtain a comprehensive view of WSS, OSI, and RRT in the whole aorta for patients with AAA and age-matched elderly controls and young normal controls. Methods 4D Flow cardiovascular magnetic resonance images of the whole aorta were acquired in 18 AAA patients (70.8 +/- 3.4 years), 22 age-matched controls (71.4 +/- 3.4 years), and 23 young subjects (23.3 +/- 3.1 years), all males. Three-dimensional segmentations of the whole aorta were created for all timeframes using a semi-automatic approach. The aorta was divided into five segments: ascending aorta, arch, descending aorta, suprarenal and infrarenal abdominal aorta. For each segment, average values of peak WSS, OSI, and RRT were computed. Students t-tests were used to compare values between the three cohorts (AAA patients vs elderly controls, and elderly controls vs young controls) where the data were normally distributed, and the non-parametric Wilcoxon rank sum tests were used otherwise. Results AAA patients had lower peak WSS in the descending aorta as well as in the abdominal aorta compared to elderly controls (p &lt;= 0.001), similar OSI, but higher RRT in the descending and abdominal aorta (p &lt;= 0.001). Elderly controls had lower peak WSS compared to young controls throughout the aorta (p &lt; 0.001), higher OSI in all segments except for the infrarenal aorta (p &lt; 0.001), and higher RRT throughout the aorta, except the infrarenal aorta (p &lt; 0.001). Conclusions This study provides novel insights into WSS, OSI, and RRT in patients with AAA in relation to normal ageing, highlighting how AAA patients have markedly abnormal hemodynamic stresses not only in the infrarenal, but in the entire aorta. Moreover, we identified RRT as a marker for abnormal AAA hemodynamics. Further investigations are needed to explore if RRT or other measures of hemodynamics stresses best predict AAA growth and/or rupture.

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  • 19.
    Frank, Sarah
    et al.
    Univ Calif Berkeley, CA 94720 USA.
    Lee, Junsung
    Univ Calif Berkeley, CA 94720 USA.
    Lantz, Jonas
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Shadden, Shawn C.
    Univ Calif Berkeley, CA 94720 USA.
    Cardiac Kinetic Energy and Viscous Dissipation Rate From Radial Flow Data2021In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 12, article id 725104Article in journal (Refereed)
    Abstract [en]

    Recent studies have correlated kinetic energy (KE) and viscous dissipation rate (VDR) in the left ventricle (LV) with heart health. These studies have relied on 4D-flow imaging or computational fluid dynamics modeling, which are able to measure, or compute, all 3 components (3C) of the blood flow velocity in 3 dimensional (3D) space. This richness of data is difficult to acquire clinically. Alternatively, color Doppler echocardiography (CDE) is more widespread clinically, but only measures a single radial component of velocity and typically only over a planar section. Because of this limitation, prior CDE-based studies have first reconstructed a second component of velocity in the measurement plane prior to evaluating VDR or KE. Herein, we propose 1C-based surrogates of KE and VDR that can be derived directly from the radial component of the flow velocity in the LV. Our results demonstrate that the proposed 1C-based surrogates of KE and VDR are generally as well-correlated with the true KE and VDR values as surrogates that use reconstructed 2C flow data. Moreover, the correlation of these 1C-based surrogates with the true values indicate that CDE (3D in particular) may be useful in evaluating these metrics in practice.

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  • 20.
    Nasr, Patrik
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken.
    Iredahl, Fredrik
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Åby.
    Dahlström, Nils
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Rådholm, Karin
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Prevention, Rehabilitation and Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Primary Care Center, Primary Health Care Center Kärna.
    Henriksson, Pontus
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). AMRA Med AB, Linkoping, Sweden.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Alfredsson, Joakim
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Region Östergötland, Heart Center, Department of Cardiology in Linköping. Linköping University, Faculty of Medicine and Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Lundberg, Peter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kechagias, Stergios
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken.
    Ekstedt, Mattias
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Mag- tarmmedicinska kliniken. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Evaluating the prevalence and severity of NAFLD in primary care: the EPSONIP study protocol2021In: BMC Gastroenterology, ISSN 1471-230X, E-ISSN 1471-230X, Vol. 21, no 1, article id 180Article in journal (Refereed)
    Abstract [en]

    BackgroundNon-alcoholic fatty liver disease (NAFLD) affects 20-30% of the general adult population. NAFLD patients with type 2 diabetes mellitus (T2DM) are at an increased risk of advanced fibrosis, which puts them at risk of cardiovascular complications, hepatocellular carcinoma, or liver failure. Liver biopsy is the gold standard for assessing hepatic fibrosis. However, its utility is inherently limited. Consequently, the prevalence and characteristics of T2DM patients with advanced fibrosis are unknown. Therefore, the purpose of the current study is to evaluate the prevalence and severity of NAFLD in patients with T2DM by recruiting participants from primary care, using the latest imaging modalities, to collect a cohort of well phenotyped patients.MethodsWe will prospectively recruit 400 patients with T2DM using biomarkers to assess their status. Specifically, we will evaluate liver fat content using magnetic resonance imaging (MRI); hepatic fibrosis using MR elastography and vibration-controlled transient elastography; muscle composition and body fat distribution using water-fat separated whole body MRI; and cardiac function, structure, and tissue characteristics, using cardiovascular MRI.DiscussionWe expect that the study will uncover potential mechanisms of advanced hepatic fibrosis in NAFLD and T2DM and equip the clinician with better diagnostic tools for the care of T2DM patients with NAFLD.Trial registration: Clinicaltrials.gov, identifier NCT03864510. Registered 6 March 2019, https://clinicaltrials.gov/ct2/show/NCT03864510.

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  • 21.
    Lantz, Jonas
    et al.
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Bäck, Sophia
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Bolger, Ann F.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Univ Calif San Francisco, CA 94143 USA.
    Persson, Anders
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Impact of prosthetic mitral valve orientation on the ventricular flow field: Comparison using patient-specific computational fluid dynamics2021In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 116Article in journal (Refereed)
    Abstract [en]

    Significant mitral valve regurgitation creates progressive adverse remodeling of the left ventricle (LV). Replacement of the failing valve with a prosthesis generally improves patient outcomes but leaves the patient with non-physiological intracardiac flow patterns that might contribute to their future risk of thrombus formation and embolism. It has been suggested that the angular orientation of the implanted valve might modify the postoperative distortion of the intraventricular flow field. In this study, we investigated the effect of prosthetic valve orientation on LV flow patterns by using heart geometry from a patient with LV dysfunction and a competent native mitral valve to calculate intracardiac flow fields with computational fluid dynamics (CFD). Results were validated using in vivo 4D Flow MRI. The computed flow fields were compared to calculations following virtual implantation of a mechanical heart valve oriented in four different angles to assess the effect of leaflet position. Flow patterns were visualized in longand short-axes and quantified with flow component analysis. In comparison to a native valve, valve implantation increased the proportion of the mitral inflow remaining in the basal region and further increased the residual volume in the apical area. Only slight changes due to valve orientation were observed. Using our numerical framework, we demonstrated quantitative changes in left ventricular blood flow due to prosthetic mitral replacement. This framework may be used to improve design of prosthetic heart valves and implantation procedures to minimize the potential for apical flow stasis, and potentially assist personalized treatment planning. (c) 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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  • 22.
    Ha, Hojin
    et al.
    Kangwon Natl Univ, South Korea.
    Huh, Hyung Kyu
    Daegu Gyeongbuk Med Innovat Fdn, South Korea.
    Park, Kyung Jin
    Yonsei Univ, South Korea; Univ Ulsan, South Korea.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kim, Dae-Hee
    Univ Ulsan, South Korea.
    Yang, Dong Hyun
    Univ Ulsan, South Korea.
    In-vitro and In-Vivo Assessment of 4D Flow MRI Reynolds Stress Mapping for Pulsatile Blood Flow2021In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 9, article id 774954Article in journal (Refereed)
    Abstract [en]

    Imaging hemodynamics play an important role in the diagnosis of abnormal blood flow due to vascular and valvular diseases as well as in monitoring the recovery of normal blood flow after surgical or interventional treatment. Recently, characterization of turbulent blood flow using 4D flow magnetic resonance imaging (MRI) has been demonstrated by utilizing the changes in signal magnitude depending on intravoxel spin distribution. The imaging sequence was extended with a six-directional icosahedral (ICOSA6) flow-encoding to characterize all elements of the Reynolds stress tensor (RST) in turbulent blood flow. In the present study, we aimed to demonstrate the feasibility of full RST analysis using ICOSA6 4D flow MRI under physiological conditions. First, the turbulence analysis was performed through in vitro experiments with a physiological pulsatile flow condition. Second, a total of 12 normal subjects and one patient with severe aortic stenosis were analyzed using the same sequence. The in-vitro study showed that total turbulent kinetic energy (TKE) was less affected by the signal-to-noise ratio (SNR), however, maximum principal turbulence shear stress (MPTSS) and total turbulence production (TP) had a noise-induced bias. Smaller degree of the bias was observed for TP compared to MPTSS. In-vivo study showed that the subject-variability on turbulence quantification was relatively low for the consistent scan protocol. The in vivo demonstration of the stenosis patient showed that the turbulence analysis could clearly distinguish the difference in all turbulence parameters as they were at least an order of magnitude larger than those from the normal subjects.

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  • 23.
    Marlevi, David
    et al.
    Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, USA.
    Balmus, Maximilian
    School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, Kings College London, United Kingdom.
    Hessenthaler, Andreas
    Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Germany.
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Fovargue, Daniel
    School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, Kings College London, United Kingdom.
    Vecchi, Adelaide de
    School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, Kings College London, United Kingdom.
    Lamata, Pablo
    School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, Kings College London, United Kingdom.
    Burris, Nicholas S
    Department of Radiology, University of Michigan, United States of America.
    Pagani, Francis D.
    Department of Radiology, University of Michigan, United States of America.
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Edelman, Elazer R
    Institute for Medical Engineering and Science, Massachusetts Institute of Technology, USA.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Nordsletten, David A
    School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, Kings College London, SE1 7EH, London, United Kingdom; Department of Surgery and Biomedical Engineering, University of Michigan, 2800 Plymouth Rd, Ann Arbor, MI 48109, United States of America. Electronic address nordslet@umich.com.
    Non-invasive estimation of relative pressure for intracardiac flows using virtual work-energy2021In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 68, article id 101948Article in journal (Refereed)
    Abstract [en]

    Intracardiac blood flow is driven by differences in relative pressure, and assessing these is critical in understanding cardiac disease. Non-invasive image-based methods exist to assess relative pressure, however, the complex flow and dynamically moving fluid domain of the intracardiac space limits assessment. Recently, we proposed a method, ?WERP, utilizing an auxiliary virtual field to probe relative pressure through complex, and previously inaccessible flow domains. Here we present an extension of ?WERP for intracardiac flow assessments, solving the virtual field over sub-domains to effectively handle the dynamically shifting flow domain. The extended ?WERP is validated in an in-silico benchmark problem, as well as in a patient-specific simulation model of the left heart, proving accurate over ranges of realistic image resolutions and noise levels, as well as superior to alternative approaches. Lastly, the extended ?WERP is applied on clinically acquired 4D Flow MRI data, exhibiting realistic ventricular relative pressure patterns, as well as indicating signs of diastolic dysfunction in an exemplifying patient case. Summarized, the extended ?WERP approach represents a directly applicable implementation for intracardiac flow assessments.

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  • 24.
    Henriksson, Lilian
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Woisetschläger, Mischa
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Alfredsson, Joakim
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Region Östergötland, Heart Center, Department of Cardiology in Linköping. Linköping University, Faculty of Medicine and Health Sciences.
    Janzon, Magnus
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Society and Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Cardiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Persson, Anders
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    The transluminal attenuation gradient does not add diagnostic accuracy to coronary computed tomography2021In: Acta Radiologica, ISSN 0284-1851, E-ISSN 1600-0455, p. 867-874Article in journal (Refereed)
    Abstract [en]

    Background A method for improving the accuracy of coronary computed tomography angiography (CCTA) is highly sought after as it would help to avoid unnecessary invasive coronary angiographies. Measurement of the transluminal attenuation gradient (TAG) has been proposed as an alternative to other existing methods, i.e. CT perfusion and CT fractional flow reserve (FFR). Purpose To evaluate the incremental value of three types of TAG in high-pitch spiral CCTA with invasive FFR measurements as reference. Material and Methods TAG was measured using two semi-automatic methods and one manual method. A receiver operating characteristic (ROC) analysis was made to determine the usefulness of TAG alone as well as TAG combined with CCTA for detection of significant coronary artery stenoses defined by an invasive FFR value &lt;= 0.80. Results A total of 51 coronary vessels in 37 patients were included in this retrospective study. Hemodynamically significant stenoses were found in 13 vessels according to FFR. The ROC analysis TAG alone resulted in areas under the curve (AUCs) of 0.530 and 0.520 for the semi-automatic TAG and 0.557 for the manual TAG. TAG and CCTA combined resulted in AUCs of 0.567, 0.562 for semi-automatic TAG, and 0.569 for the manual TAG. Conclusion The results from our study showed no incremental value of TAG measured in single heartbeat CCTA in determining the severity of coronary artery stenosis degrees.

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  • 25.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI2021In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 54, no 3, p. 777-786Article in journal (Refereed)
    Abstract [en]

    Background Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications. Purpose To develop and evaluate a deep learning architecture to generate high blood-tissue contrast in noncontrast 4D flow MRI by emulating the use of an external contrast agent. Study Type Retrospective. Subjects Of 222 data sets, 141 were used for neural network (NN) training (69 with and 72 without contrast agent). Evaluation was performed on the remaining 81 noncontrast data sets. Field Strength/Sequences Gradient echo or echo-planar 4D flow MRI at 1.5 T and 3 T. Assessment A cyclic generative adversarial NN was trained to perform image translation between noncontrast and contrast data. Evaluation was performed quantitatively using contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), structural similarity index (SSIM), mean squared error (MSE) of edges, and Dice coefficient of segmentations. Three observers performed a qualitative assessment of blood-tissue contrast, noise, presence of artifacts, and image structure visualization. Statistical Tests The Wilcoxon rank-sum test evaluated statistical significance. Kendalls concordance coefficient assessed interobserver agreement. Results Contrast in the regions of interest (ROIs) in the NN enhanced images increased by 88%, CNR increased by 63%, and SNR improved by 48% (all P &lt; 0.001). The SSIM was 0.82 +/- 0.01, and the MSE of edges was 0.09 +/- 0.01 (range [0,1]). Segmentations based on the generated images resulted in a Dice similarity increase of 15.25%. The observers managed to differentiate between contrast MR images and our results; however, they preferred the NN enhanced images in 76.7% of cases. This percentage increased to 93.3% for phase-contrast MR angiograms created from the NN enhanced data. Visual grading scores were blood-tissue contrast = 4.30 +/- 0.74, noise = 3.12 +/- 0.98, and presence of artifacts = 3.63 +/- 0.76. Image structures within and without the ROIs resulted in scores of 3.42 +/- 0.59 and 3.07 +/- 0.71, respectively (P &lt; 0.001). Data Conclusion The proposed approach improves blood-tissue contrast in MR images and could be used to improve data quality, visualization, and postprocessing of cardiovascular 4D flow data. Evidence Level 3 Technical Efficacy Stage 1

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  • 26.
    Garg, Pankaj
    et al.
    Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK..
    Swift, Andrew J
    Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK.
    Zhong, Liang
    National Heart Centre Singapore, Duke-NUS Medical School, National University of Singapore, Singapore,.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Westenberg, Jos
    Department of Radiology, Leiden University Medical Center, Leiden, Netherlands.
    Hope, Michael D
    Department of Radiology, University of California-San Francisco, San Francisco, CA, USA.
    Bucciarelli-Ducci, Chiara
    Bristol Heart Institute, Bristol National Institute of Health Research (NIHR) Biomedical Research Centre, University Hospitals Bristol NHS Trust and University of Bristol, Bristol, UK.
    Bax, Jeroen J
    Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands.
    Myerson, Saul G
    Departments of Cardiology and Cardiovascular Medicine, University of Oxford Centre for Clinical Magnetic Resonance Research, John Radcliffe Hospital, Oxford, UK.
    Assessment of mitral valve regurgitation by cardiovascular magnetic resonance imaging2020In: Nature Reviews Cardiology, ISSN 1759-5002, E-ISSN 1759-5010, Vol. 17, no 5, p. 298-312Article in journal (Refereed)
    Abstract [en]

    Mitral regurgitation (MR) is a common valvular heart disease and is the second most frequent indication for heart valve surgery in Western countries. Echocardiography is the recommended first-line test for the assessment of valvular heart disease, but cardiovascular magnetic resonance imaging (CMR) provides complementary information, especially for assessing MR severity and to plan the timing of intervention. As new CMR techniques for the assessment of MR have arisen, standardizing CMR protocols for research and clinical studies has become important in order to optimize diagnostic utility and support the wider use of CMR for the clinical assessment of MR. In this Consensus Statement, we provide a detailed description of the current evidence on the use of CMR for MR assessment, highlight its current clinical utility, and recommend a standardized CMR protocol and report for MR assessment.

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  • 27.
    Kihlberg, Johan
    et al.
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Gupta, Vikas
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences.
    Haraldsson, Henrik
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, USA.
    Sigfridsson, Andreas
    Department of Clinical Physiology & Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital, 17176, Stockholm, Sweden.
    Sarvari, Sebastian I
    Department of Cardiology, Oslo University Hospital, Rikshospitalet, 0316, Oslo, Norway.
    Ebbers, Tino
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine.
    Engvall, Jan
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Clinical validation of three cardiovascular magnetic resonance techniques to measure strain and torsion in patients with suspected coronary artery disease2020In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 22, no 83Article in journal (Refereed)
    Abstract [en]

    BackgroundSeveral cardiovascular magnetic resonance (CMR) techniques can measure myocardial strain and torsion with high accuracy. The purpose of this study was to compare displacement encoding with stimulated echoes (DENSE), tagging and feature tracking (FT) for measuring circumferential and radial myocardial strain and myocardial torsion in order to assess myocardial function and infarct scar burden both at a global and at a segmental level.

    Method116 patients with a high likelihood of coronary artery disease (European SCORE > 15%) underwent CMR examination including cine images, tagging, DENSE and late gadolinium enhancement (LGE) in the short axis direction. In total, 97 patients had signs of myocardial disease and 19 had no abnormalities in terms of left ventricular (LV) wall mass index, LV ejection fraction, wall motion, LGE or a history of myocardial infarction. Thirty-four patients had myocardial infarct scar with a transmural LGE extent (transmurality) that exceeded 50% of the wall thickness in at least one segment. Global circumferential strain (GCS) and global radial strain (GRS) was analyzed using FT of cine loops, deformation of tag lines or DENSE displacement.

    ResultsDENSE and tagging both showed high sensitivity (82% and 71%) at a specificity of 80% for the detection of segments with > 50% LGE transmurality, and receiver operating characteristics (ROC) analysis showed significantly higher area under the curve-values (AUC) for DENSE (0.87) than for tagging (0.83, p < 0.001) and FT (0.66, p = 0.003). GCS correlated with global LGE when determined with DENSE (r = 0.41), tagging (r = 0.37) and FT (r = 0.15). GRS had a low but significant negative correlation with LGE; DENSE r = − 0.10, FT r = − 0.07 and tagging r = − 0.16. Torsion from DENSE and tagging had a weak correlation (− 0.20 and − 0.22 respectively) with global LGE.

    ConclusionCircumferential strain from DENSE detected segments with > 50% scar with a higher AUC than strain determined from tagging and FT at a segmental level. GCS and torsion computed from DENSE and tagging showed similar correlation with global scar size, while when computed from FT, the correlation was lower.

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  • 28.
    Viola, Federica
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Data Quality and Optimal Background Correction Order of Respiratory-Gated k-Space Segmented Spoiled Gradient Echo (SGRE) and Echo Planar Imaging (EPI)-Based 4D Flow MRI2020In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 51, no 3, p. 885-896Article in journal (Refereed)
    Abstract [en]

    Background A reduction in scan time of 4D Flow MRI would facilitate clinical application. A recent study indicates that echo-planar imaging (EPI) 4D Flow MRI allows for a reduction in scan time and better data quality than the recommended k-space segmented spoiled gradient echo (SGRE) sequence. It was argued that the poor data quality of SGRE was related to the nonrecommended absence of respiratory motion compensation. However, data quality can also be affected by the background offset compensation. Purpose To compare the data quality of respiratory motion-compensated SGRE and EPI 4D Flow MRI and their dependence on background correction (BC) order. Study Type Retrospective. Subjects Eighteen healthy subjects (eight female, mean age 32 +/- 5 years). Field Strength and Sequence 5T. SGRE and EPI-based 4D Flow MRI. Assessment Data quality was investigated visually and by comparing flows through the cardiac valves and aorta. Measurements were obtained from transvalvular flow and pathline analysis. Statistical Tests Linear regression and Bland-Altman analysis were used. Wilcoxon test was used for comparison of visual scoring. Students t-test was used for comparison of flow volumes. Results No significant difference was found by visual inspection (P = 0.08). Left ventricular (LV) flows were strongly and very strongly associated with SGRE and EPI, respectively (R-2 = 0.86-0.94 SGRE; 0.71-0.79 EPI, BC0-4). LV and right ventricular (RV) outflows and LV pathline flows were very strongly associated (R-2 = 0.93-0.95 SGRE; 0.88-0.91 EPI, R-2 = 0.91-0.95 SGRE; 0.91-0.93 EPI, BC1-4). EPI LV outflow was lower than the short-axis-based stroke volume. EPI RV outflow and proximal descending aortic flow were lower than SGREs. Data Conclusion Both sequences yielded good internal data consistency when an adequate background correction was applied. Second and first BC order were considered sufficient for transvalvular flow analysis in SGRE and EPI, respectively. Higher BC orders were preferred for particle tracing. Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2019.

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  • 29.
    Sundin, Jonathan
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engvall, Jan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Nylander, Eva
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bolger, Ann F
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV). Univ Calif San Francisco, CA 94143 USA.
    Carlhäll, Carljohan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Improved Efficiency of Intraventricular Blood Flow Transit Under Cardiac Stress: A 4D Flow Dobutamine CMR Study2020In: Frontiers in cardiovascular medicine, ISSN 2297-055X, Vol. 7, article id 581495Article in journal (Refereed)
    Abstract [en]

    Introduction: The effects of heart rate, inotropy, and lusitropy on multidimensional flow patterns and energetics within the human heart remain undefined. Recently, reduced volume and end-diastolic kinetic energy (KE) of the portion of left ventricular (LV) inflow passing directly to outflow, Direct flow (DF), have been shown to reflect inefficient LV pumping and to be a marker of LV dysfunction in heart failure patients. In this study, we hypothesized that increasing heart rate, inotropy, and lusitropy would result in an increased efficiency of intraventricular blood flow transit. Therefore, we sought to investigate LV 4D blood flow patterns and energetics with dobutamine infusion. Methods: 4D flow and morphological cardiovascular magnetic resonance (CMR) data were acquired in twelve healthy subjects: at rest and with dobutamine infusion to achieve a target heart rate similar to 60% higher than the resting heart rate. A previously validated method was used for flow analysis: pathlines were emitted from the end-diastolic (ED) LV blood volume and traced forward and backward in time to separate four functional LV flow components. For each flow component, KE/mL blood volume at ED was calculated. Results: With dobutamine infusion there was an increase in heart rate (64%, p &lt; 0.001), systolic blood pressure (p = 0.02) and stroke volume (p = 0.01). Of the 4D flow parameters, the most efficient flow component (DF), increased its proportion of EDV (p &lt; 0.001). The EDV proportion of Residual volume, the blood residing in the ventricle over at least two cardiac cycles, decreased (p &lt; 0.001). The KE/mL at ED for all flow components increased (p &lt; 0.001). DF had the largest absolute and relative increase while Residual volume had the smallest absolute and relative increase. Conclusions: This study demonstrates that it is feasible to compare 4D flow patterns within the normal human heart at rest and with stress. At higher heart rate, inotropy and lusitropy, elicited by dobutamine infusion, the efficiency of intraventricular blood flow transit improves, as quantified by an increased relative volume and pre-systolic KE of the most efficient DF component of the LV volume. The change in these markers may allow a novel assessment of LV function and LV dysfunction over a range of stress.

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  • 30.
    Ha, Hojin
    et al.
    Kangwon Natl Univ, South Korea.
    Park, Kyung Jin
    Yonsei Univ, South Korea; Univ Ulsan, South Korea.
    Dyverfeldt, Petter
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Yang, Dong Hyun
    University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea.
    In vitro experiments on ICOSA6 4D flow MRI measurement for the quantification of velocity and turbulence parameters2020In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 72, p. 49-60Article in journal (Refereed)
    Abstract [en]

    Purpose: To perform comprehensive in vitro experiments using six-directional icosahedral flow encoding (ICOSA6) 4D flow magnetic resonance imaging (MRI) under various scan conditions to analyze the robustness of velocity and turbulence quantification. Materials and methods: In vitro flow phantoms with steady flow rates of 10 and 20 L/min were scanned using both conventional 4D flow MRI and ICOSA6. Experiments focused on comparisons between ICOSA6 and conventional four point (4P) methods, and the effects of contrast agents, velocity encoding range (Venc), and scan direction on velocity and turbulence quantification. Results: The results demonstrated that 1) ICOSA6 improves the velocity-to-noise ratio (VNR) of velocity estimation by 33% (on average) and results in similar turbulent kinetic energy (TKE) estimation as the 4P method. 2) Measurements with a contrast agent resulted in more than a 2.5 fold increase in average VNR. However, the improvement of total TKE quantification was not obvious. 3) TKE estimation was less affected by Venc and the scan direction, whereas turbulence production (TP) estimation was largely affected by these measurement conditions. The effects of Venc and scan direction accounted for less than 11.63% of TKE estimation, but up to 33.89% of TP estimation. Conclusion: The ICOSA6 scheme is compatible with conventional 4D flow MRI for velocity and TKE measurement. Contrast agents are effective at increasing VNR, but not signal-to-noise ratio for TKE quantification. The effects of Venc and scan direction influence total TP more than total TKE.

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  • 31.
    Marlevi, David
    et al.
    KTH Royal Inst Technol, Sweden; Karolinska Inst, Sweden.
    Ha, Hojin
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Kangwon Natl Univ, South Korea.
    Dillon-Murphy, Desmond
    Kings Coll London, England.
    Fernandes, Joao F.
    Kings Coll London, England.
    Fovargue, Daniel
    Kings Coll London, England.
    Colarieti-Tosti, Massimiliano
    KTH Royal Inst Technol, Sweden.
    Larsson, Matilda
    KTH Royal Inst Technol, Sweden.
    Lamata, Pablo
    Kings Coll London, England.
    Figueroa, C. Alberto
    Kings Coll London, England; Univ Michigan, MI 48109 USA.
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Nordsletten, David A.
    Kings Coll London, England; Univ Michigan, MI 48109 USA.
    Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy2020In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 60, article id 101627Article in journal (Refereed)
    Abstract [en]

    Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, nu WERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: nu WERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. nu WERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patientspecific in-silico model of an acute aortic dissection. Over all tests nu WERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original nu WERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended nu WERP-t further enlarges the methods clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo. (C) 2019 The Authors. Published by Elsevier B.V.

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  • 32.
    Casas Garcia, Belén
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Viola, Federica
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Cedersund, Gunnar
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Bolger, Ann F.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping. Department of Medicine, University of California San Francisco, San Francisco, California, USA.
    Carlhäll, Carl-Johan
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart Center, Department of Clinical Physiology in Linköping.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Publisher Correction: Bridging the gap between measurements and modelling: a cardiovascular functional avatar2020In: Scientific Reports, E-ISSN 2045-2322, Vol. 10, no 1Article in journal (Other academic)
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  • 33.
    Ha, Hojin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Kangwon Natl Univ, South Korea.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Linköping University, Center for Medical Image Science and Visualization (CMIV). Oslo Univ Hosp, Norway.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    4D Flow MRI quantification of blood flow patterns, turbulence and pressure drop in normal and stenotic prosthetic heart valves2019In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 55, p. 118-127Article in journal (Refereed)
    Abstract [en]

    Purpose: To assess valvular flow characteristics and pressure drop in a variety of normal and stenotic prosthetic heart valves (PHVs) using 4D Flow MRI. Materials and methods: In-vitro flow phantoms with four different PHVs were studied: Medtronic-Hall tilting disc, St. Jude Medical standard bileaflet (STJM), Medtronic CoreValve Evolut R and Edwards SAPIEN 3. The valvular flow characteristics were investigated in normal and stenotic PHVs by using 4D Flow MRI. Results: The results showed that each valve provided a different amount of signal loss in the 4D Flow MRI. The defect size of the signal loss from each valve was 37.5 mm, 39.0 mm, 37.5 mm and 51.0 mm for the Tilting disk, STJM, SAPIEN 3 and CoreValve, respectively. The 4D Flow MRI-based estimation of the elevation of the pressure drop through the stenotic PHV using both Bernoulli-based and turbulence-based methods correlated well with the true values for the Tilting disc, STJM and SAPIEN 3 valve. However, the obstructive hemodynamics in the stenotic CoreValve was not clearly identified due to the large signal void from the long struts, resulting in a severe underestimation of the pressure drop using 4D Flow MRI. Conclusion: The Tilting disc, STJM and SAPIEN 3 valves provided reasonable estimates of peak velocity, turbulence production and the corresponding pressure drop. In contrast, the large strut of the CoreValve and corresponding signal void prevented accurate measurements of the velocity and turbulence production; therefore, 4D Flow MRI prediction of the pressure drop through the CoreValve was not feasible.

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  • 34.
    Andersson, Magnus
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Characterization and estimation of turbulence-related wall shear stress in patient-specific pulsatile blood flow2019In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 85, p. 108-117Article in journal (Refereed)
    Abstract [en]

    Disturbed, turbulent-like blood flow promotes chaotic wall shear stress (WSS) environments, impairing essential endothelial functions and increasing the susceptibility and progression of vascular diseases. These flow characteristics are today frequently detected at various anatomical, lesion and intervention-related sites, while their role as a pathological determinant is less understood. To present-day, numerous WSS-based descriptors have been proposed to characterize the spatiotemporal nature of the WSS disturbances, however, without differentiation between physiological laminar oscillations and turbulence-related WSS (tWSS) fluctuations. Also, much attention has been focused on magnetic resonance (MR) WSS estimations, so far with limited success; promoting the need of a near-wall surrogate marker. In this study, a new approach is explored to characterize the tWSS, by taking advantage of the tensor characteristics of the fluctuating WSS correlations, providing both a magnitude and an anisotropy measure of the disturbances. These parameters were studied in two patient-specific coarctation models (sever and mild), using large eddy simulations, and correlated against near-wall reciprocal Reynolds stress parameters. Collectively, results showed distinct regions of differing tWSS characteristics, features which were sensitive to changes in flow conditions. Generally, the post-stenotic tWSS was governed by near axisymmetric fluctuations, findings that where not consistent with conventional WSS disturbance predictors. At the 2-3 mm wall-offset range, a strong linear correlation was found between tWSS magnitude and near-wall turbulence kinetic energy (TKE), in contrast to the anisotropy indices, suggesting that MR-measured TKE can be used to assess elevated tWSS regions while tWSS anisotropy estimates request well-resolved simulation methods. (C) 2019 Elsevier Ltd. All rights reserved.

  • 35.
    Lantz, Jonas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Gupta, Vikas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Henriksson, Lilian
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Carlhäll, Carl-Johan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Faculty of Medicine and Health Sciences.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Impact of Pulmonary Venous Inflow on Cardiac Flow Simulations: Comparison with In Vivo 4D Flow MRI2019In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 47, no 2, p. 413-424Article in journal (Refereed)
    Abstract [en]

    Blood flow simulations are making their way into the clinic, and much attention is given to estimation of fractional flow reserve in coronary arteries. Intracardiac blood flow simulations also show promising results, and here the flow field is expected to depend on the pulmonary venous (PV) flow rates. In the absence of in vivo measurements, the distribution of the flow from the individual PVs is often unknown and typically assumed. Here, we performed intracardiac blood flow simulations based on time-resolved computed tomography on three patients, and investigated the effect of the distribution of PV flow rate on the flow field in the left atrium and ventricle. A design-of-experiment approach was used, where PV flow rates were varied in a systematic manner. In total 20 different simulations were performed per patient, and compared to in vivo 4D flow MRI measurements. Results were quantified by kinetic energy, mitral valve velocity profiles and root-mean-square errors of velocity. While large differences in atrial flow were found for varying PV inflow distributions, the effect on ventricular flow was negligible, due to a regularizing effect by mitral valve. Equal flow rate through all PVs most closely resembled in vivo measurements and is recommended in the absence of a priori knowledge.

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  • 36.
    Zhong, Liang
    et al.
    Natl Heart Ctr Singapore, Singapore; Natl Univ Singapore, Singapore.
    Schrauben, Eric M.
    Hosp Sick Children, Canada.
    Garcia, Julio
    Univ Calgary, Canada.
    Uribe, Sergio
    Pontificia Univ Catolica Chile, Chile.
    Grieve, Stuart M.
    Univ Sydney, Australia; Royal Prince Alfred Hosp, Australia.
    Elbaz, Mohammed S. M.
    Northwestern Univ, IL 60611 USA.
    Barker, Alex J.
    Univ Colorado, CO 80202 USA.
    Geiger, Julia
    Univ Childrens Hosp Zurich, Switzerland.
    Nordmeyer, Sarah
    German Heart Ctr, Germany; Charite, Germany.
    Marsden, Alison
    Stanford Univ, CA 94305 USA.
    Carlsson, Marcus
    Lund Univ, Sweden.
    Tan, Ru-San
    Natl Heart Ctr Singapore, Singapore; Natl Univ Singapore, Singapore.
    Garg, Pankaj
    Univ Sheffield, England.
    Westenberg, Jos J. M.
    Leiden Univ, Netherlands.
    Markl, Michael
    Northwestern Univ, IL 60611 USA.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group2019In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 50, no 3, p. 677-681Article in journal (Refereed)
    Abstract [en]

    Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

  • 37.
    Stoll, Victoria M.
    et al.
    Univ Oxford, England.
    Hess, Aaron T.
    Univ Oxford, England.
    Rodgers, Christopher T.
    Univ Oxford, England; Univ Cambridge, England.
    Bissell, Malenka M.
    Univ Oxford, England.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Myerson, Saul G.
    Univ Oxford, England.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Neubauer, Stefan
    Univ Oxford, England.
    Left Ventricular Flow Analysis Novel Imaging Biomarkers and Predictors of Exercise Capacity in Heart Failure2019In: Circulation Cardiovascular Imaging, ISSN 1941-9651, E-ISSN 1942-0080, Vol. 12, no 5Article in journal (Refereed)
    Abstract [en]

    Background: Cardiac remodeling, after a myocardial insult, often causes progression to heart failure. The relationship between alterations in left ventricular blood flow, including kinetic energy (KE), and remodeling is uncertain. We hypothesized that increasing derangements in left ventricular blood flow would relate to (1) conventional cardiac remodeling markers, (2) increased levels of biochemical remodeling markers, (3) altered cardiac energetics, and (4) worsening patient symptoms and functional capacity. Methods: Thirty-four dilated cardiomyopathy patients, 30 ischemic cardiomyopathy patients, and 36 controls underwent magnetic resonance including 4-dimensional flow, BNP (brain-type natriuretic peptide) measurement, functional capacity assessment (6-minute walk test), and symptom quantification. A subgroup of dilated cardiomyopathy and control subjects underwent cardiac energetic assessment. Left ventricular flow was separated into 4 components: direct flow, retained inflow, delayed ejection flow, and residual volume. Average KE throughout the cardiac cycle was calculated. Results: Patients had reduced direct flow proportion and direct-flow average KE compared with controls (Pamp;lt;0.0001). The residual volume proportion and residual volume average KE were increased in patients (Pamp;lt;0.0001). Importantly, in a multiple linear regression model to predict the patients 6-minute walk test, the independent predictors were age (beta=-0.3015; P=0.019) and direct-flow average KE (beta=0.280, P=0.035; R-2 model, 0.466, P=0.002). In contrast, neither ejection fraction nor left ventricular volumes were independently predictive. Conclusions: This study demonstrates an independent predictive relationship between the direct-flow average KE and a prognostic measure of functional capacity. Intracardiac 4-dimensional flow parameters are novel biomarkers in heart failure and may provide additive value in monitoring new therapies and predicting prognosis.

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  • 38.
    Peolsson, Anneli
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Anette
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ghafouri, Bijar
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Engström, Maria
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Jönsson, Margaretha
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences. Herrgardets Vardcentral, Sweden.
    Wåhlén, Karin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Pain and Rehabilitation Center.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kristjansson, Eythor
    Univ Iceland, Iceland.
    Bahat, Hilla Sarig
    Univ Haifa, Israel.
    German, Dmitry
    Univ Haifa, Israel.
    Zsigmond, Peter
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
    Peterson, Gunnel
    Linköping University, Department of Medical and Health Sciences, Division of Physiotherapy. Linköping University, Faculty of Medicine and Health Sciences. Uppsala Univ, Sweden.
    Pathophysiology behind prolonged whiplash associated disorders: study protocol for an experimental study2019In: BMC Musculoskeletal Disorders, ISSN 1471-2474, E-ISSN 1471-2474, Vol. 20, article id 51Article in journal (Refereed)
    Abstract [en]

    BackgroundThere is insufficient knowledge of pathophysiological parameters to understand the mechanism behind prolonged whiplash associated disorders (WAD), and it is not known whether or not changes can be restored by rehabilitation. The aims of the projects are to investigate imaging and molecular biomarkers, cervical kinaesthesia, postural sway and the association with pain, disability and other outcomes in individuals with longstanding WAD, before and after a neck-specific exercise intervention. Another aim is to compare individuals with WAD with healthy controls.MethodsParticipants are a sub-group (n=30) of individuals recruited from an ongoing randomized controlled study (RCT). Measurements in this experimental prospective study will be carried out at baseline (before intervention) and at a three month follow-up (end of physiotherapy intervention), and will include muscle structure and inflammation using magnetic resonance imaging (MRI), brain structure and function related to pain using functional MRI (fMRI), muscle function using ultrasonography, biomarkers using samples of blood and saliva, cervical kinaesthesia using the butterfly test and static balance test using an iPhone app. Association with other measures (self-reported and clinical measures) obtained in the RCT (e.g. background data, pain, disability, satisfaction with care, work ability, quality of life) may be investigated. Healthy volunteers matched for age and gender will be recruited as controls (n=30).DiscussionThe study results may contribute to the development of improved diagnostics and improved rehabilitation methods for WAD.Trial registrationClinicaltrial.gov Protocol ID: NCT03664934, initial release 09/11/2018.

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  • 39.
    Karlsson, Lars
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Cardiology in Linköping.
    Erixon, Hanna
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Bolger, Ann
    Univ Calif San Francisco, CA USA.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Post-cardioversion Improvement in LV Function Defined by 4D Flow Patterns and Energetics in Patients With Atrial Fibrillation2019In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 10, article id 659Article in journal (Refereed)
    Abstract [en]

    Background: Atrial fibrillation (AF) is a prevalent cause of cardiovascular morbidity, including thromboembolism and heart failure. Left ventricular dysfunction (LVD) detected in AF patients may be either precursor or consequence of the arrythmia. Successful cardioversion of chronic AF is often followed by a transient period of left atrial (LA) stunning, where depressed mechanical atrial contraction persists despite reinstitution of sinus rhythm. To determine if AF-associated LVD would improve with resolution of LA dysfunction, AF patients were examined immediately and 4 weeks after cardioversion to sinus rhythm. 4D flow cardiovascular magnetic resonance (CMR) assesses ventricular function according to the volumes and energetics of functional components of the LV volume. Previously, described 4D CMR markers of LVD include decreased volume and end-diastolic kinetic energy (KE) of the Direct flow, which is the portion of LV volume that passes directly from inflow to outflow in a single cycle. We hypothesize that impaired LV flow patterns and energetics will be found immediately after cardioversion during atrial stunning, and that those parameters will improve as atrial function returns. Methods: Ten patients with a history of AF underwent CMR 2-3 h (Time-1) and 4 weeks (time-2), following electrical cardioversion to sinus rhythm. 4D phase-contrast velocity data and morphological images were acquired at a 3T CMR system. Using a previously evaluated method, pathlines were emitted from the LV end diastolic volume (LVEDV) and traced forward and backward in time until end-systole. The LVEDV was automatically separated into four functional flow components whose volume and KE were calculated. Results: Left atrial fractional area change increased over the follow-up period (P = 0.001), indicating recovery of LA mechanical function. LVEF increased between Time-1 and Time-2 (P = 0.003); LVEDVI did not change (P = 0.319). Over that interval, the ratios of Direct flow/LVEDV volume and KE increased (P = 0.001 and P = 0.003, respectively), while the ratios of Residual volume/LVEDV volume and KE decreased (P = 0.001 and P = 0.005, respectively). Conclusion: Post-cardioversion recovery of LA function was associated with improvements in conventional and 4D CMR markers of LV function. Flow-specific measures demonstrate the negative but potentially reversible impact of LA dysfunction on volume and energetic aspects of LV function.

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  • 40.
    Ha, Hojin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, Republic of Korea.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Department of Cardiothoracic Surgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Validation of pressure drop assessment using 4D flow MRI-based turbulence production in various shapes of aortic stenoses2019In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 81, no 2, p. 893-906Article in journal (Refereed)
    Abstract [en]

    Purpose

    To validate pressure drop measurements using 4D flow MRI‐based turbulence production in various shapes of stenotic stenoses.

    Methods

    In vitro flow phantoms with seven different 3D‐printed aortic valve geometries were constructed and scanned with 4D flow MRI with six‐directional flow encoding (ICOSA6). The pressure drop through the valve was non‐invasively predicted based on the simplified Bernoulli, the extended Bernoulli, the turbulence production, and the shear‐scaling methods. Linear regression and agreement of the predictions with invasively measured pressure drop were analyzed.

    Results

    All pressure drop predictions using 4D Flow MRI were linearly correlated to the true pressure drop but resulted in different regression slopes. The regression slope and 95% limits of agreement for the simplified Bernoulli method were 1.35 and 11.99 ± 21.72 mm Hg. The regression slope and 95% limits of agreement for the extended Bernoulli method were 1.02 and 0.74 ± 8.48 mm Hg. The regression slope and 95% limits of agreement for the turbulence production method were 0.89 and 0.96 ± 8.01 mm Hg. The shear‐scaling method presented good correlation with an invasively measured pressure drop, but the regression slope varied between 0.36 and 1.00 depending on the shear‐scaling coefficient.

    Conclusion

    The pressure drop assessment based on the turbulence production method agrees well with the extended Bernoulli method and invasively measured pressure drop in various shapes of the aortic valve. Turbulence‐based pressure drop estimation can, as a complement to the conventional Bernoulli method, play a role in the assessment of valve diseases.

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  • 41.
    Ziegler, Magnus
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Welander, Martin
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lindenberger, Marcus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Cardiology in Linköping.
    Bjarnegård, Niclas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Länne, Toste
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Visualizing and quantifying flow stasis in abdominal aortic aneurysms in men using 4D flow MRI2019In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 57, p. 103-110Article in journal (Refereed)
    Abstract [en]

    Purpose: To examine methods for visualizing and quantifying flow stasis in abdominal aortic aneurysms (AAA) using 4D Flow MRI. Methods: Three methods were investigated: conventional volumetric residence time (VRT), mean velocity analysis (MVA), and particle travel distance analysis (TDA). First, ideal 4D Flow MRI data was generated using numerical simulations and used as a platform to explore the effects of noise and background phase-offset errors, both of which are common 4D Flow MRI artifacts. Error-free results were compared to noise or offset affected results using linear regression. Subsequently, 4D Flow MRI data for thirteen (13) subjects with AAA was acquired and used to compare the stasis quantification methods against conventional flow visualization. Results: VRT (R-2 = 0.69) was more sensitive to noise than MVA (R-2 = 0.98) and TDA (R-2 = 0.99) at typical noncontrast signal-to-noise ratio levels (SNR = 20). VRT (R-2 = 0.14) was more sensitive to background phase-offsets than MVA (R-2 = 0.99) and TDA (R-2 = 0.96) when considering a 95% effective background phase-offset correction. Qualitatively, TDA outperformed MVA (Wilcoxon p amp;lt; 0.005, mean score improvement 1.6/5), and had good agreement (median score 4/5) with flow visualizations. Conclusion: Flow stasis can be quantitatively assessed using 4D Flow MRI. While conventional residence time calculations fail due to error accumulation as a result of imperfect measured velocity fields, methods that do not require lengthy particle tracking perform better. MVA and TDA are less sensitive to measurement errors, and TDA generates results most similar to those obtained using conventional flow visualization.

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  • 42.
    Ha, Hojin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Kangwon Natl Univ, South Korea.
    Ziegler, Magnus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Welander, Martin
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Bjarnegård, Niclas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lindenberger, Marcus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Cardiology in Linköping.
    Länne, Toste
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Age-Related Vascular Changes Affect Turbulence in Aortic Blood Flow2018In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 36Article in journal (Refereed)
    Abstract [en]

    Turbulent blood flow is implicated in the pathogenesis of several aortic diseases but the extent and degree of turbulent blood flow in the normal aorta is unknown. We aimed to quantify the extent and degree of turbulece in the normal aorta and to assess whether age impacts the degree of turbulence. 22 young normal males (23.7 +/- 3.0 y.o.) and 20 old normal males (70.9 +/- 3.5 y.o.) were examined using four dimensional flow magnetic resonance imaging (4D Flow MRI) to quantify the turbulent kinetic energy (TKE), a measure of the intensity of turbulence, in the aorta. All healthy subjects developed turbulent flow in the aorta, with total TKE of 3-19 mJ. The overall degree of turbulence in the entire aorta was similar between the groups, although the old subjects had about 73% more total TKE in the ascending aorta compared to the young subjects (young = 3.7 +/- 1.8 mJ, old = 6.4 +/- 2.4 mJ, p amp;lt; 0.001). This increase in ascending aorta TKE in old subjects was associated with age-related dilation of the ascending aorta which increases the volume available for turbulence development. Conversely, age-related dilation of the descending and abdominal aorta decreased the average flow velocity and suppressed the development of turbulence. In conclusion, turbulent blood flow develops in the aorta of normal subjects and is impacted by age-related geometric changes. Non-invasive assessment enables the determination of normal levels of turbulent flow in the aorta which is a prerequisite for understanding the role of turbulence in the pathophysiology of cardiovascular disease.

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  • 43.
    Haraldsson, Henrik
    et al.
    Univ Calif San Francisco, CA 94143 USA.
    Kefayati, Sarah
    Univ Calif San Francisco, CA 94143 USA.
    Ahn, Sinyeob
    Siemens Healthcare, Germany.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Laub, Gerhard
    Siemens Healthcare, Germany.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Saloner, David
    Univ Calif San Francisco, CA 94143 USA; Vet Affairs Med Ctr, CA 94121 USA.
    Assessment of Reynolds stress components and turbulent pressure loss using 4D flow MRI with extended motion encoding2018In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 79, no 4, p. 1962-1971Article in journal (Refereed)
    Abstract [en]

    PurposeTo measure the Reynolds stress tensor using 4D flow MRI, and to evaluate its contribution to computed pressure maps. MethodsA method to assess both velocity and Reynolds stress using 4D flow MRI is presented and evaluated. The Reynolds stress is compared by cross-sectional integrals of the Reynolds stress invariants. Pressure maps are computed using the pressure Poisson equationboth including and neglecting the Reynolds stress. ResultGood agreement is seen for Reynolds stress between computational fluid dynamics, simulated MRI, and MRI experiment. The Reynolds stress can significantly influence the computed pressure loss for simulated (eg, -0.52% vs -15.34% error; Pamp;lt;0.001) and experimental (eg, 30611 vs 203 +/- 6 Pa; Pamp;lt;0.001) data. A 54% greater pressure loss is seen at the highest experimental flow rate when accounting for Reynolds stress (Pamp;lt;0.001). Conclusion4D flow MRI with extended motion-encoding enables quantification of both the velocity and the Reynolds stress tensor. The additional information provided by this method improves the assessment of pressure gradients across a stenosis in the presence of turbulence. Unlike conventional methods, which are only valid if the flow is laminar, the proposed method is valid for both laminar and disturbed flow, a common presentation in diseased vessels. Magn Reson Med 79:1962-1971, 2018. (c) 2017 International Society for Magnetic Resonance in Medicine.

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  • 44.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Gupta, Vikas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Forsberg, Daniel
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra, Linköping, Sweden.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Automated multi-atlas segmentation of cardiac 4D flow MRI2018In: Medical Image Analysis, ISSN 1361-8415, E-ISSN 1361-8423, Vol. 49, p. 128-140Article in journal (Refereed)
    Abstract [en]

    Four-dimensional (4D) flow magnetic resonance imaging (4D Flow MRI) enables acquisition of time-resolved three-directional velocity data in the entire heart and all major thoracic vessels. The segmentation of these tissues is typically performed using semi-automatic methods. Some of which primarily rely on the velocity data and result in a segmentation of the vessels only during the systolic phases. Other methods, mostly applied on the heart, rely on separately acquired balanced Steady State Free Precession (b-SSFP) MR images, after which the segmentations are superimposed on the 4D Flow MRI. While b-SSFP images typically cover the whole cardiac cycle and have good contrast, they suffer from a number of problems, such as large slice thickness, limited coverage of the cardiac anatomy, and being prone to displacement errors caused by respiratory motion. To address these limitations we propose a multi-atlas segmentation method, which relies only on 4D Flow MRI data, to automatically generate four-dimensional segmentations that include the entire thoracic cardiovascular system present in these datasets. The approach was evaluated on 4D Flow MR datasets from a cohort of 27 healthy volunteers and 83 patients with mildly impaired systolic left-ventricular function. Comparison of manual and automatic segmentations of the cardiac chambers at end-systolic and end-diastolic timeframes showed agreements comparable to those previously reported for automatic segmentation methods of b-SSFP MR images. Furthermore, automatic segmentation of the entire thoracic cardiovascular system improves visualization of 4D Flow MRI and facilitates computation of hemodynamic parameters.

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  • 45.
    Gupta, Vikas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Henriksson, Lilian
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Persson, Anders
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Radiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Automated three-dimensional tracking of the left ventricular myocardium in time-resolved and dose-modulated cardiac CT images using deformable image registration2018In: Journal of Cardiovascular Computed Tomography, ISSN 1934-5925, Vol. 12, no 2, p. 139-148Article in journal (Refereed)
    Abstract [en]

    Background Assessment of myocardial deformation from time-resolved cardiac computed tomography (4D CT) would augment the already available functional information from such an examination without incurring any additional costs. A deformable image registration (DIR) based approach is proposed to allow fast and automatic myocardial tracking in clinical 4D CT images.

    Methods Left ventricular myocardial tissue displacement through a cardiac cycle was tracked using a B-spline transformation based DIR. Gradient of such displacements allowed Lagrangian strain estimation with respect to end-diastole in clinical 4D CT data from ten subjects with suspected coronary artery disease. Dice similarity coefficient (DSC), point-to-curve error (PTC), and tracking error were used to assess the tracking accuracy. Wilcoxon signed rank test provided significance of tracking errors. Topology preservation was verified using Jacobian of the deformation. Reliability of estimated strains and torsion (normalized twist angle) was tested in subjects with normal function by comparing them with normal strain in the literature.

    Results Comparison with manual tracking showed high accuracy (DSC: 0.99± 0.05; PTC: 0.56mm± 0.47 mm) and resulted in determinant(Jacobian) > 0 for all subjects, indicating preservation of topology. Average radial (0.13 mm), angular (0.64) and longitudinal (0.10 mm) tracking errors for the entire cohort were not significant (p > 0.9). For patients with normal function, average strain [circumferential, radial, longitudinal] and peak torsion estimates were: [-23.5%, 31.1%, −17.2%] and 7.22°, respectively. These estimates were in conformity with the reported normal ranges in the existing literature.

    Conclusions Accurate wall deformation tracking and subsequent strain estimation are feasible with the proposed method using only routine time-resolved 3D cardiac CT.

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  • 46.
    Gaeta, Stephen
    et al.
    Duke Univ, NC USA.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Eriksson, Jonatan
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Bolger, Ann F
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Univ Calif San Francisco, CA 94143 USA.
    Fixed volume particle trace emission for the analysis of left atrial blood flow using 4D Flow MRI2018In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 47, p. 83-88Article in journal (Refereed)
    Abstract [en]

    4D Flow MRI has been used to quantify normal and deranged left ventricular blood flow characteristics on the basis of functionally distinct flow components. However, the application of this technique to the atria is challenging due to the presence of continuous inflow. This continuous inflow necessitates plane-based emission of particle traces from the inlet veins, leading to particles that represents different amounts of blood, and related quantification errors. The purpose of this study was to develop a novel fixed-volume approach for particle tracing and employ this method to develop quantitative analysis of 4D blood flow characteristics in the left atrium. 4D Flow MRI data were acquired during free-breathing using a navigator-gated gradient-echo sequence in three volunteers at 1.5 T. Fixed-volume particle traces emitted from the pulmonary veins were used to visualize left atrial blood flow and to quantitatively separate the flow into two functionally distinct flow components: Direct flow = particle traces that enter and leave the atrium in one heartbeat, Retained flow = particle traces that enter the atrium and remains there for one cardiac cycle. Flow visualization based on fixed-volume traces revealed that, beginning in early ventricular systole, flow enters the atrium and engages with residual blood volume to form a vortex. In early diastole during early ventricular filling, the organized vortical flow is extinguished, followed by formation of a second transient atrial vortex. Finally, in late diastole during atrial contraction, a second acceleration of blood into the ventricle is seen. The direct and retained left atrial flow components were between 44 and 57% and 43-56% of the stroke volume, respectively. In conclusion, fixed volume particle tracing permits separation of left atrial blood flow into different components based on the transit of blood through the atrium.