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  • 1.
    Andersson, Charlotta
    et al.
    Region Östergötland, Center for Diagnostics, Department of Clinical Physiology in Norrköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). 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.
    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).
    Lindström, Lena
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    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).
    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).
    Phase-contrast MRI volume flow - a comparison of breath held and navigator based acquisitions2016In: BMC Medical Imaging, ISSN 1471-2342, E-ISSN 1471-2342, Vol. 16, no 26Article in journal (Refereed)
    Abstract [en]

    Background: Magnetic Resonance Imaging (MRI) 2D phase-contrast flow measurement has been regarded as the gold standard in blood flow measurements and can be performed with free breathing or breath held techniques. We hypothesized that the accuracy of flow measurements obtained with segmented phase-contrast during breath holding, and in particular higher number of k-space segments, would be non-inferior compared to navigator phase-contrast. Volumes obtained from anatomic segmentation of cine MRI and Doppler echocardiography were used for additional reference. Methods: Forty patients, five women and 35 men, mean age 65 years (range 53-80), were randomly selected and consented to the study. All underwent EKG-gated cardiac MRI including breath hold cine, navigator based free-breathing phase-contrast MRI and breath hold phase-contrast MRI using k-space segmentation factors 3 and 5, as well as transthoracic echocardiography within 2 days. Results: In navigator based free-breathing phase-contrast flow, mean stroke volume and cardiac output were 79.7 +/- 17.1 ml and 5071 +/- 1192 ml/min, respectively. The duration of the acquisition was 50 +/- 6 s. With k-space segmentation factor 3, the corresponding values were 77.7 ml +/- 17.5 ml and 4979 +/- 1211 ml/min (p = 0.15 vs navigator). The duration of the breath hold was 17 +/- 2 s. K-space segmentation factor 5 gave mean stroke volume 77.9 +/- 16.4 ml, cardiac output 5142 +/- 1197 ml/min (p = 0.33 vs navigator), and breath hold time 11 +/- 1 s. Anatomical segmentation of cine gave mean stroke volume and cardiac output 91.2 +/- 20.8 ml and 5963 +/- 1452 ml/min, respectively. Echocardiography was reliable in 20 of the 40 patients. The mean diameter of the left ventricular outflow tract was 20.7 +/- 1.5 mm, stroke volume 78.3 ml +/- 15.2 ml and cardiac output 5164 +/- 1249 ml/min. Conclusions: In forty consecutive patients with coronary heart disease, breath holding and segmented k-space sampling techniques for phase-contrast flow produced stroke volumes and cardiac outputs similar to those obtained with free-breathing navigator based phase-contrast MRI, using less time. The values obtained agreed fairly well with Doppler echocardiography while there was a larger difference when compared with anatomical volume determinations using SSFP (steady state free precession) cine MRI.

  • 2.
    Andersson, Magnus
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Swedish E Science Research Centre SeRC, Sweden.
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish E Science Research Centre SeRC, Sweden.
    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). Swedish E Science Research Centre SeRC, Sweden.
    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). Swedish E Science Research Centre SeRC, Sweden.
    Correction: Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions (vol 6, pg 281, 2015)2015In: Cardiovascular Engineering and Technology, ISSN 1869-408X, E-ISSN 1869-4098, Vol. 6, no 4, p. 577-589Article in journal (Refereed)
    Abstract [en]

    Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where the pre-stenotic hypoplastic segment may limit the possible improvement by treating the CoA alone. Spatiotem-poral maps of TKE and flow eccentricity could be linked to the characteristics of the post-stenotic jet, showing a versatile response between the CoA dilatations. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre-and immediate post treatment, as well as during follow-up studies.

  • 3.
    Andersson, Magnus
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering.
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. 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).
    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).
    Multidirectional WSS disturbances in stenotic turbulent flows: A pre- and post-intervention study in an aortic coarctation2017In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 51Article in journal (Refereed)
    Abstract [en]

    Wall shear stress (WSS) disturbances are commonly expressed at sites of abnormal flow obstructions and may play an essential role in the pathogenesis of various vascular diseases. In laminar flows these disturbances have recently been assessed by the transverse wall shear stress (transWSS), which accounts for the WSS multidirectionality. Site-specific estimations of WSS disturbances in pulsatile transitional and turbulent type of flows are more challenging due to continuous and unpredictable changes in WSS behavior. In these complex flow settings, the transWSS may serve as a more comprehensive descriptor for assessing WSS disturbances of general nature compared to commonly used parameters. In this study large eddy simulations (LES) were used to investigate the transWSS properties in flows subjected to different pathological turbulent flow conditions, governed by a patient-specific model of an aortic coarctation pre and post balloon angioplasty. Results showed that regions of strong near-wall turbulence were collocated with regions of elevated transWSS and turbulent WSS, while in more transitional-like near-wall flow regions a closer resemblance was found between transWSS and low, and oscillatory WSS. Within the frame of this study, the transWSS parameter demonstrated a more multi-featured picture of WSS disturbances when exposed to different types of flow regimes, characteristics which were not depicted by the other parameters alone. (C) 2016 Published by Elsevier Ltd.

  • 4.
    Andersson, Magnus
    et al.
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Lantz, Jonas
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Östergötlands Läns Landsting, 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, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation - Impact of Virtual Interventions2015In: Cardiovascular Engineering and Technology, ISSN 1869-408X, E-ISSN 1869-4098, Vol. 6, no 6, p. 281-293Article in journal (Refereed)
    Abstract [en]

    Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation (LES) including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where turbulent flow proximal the constriction limits the possible improvement by treating the CoA alone. Spatiotemporal maps of TKE and flow eccentricity could be linked to the characteristics of the jet, where improved flow conditions were favored by an eccentric dilatation of the CoA. By including these flow markers into a combined MRI-CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre- and immediate post treatment, as well as during follow-up studies.

  • 5.
    Aneq Åström, Meriam
    et al.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Nylander, Eva
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Determination of right ventricular volume and function using multiple axially rotated MRI slices2011In: Clinical Physiology and Functional Imaging, ISSN 1475-0961, E-ISSN 1475-097X, Vol. 31, no 3, p. 233-239Article in journal (Refereed)
    Abstract [en]

    Pandgt;Background: The conventional magnetic resonance imaging (MRI) method for right ventricular (RV) volume and motion, using short-axis (SA) orientation, is limited by RV anatomy and shape. We suggest an orientation based on six slices rotated around the long axis of the RV, rotated long axis (RLA). Materials and methods: Three phantoms were investigated in SA and RLA using cine balanced steady-state free precession MRI. Volumes were calculated based on segmentation and checked against true volumes. In 23 healthy male volunteers, we used six long-axis planes from the middle of the tricuspid valve to the RV apex, rotated in 30 degrees increments. For comparison, short-axis slices were acquired. Imaging parameters were identical in both acquisitions. Results: Right ventricular end-diastolic (EDV), end-systolic (ESV) and stroke volumes (SV) determined in the RLA 179 center dot 1 +/- 29 center dot 3; 80 center dot 1 +/- 17 center dot 1; 99 center dot 3 +/- 16 center dot 9 ml and in the SA were 174 center dot 0 +/- 21 center dot 1; 78 center dot 8 +/- 13 center dot 6; 95 center dot 3 +/- 14 center dot 5 ml with P-values for the difference from 0 center dot 17 to 0 center dot 64 (ns). Interobserver variability ranged between 3 center dot 2% and 6 center dot 6% and intraobserver variability between 2 center dot 8% and 6 center dot 8%. In SA views, consensus for the definition of the basal slice was necessary in 39% of the volunteers for whom the average volume change was 20% in ESV and 10% in EDV. Conclusions: The RLA method results in better visualization and definition of the RV inflow, outflow and apex. Accurate measurement of RV volumes for diagnosis and follow-up of cardiac diseases are enhanced by the RLA orientation, even though additional acquisition time is required.

  • 6.
    Arzani, Amirhossein
    et al.
    IIT.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Shadden, Shawn C
    IIT.
    In Vivo Validation of Numerical Prediction for Turbulence Intensity in an Aortic Coarctation2012In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 40, no 4, p. 860-870Article in journal (Refereed)
    Abstract [en]

    This paper compares numerical predictions of turbulence intensity with in vivo measurement. Magnetic resonance imaging (MRI) was carried out on a 60-year-old female with a restenosed aortic coarctation. Time-resolved three-directional phase-contrast (PC) MRI data was acquired to enable turbulence intensity estimation. A contrast-enhanced MR angiography (MRA) and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics (CFD) modeling. A 3D model of the aortic coarctation and surrounding vasculature was constructed from the MRA data, and physiologic boundary conditions were modeled to match 2D PCMRI and pressure pulse measurements. Blood flow velocity data was subsequently obtained by numerical simulation. Turbulent kinetic energy (TKE) was computed from the resulting CFD data. Results indicate relative agreement (error a parts per thousand 10%) between the in vivo measurements and the CFD predictions of TKE. The discrepancies in modeled vs. measured TKE values were within expectations due to modeling and measurement errors.

  • 7.
    Björck, Hanna M.
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences.
    Renner, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Maleki, Shohreh
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Nilsson, Siv F.E.
    Linköping University, Department of Medical and Health Sciences, Pharmacology. Linköping University, Faculty of Health Sciences.
    Kihlberg, Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Radiology. Linköping University, Faculty of Health Sciences.
    Folkersen, Lasse
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Karlsson, Matts
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Eriksson, Per
    Atherosclerosis Research Unit, Center for Molecular Medicine, Department of Medicine, Karolinska Institute, Sweden.
    Länne, Toste
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Thoracic and Vascular Surgery in Östergötland.
    Characterization of Shear-Sensitive Genes in the NormalRat Aorta Identifies Hand2 as a Major Flow-ResponsiveTranscription Factor2012In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 12Article in journal (Refereed)
    Abstract [en]

    Objective: Shear forces play a key role in the maintenance of vessel wall integrity. Current understanding regarding shear-dependent gene expression is mainly based on in vitro or in vivo observations with experimentally deranged shear, hence reflecting acute molecular events in relation to flow. Our objective was to determine wall shear stress (WSS) in the rat aorta and study flow-dependent vessel wall biology under physiological conditions.

    Methods and Results: Animal-specific aortic WSS magnitude and vector direction were estimated using computational fluid dynamic simulation based on aortic geometry and flow information acquired by MRI. Two distinct flow pattern regions were identified in the normal rat aorta; the distal part of the inner curvature being exposed to low WSS and a non-uniform vector direction, and a region along the outer curvature being subjected to markedly higher levels of WSS and a uniform vector direction. Microarray analysis revealed a strong differential expression between the flow regions, particularly associated with transcriptional regulation. In particular, several genes related to Ca2+-signalling, inflammation, proliferation and oxidative stress were among the most highly differentially expressed.

    Conclusions: Microarray analysis validated the CFD-defined WSS regions in the rat aorta, and several novel flow-dependent genes were identified. The importance of these genes in relation to atherosusceptibility needs further investigation.

  • 8.
    Bolger, Ann F
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Heiberg, Einar
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dyverfeldt, Petter
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Carlsson, Mats
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Johansson, P
    Markenroth, K
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Arheden, H
    Tredimensionellt MR-blodflöde och diastolisk kinetisk energi kvantiferat med magnetisk resonanstomografi efter kirurgisk vänsterkammarrekonstruktion. Ny teknik för utvärdering av kammarfunktion.2007In: Riksstämman,2007, 2007Conference paper (Other academic)
  • 9.
    Bolger, Ann F
    et al.
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Faculty of Health Sciences.
    Heiberg, Einar
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Faculty of Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wigström, Lars
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Engvall, Jan
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Sigfridsson, Andreas
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Ebbers, Tino
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Carlhäll, Carljohan
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Transit of blood flow through thehuman left ventricle mapped by cardiovascular magnetic resonance2007In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 9, no 5, p. 741-747Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    The transit of blood through the beating heart is a basic aspect of cardiovascular physiology which remains incompletely studied. Quantification of the components of multidirectional flow in the normal left ventricle (LV) is lacking, making it difficult to put the changes observed with LV dysfunction and cardiac surgery into context.

    METHODS:

    Three dimensional, three directional, time resolved magnetic resonance phase-contrast velocity mapping was performed at 1.5 Tesla in 17 normal subjects, 6 female, aged 44+/-14 years (mean+/-SD). We visualized and measured the relative volumes of LV flow components and the diastolic changes in inflowing kinetic energy (KE). Of total diastolic inflow volume, 44+/-11% followed a direct, albeit curved route to systolic ejection (videos 1 and 2), in contrast to 11% in a subject with mildly dilated cardiomyopathy (DCM), who was included for preliminary comparison (video 3). In normals, 16+/-8% of the KE of inflow was conserved to the end of diastole, compared with 5% in the DCM patient. Blood following the direct route lost or transferred less of its KE during diastole than blood that was retained until the next beat (1.6+/-1.0 millijoules vs 8.2+/-1.9 millijoules, p<0.05); whereas, in the DCM patient, the reduction in KE of retained inflow was 18-fold greater than that of the blood tracing the direct route.

    CONCLUSION:

    Multidimensional flow mapping can measure the paths, compartmentalization and kinetic energy changes of blood flowing into the LV, demonstrating differences of KE loss between compartments, and potentially between the flows in normal and dilated left ventricles.

  • 10.
    Brandt, Einar
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Wigström, Lars
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Physiological Measurements.
    Automatisk flödeskaraktärisering av tredimensionella vektorfält.2001In: In proceedings of Svenska Mekanikdagarna,2001, 2001, p. 61-62Conference paper (Refereed)
  • 11.
    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).
    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.
    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).
    Improving visualization of 4D flow cardiovascular magnetic resonance with four-dimensional angiographic data: generation of a 4D phase-contrast magnetic resonance CardioAngiography (4D PC-MRCA)2017In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 19, article id 47Article in journal (Refereed)
    Abstract [en]

    Magnetic Resonance Angiography (MRA) and Phase-Contrast MRA (PC-MRA) approaches used for assessment of cardiovascular morphology typically result in data containing information from the entire cardiac cycle combined into one 2D or 3D image. Information specific to each timeframe of the cardiac cycle is, however, lost in this process. This study proposes a novel technique, called Phase-Contrast Magnetic Resonance CardioAngiography (4D PC-MRCA), that utilizes the full potential of 4D Flow CMR when generating temporally resolved PC-MRA data to improve visualization of the heart and major vessels throughout the cardiac cycle. Using non-rigid registration between the timeframes of the 4D Flow CMR acquisition, the technique concentrates information from the entire cardiac cycle into an angiographic dataset at one specific timeframe, taking movement over the cardiac cycle into account. Registration between the timeframes is used once more to generate a time-resolved angiography. The method was evaluated in ten healthy volunteers. Visual comparison of the 4D PC-MRCAs versus PC-MRAs generated from 4D Flow CMR using the traditional approach was performed by two observers using Maximum Intensity Projections (MIPs). The 4D PC-MRCAs resulted in better visibility of the main anatomical regions of the cardiovascular system, especially where cardiac or vessel motion was present. The proposed method represents an improvement over previous PC-MRA generation techniques that rely on 4D Flow CMR, as it effectively utilizes all the information available in the acquisition. The 4D PC-MRCA can be used to visualize the motion of the heart and major vessels throughout the entire cardiac cycle.

  • 12.
    Bustamante, Mariana
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Petersson, Sven
    Linköping University, Department of Medical and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
    Eriksson, Jonatan
    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).
    Alehagen, Urban
    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.
    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).
    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).
    Atlas-based analysis of 4D flow CMR: Automated vessel segmentation and flow quantification2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, no 87Article in journal (Refereed)
    Abstract [en]

    Background: Flow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases. Clinically, it is often based on semi-automatic segmentation of a vessel throughout the cardiac cycle in 2D cine phase-contrast Cardiovascular Magnetic Resonance (CMR) images. Three-dimensional (3D), time-resolved phase-contrast CMR with three-directional velocity encoding (4D flow CMR) permits assessment of net flow volumes and flow patterns retrospectively at any location in a time-resolved 3D volume. However, analysis of these datasets can be demanding. The aim of this study is to develop and evaluate a fully automatic method for segmentation and analysis of 4D flow CMR data of the great thoracic vessels. Methods: The proposed method utilizes atlas-based segmentation to segment the great thoracic vessels in systole, and registration between different time frames of the cardiac cycle in order to segment these vessels over time. Additionally, net flow volumes are calculated automatically at locations of interest. The method was applied on 4D flow CMR datasets obtained from 11 healthy volunteers and 10 patients with heart failure. Evaluation of the method was performed visually, and by comparison of net flow volumes in the ascending aorta obtained automatically (using the proposed method), and semi-automatically. Further evaluation was done by comparison of net flow volumes obtained automatically at different locations in the aorta, pulmonary artery, and caval veins. Results: Visual evaluation of the generated segmentations resulted in good outcomes for all the major vessels in all but one dataset. The comparison between automatically and semi-automatically obtained net flow volumes in the ascending aorta resulted in very high correlation (r(2) = 0.926). Moreover, comparison of the net flow volumes obtained automatically in other vessel locations also produced high correlations where expected: pulmonary trunk vs. proximal ascending aorta (r(2) = 0.955), pulmonary trunk vs. pulmonary branches (r(2) = 0.808), and pulmonary trunk vs. caval veins (r(2) = 0.906). Conclusions: The proposed method allows for automatic analysis of 4D flow CMR data, including vessel segmentation, assessment of flow volumes at locations of interest, and 4D flow visualization. This constitutes an important step towards facilitating the clinical utility of 4D flow CMR.

  • 13.
    Carhall, C
    et al.
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Health Sciences.
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Bolger, A
    University of California San Francisco.
    Pre-systolic preparation for left ventricular ejection is impaired in heart failure in EUROPEAN HEART JOURNAL, vol 31, issue , pp 726-7272010In: EUROPEAN HEART JOURNAL, Oxford University Press , 2010, Vol. 31, p. 726-727Conference paper (Refereed)
    Abstract [en]

    n/a

  • 14.
    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.
    Lantz, Jonas
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    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). 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, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Faculty of Science & Engineering. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    4D Flow MRI-Based Pressure Loss Estimation in Stenotic Flows: Evaluation Using Numerical Simulations2016In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 75, no 4, p. 1808-1821Article in journal (Refereed)
    Abstract [en]

    Purpose: To assess how 4D flow MRI-based pressure and energy loss estimates correspond to net transstenotic pressure gradients (TPG(net)) and their dependence on spatial resolution. Methods: Numerical velocity data of stenotic flow were obtained from computational fluid dynamics (CFD) simulations in geometries with varying stenosis degrees, poststenotic diameters and flow rates. MRI measurements were simulated at different spatial resolutions. The simplified and extended Bernoulli equations, Pressure-Poisson equation (PPE), and integration of turbulent kinetic energy (TKE) and viscous dissipation were compared against the true TPG(net). Results: The simplified Bernoulli equation overestimated the true TPG(net) (8.74 +/- 0.67 versus 6.76 +/- 0.54 mmHg). The extended Bernoulli equation performed better (6.57 +/- 0.53 mmHg), although errors remained at low TPG(net). TPG(net) estimations using the PPE were always close to zero. Total TKE and viscous dissipation correlated strongly with TPG(net) for each geometry (r(2) &gt; 0.93) and moderately considering all geometries (r(2) = 0.756 and r(2) = 0.776, respectively). TKE estimates were accurate and minorly impacted by resolution. Viscous dissipation was overall underestimated and resolution dependent. Conclusion: Several parameters overestimate or are not linearly related to TPG(net) and/or depend on spatial resolution. Considering idealized axisymmetric geometries and in absence of noise, TPG(net) was best estimated using the extended Bernoulli equation. (C) 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

  • 15.
    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, Frederica
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular 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 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. University of 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).
    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).
    Bridging the gap between measurements and modelling: a cardiovascular functional avatar2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 6214Article in journal (Refereed)
    Abstract [en]

    Lumped parameter models of the cardiovascular system have the potential to assist researchers and clinicians to better understand cardiovascular function. The value of such models increases when they are subject specific. However, most approaches to personalize lumped parameter models have thus far required invasive measurements or fall short of being subject specific due to a lack of the necessary clinical data. Here, we propose an approach to personalize parameters in a model of the heart and the systemic circulation using exclusively non-invasive measurements. The personalized model is created using flow data from four-dimensional magnetic resonance imaging and cuff pressure measurements in the brachial artery. We term this personalized model the cardiovascular avatar. In our proof-of-concept study, we evaluated the capability of the avatar to reproduce pressures and flows in a group of eight healthy subjects. Both quantitatively and qualitatively, the model-based results agreed well with the pressure and flow measurements obtained in vivo for each subject. This non-invasive and personalized approach can synthesize medical data into clinically relevant indicators of cardiovascular function, and estimate hemodynamic variables that cannot be assessed directly from clinical measurements.

  • 16.
    Cibis, Merih
    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).
    Bustamante, Mariana
    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).
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    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).
    Creating Hemodynamic Atlases of Cardiac 4D Flow MRI2017In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 46, no 5, p. 1389-1399Article in journal (Refereed)
    Abstract [en]

    Purpose: Hemodynamic atlases can add to the pathophysiological understanding of cardiac diseases. This study proposes a method to create hemodynamic atlases using 4D Flow magnetic resonance imaging (MRI). The method is demonstrated for kinetic energy (KE) and helicity density (Hd). Materials and Methods: Thirteen healthy subjects underwent 4D Flow MRI at 3T. Phase-contrast magnetic resonance cardioangiographies (PC-MRCAs) and an average heart were created and segmented. The PC-MRCAs, KE, and Hd were nonrigidly registered to the average heart to create atlases. The method was compared with 1) rigid, 2) affine registration of the PC-MRCAs, and 3) affine registration of segmentations. The peak and mean KE and Hd before and after registration were calculated to evaluate interpolation error due to nonrigid registration. Results: The segmentations deformed using nonrigid registration overlapped (median: 92.3%) more than rigid (23.1%, P amp;lt; 0.001), and affine registration of PC-MRCAs (38.5%, P amp;lt; 0.001) and affine registration of segmentations (61.5%, P amp;lt; 0.001). The peak KE was 4.9 mJ using the proposed method and affine registration of segmentations (P50.91), 3.5 mJ using rigid registration (P amp;lt; 0.001), and 4.2 mJ using affine registration of the PC-MRCAs (P amp;lt; 0.001). The mean KE was 1.1 mJ using the proposed method, 0.8 mJ using rigid registration (P amp;lt; 0.001), 0.9 mJ using affine registration of the PC-MRCAs (P amp;lt; 0.001), and 1.0 mJ using affine registration of segmentations (P50.028). The interpolation error was 5.262.6% at mid-systole, 2.863.8% at early diastole for peak KE; 9.669.3% at mid-systole, 4.064.6% at early diastole, and 4.964.6% at late diastole for peak Hd. The mean KE and Hd were not affected by interpolation. Conclusion: Hemodynamic atlases can be obtained with minimal user interaction using nonrigid registration of 4D Flow MRI. Level of Evidence: 2 Technical Efficacy: Stage 1

  • 17.
    Cibis, Merih
    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).
    Lindahl, Tomas
    Linköping University, Department of Clinical and Experimental Medicine, Division of Microbiology and Molecular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Chemistry.
    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, Lars
    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.
    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).
    Left Atrial 4D Blood Flow Dynamics and Hemostasis following Electrical Cardioversion of Atrial Fibrillation2017In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 8, article id 1052Article in journal (Refereed)
    Abstract [en]

    Background: Electrical cardioversion in patients with atrial fibrillation is followed by a transiently impaired atrial mechanical function, termed atrial stunning. During atrial stunning, a retained risk of left atrial thrombus formation exists, which may be attributed to abnormal left atrial blood flow patterns. 4D Flow cardiovascular magnetic resonance (CMR) enables blood flow assessment from the entire three-dimensional atrial volume throughout the cardiac cycle. We sought to investigate left atrial 4D blood flow patterns and hemostasis during left atrial stunning and after left atrial mechanical function was restored. Methods: 4D Flow and morphological CMR data as well as blood samples were collected in fourteen patients at two time-points: 2-3 h (Time-1) and 4 weeks (Time-2) following cardioversion. The volume of blood stasis and duration of blood stasis were calculated. In addition, hemostasis markers were analyzed. Results: From Time-1 to Time-2: Heart rate decreased (61 +/- 7 vs. 56 +/- 8 bpm, p = 0.01); Maximum change in left atrial volume increased (8 +/- 4 vs. 22 +/- 15%, p = 0.009); The duration of stasis (68 +/- 11 vs. 57 +/- 8%, p = 0.002) and the volume of stasis (14 +/- 9 vs. 9 +/- 7%, p = 0.04) decreased; Thrombin-antithrombin complex (TAT) decreased (5.2 +/- 3.3 vs. 3.3 +/- 2.2it.g/L, p = 0.008). A significant correlation was found between TAT and the volume of stasis (r(2) = 0.69, p amp;lt; 0.001) at Time-1 and between TAT and the duration of stasis (r(2) = 0.34, p = 0.04) at Time-2. Conclusion: In this longitudinal study, left atrial multidimensional blood flow was altered and blood stasis was elevated during left atrial stunning compared to the restored left atrial mechanical function. The coagulability of blood was also elevated during atrial stunning. The association between blood stasis and hypercoagulability proposes that assessment of left atrial 4D flow can add to the pathophysiological understanding of thrombus formation during atrial fibrillation related atrial stunning.

  • 18.
    Dyverfeldt, Petter
    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).
    Bissell, Malenka
    University of Oxford, England.
    Barker, Alex J.
    Northwestern University, IL 60611 USA.
    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. University of 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).
    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).
    Francios, Christopher J.
    University of Wisconsin, WI 53706 USA.
    Frydrychowicz, Alex
    University Hospital Schleswig Holstein, Germany.
    Geiger, Julia
    University of Childrens Hospital Zurich, Switzerland.
    Giese, Daniel
    University Hospital Cologne, Germany.
    Hope, Michael D.
    University of Calif San Francisco, CA USA.
    Kilner, Philip J.
    University of London Imperial Coll Science Technology and Med, England.
    Kozerke, Sebastian
    University of Zurich, Switzerland; ETH, Switzerland.
    Myerson, Saul
    University of Oxford, England.
    Neubauer, Stefan
    University of Oxford, England.
    Wieben, Oliver
    University of Wisconsin, WI 53706 USA.
    Markl, Michael
    Northwestern University, IL 60611 USA; Northwestern University, IL 60611 USA.
    4D flow cardiovascular magnetic resonance consensus statement2015In: Journal of Cardiovascular Magnetic Resonance, ISSN 1097-6647, E-ISSN 1532-429X, Vol. 17, no 72Article, review/survey (Refereed)
    Abstract [en]

    Pulsatile blood flow through the cavities of the heart and great vessels is time-varying and multidirectional. Access to all regions, phases and directions of cardiovascular flows has formerly been limited. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has enabled more comprehensive access to such flows, with typical spatial resolution of 1.5x1.5x1.5 - 3x3x3 mm(3), typical temporal resolution of 30-40 ms, and acquisition times in the order of 5 to 25 min. This consensus paper is the work of physicists, physicians and biomedical engineers, active in the development and implementation of 4D Flow CMR, who have repeatedly met to share experience and ideas. The paper aims to assist understanding of acquisition and analysis methods, and their potential clinical applications with a focus on the heart and greater vessels. We describe that 4D Flow CMR can be clinically advantageous because placement of a single acquisition volume is straightforward and enables flow through any plane across it to be calculated retrospectively and with good accuracy. We also specify research and development goals that have yet to be satisfactorily achieved. Derived flow parameters, generally needing further development or validation for clinical use, include measurements of wall shear stress, pressure difference, turbulent kinetic energy, and intracardiac flow components. The dependence of measurement accuracy on acquisition parameters is considered, as are the uses of different visualization strategies for appropriate representation of time-varying multidirectional flow fields. Finally, we offer suggestions for more consistent, user-friendly implementation of 4D Flow CMR acquisition and data handling with a view to multicenter studies and more widespread adoption of the approach in routine clinical investigations.

  • 19.
    Dyverfeldt, Petter
    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 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).
    Comparison of Respiratory Motion Suppression Techniques for 4D Flow MRI2017In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 78, no 5, p. 1877-1882Article in journal (Refereed)
    Abstract [en]

    Purpose: The purpose of this work was to assess the impact of respiratory motion and to compare methods for suppression of respiratory motion artifacts in 4D Flow MRI. Methods: A numerical 3D aorta phantom was designed based on an aorta velocity field obtained by computational fluid mechanics. Motion-distorted 4D Flow MRI measurements were simulated and several different motion-suppression techniques were evaluated: Gating with fixed acceptance window size, gating with different window sizes in inner and outer kspace, and k-space reordering. Additionally, different spatial resolutions were simulated. Results: Respiratory motion reduced the image quality. All motion-suppression techniques improved the data quality. Flow rate errors of up to 30% without gating could be reduced to less than 2.5% with the most successful motion suppression methods. Weighted gating and gating combined with kspace reordering were advantageous compared with conventional fixed-window gating. Spatial resolutions finer than the amount of accepted motion did not lead to improved results. Conclusion: Respiratory motion affects 4D Flow MRI data. Several different motion suppression techniques exist that are capable of reducing the errors associated with respiratory motion. Spatial resolutions finer than the degree of accepted respiratory motion do not result in improved data quality. (C) 2017 International Society for Magnetic Resonance in Medicine.

  • 20.
    Dyverfeldt, Petter
    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).
    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).
    Letter by Dyverfeldt and Ebbers regarding article "Estimation of turbulent kinetic energy using 4D phase-contrast MRI: Effect of scan parameters and target vessel size"2016In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 34, no 8, p. 1226-1226Article in journal (Other academic)
    Abstract [en]

    n/a

  • 21.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of 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 Health Sciences. Östergötlands Läns Landsting, 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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Thoracic and Vascular Surgery. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Pulse wave velocity with 4D flow MRI: Systematic differences and age-related regional vascular stiffness2014In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 32, no 10, p. 1266-1271Article in journal (Refereed)
    Abstract [en]

    Purpose: The objective of this study was to compare multiple methods for estimation of PWV from 4D flow MRI velocity data and to investigate if 4D flow MRI-based PWV estimation with piecewise linear regression modeling of travel-distance vs. travel time is sufficient to discern age-related regional differences in PWV. Methods: 4D flow MRI velocity data were acquired in 8 young and Solder (age: 23 +/- 2 vs. 58 +/- 2 years old) normal volunteers. Travel-time and travel-distance were measured throughout the aorta and piecewise linear regression was used to measure global PWV in the descending aorta and regional PWV in three equally sized segments between the top of the aortic arch and the renal arteries. Six different methods for extracting travel-time were compared. Results: Methods for estimation of travel-time that use information about the whole flow waveform systematically overestimate PWV when compared to methods restricted to the upslope-portion of the waveforms (p less than 0.05). In terms of regional PWV, a significant interaction was found between age and location (p less than 0.05). The age-related differences in regional PWV were greater in the proximal compared to distal descending aorta. Conclusion: Care must be taken as different classes of methods for the estimation of travel-time produce different results. 4D flow MRI-based PWV estimation with piecewise linear regression modeling of travel-distance vs. travel time can discern age-related differences in regional PWV well in line with previously reported data.

  • 22.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Eriksson, Jonatan
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Carlhäll, Carljohan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F.
    University of California San Francisco, San Francisco, California, USA.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Extending 4D Flow Visualization to the Human Right Ventricle2009In: Proceedings of International Society for Magnetic Resonance in Medicine: 17th Scientific Meeting 2009, International Society for Magnetic Resonance in Medicine , 2009, p. 3860-3860Conference paper (Refereed)
    Abstract [en]

    The right ventricle has an important role in cardiovascular disease. However, because of the complex geometry and the sensitivity to the respiratory cycle, imaging of the right ventricle is challenging. We investigated whether 3D cine phase-contrast MRI can provide data with sufficient accuracy for visualizations of the 4D blood flow in the right ventricle. Whole-heart 4D flow measurements with optimized imaging parameters and post-processing tools were made in healthy volunteers. Pathlines emitted from the right atrium could be traced through the right ventricle to the pulmonary artery without leaving the blood pool and thereby met our criteria for sufficient accuracy.

  • 23.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Boano, G.
    Östergötlands Läns Landsting.
    Carlhäll, Carljohan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Hermansson, Ulf
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, A.F.
    University of California, San Fransisco, San Franisco, California, United States.
    Engvall, Jan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Turbulence Mapping Extends the Utility of Phase-Contrast MRI in Mitral Valve Regurgitation2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 3939-Conference paper (Refereed)
  • 24.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Department of Medical and Health Sciences, Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Carlhäll, Carl Johan
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Boano, Gabriella
    Östergötlands Läns Landsting, Heart Centre, Department of Cardiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Hermansson, Ulf
    Linköping University, Department of Medical and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, Ann F.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Linköping University, Department of Medical and Health Sciences, Physiology.
    Hemodynamic aspects of mitral regurgitation assessed by generalized phase-contrast MRI2011In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 33, no 3, p. 582-588Article in journal (Refereed)
    Abstract [en]

    Purpose: Mitral regurgitation creates a high velocity jet into the left atrium (LA), contributing both volume andpressure; we hypothesized that the severity of regurgitation would be reflected in the degree of LA flowdistortion.

    Material and Methods: Three-dimensional cine PC-MRI was applied to determine LA flow patterns andturbulent kinetic energy (TKE) in seven subjects (five patients with posterior mitral leaflet prolapse, two normalsubjects). In addition, the regurgitant volume and the time-velocity profiles in the pulmonary veins weremeasured.

    Results: The LA flow in the mitral regurgitation patients was highly disturbed with elevated values of TKE.Peak TKE occurred consistently at late systole. The total LA TKE was closely related to the regurgitant volume.LA flow patterns were characterized by a pronounced vortex in proximity to the regurgitant jet. In some patients,pronounced discordances were observed between individual pulmonary venous inflows, but these could not berelated to the direction of the flow jet or parameters describing global LA hemodynamics.

    Conclusion: PC-MRI permits investigations of atrial and pulmonary vein flow patterns and TKE in significantmitral regurgitation, reflecting the impact of the highly disturbed blood flow that accompanies this importantvalve disease.

  • 25.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Assessment of fluctuating velocities in disturbed cardiovascular blood flow: in vivo feasibility of generalized phase-contrast MRI2008In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 28, no 3, p. 655-663Article in journal (Refereed)
    Abstract [en]

    Purpose

    To evaluate the feasibility of generalized phase-contrast magnetic resonance imaging (PC-MRI) for the noninvasive assessment of fluctuating velocities in cardiovascular blood flow.

    Materials and Methods

    Multidimensional PC-MRI was used in a generalized manner to map mean flow velocities and intravoxel velocity standard deviation (IVSD) values in one healthy aorta and in three patients with different cardiovascular diseases. The acquired data were used to assess the kinetic energy of both the mean (MKE) and the fluctuating (TKE) velocity field.

    Results

    In all of the subjects, both mean and fluctuating flow data were successfully acquired. The highest TKE values in the patients were found at sites characterized by abnormal flow conditions. No regional increase in TKE was found in the normal aorta.

    Conclusion

    PC-MRI IVSD mapping is able to detect flow abnormalities in a variety of human cardiovascular conditions and shows promise for the quantitative assessment of turbulence. This approach may assist in clarifying the role of disturbed hemodynamics in cardiovascular diseases.

  • 26.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Assessment of Turbulent Flow using Magnetic Resonance Imaging2007In: IX Svenska Kardiovaskulära Vårmötet,2007, 2007Conference paper (Other academic)
    Abstract [en]

      

  • 27.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Improved image acquisition and processing allow accurate 4D flow investigations of the right ventricle2008In: Medicinteknikdagarna,2008, 2008Conference paper (Other academic)
    Abstract [en]

      

  • 28.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics .
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland. Linköping University, Center for Medical Image Science and Visualization, CMIV.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    In-vivo quantification of turbulent velocity fluctuations2007In: 15th Int Soc Magn Reson Med,2007, 2007Conference paper (Other academic)
  • 29.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Non-invsive assessment of turbulent flow using magnetic resonance imaging2007In: Medicinteknikdagarna,2007, 2007Conference paper (Other academic)
  • 30.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Engvall, Jan
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Mätning och visualisering av blodflödet i höger kammare med tidsupplöst tredimensionell MR2007In: Riksstämman,2007, 2007Conference paper (Other academic)
    Abstract [sv]

       

  • 31.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Franzén, Stefan
    Linköping University, Department of Medicine and Health Sciences, Thoracic Surgery. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Bolger, Ann F.
    University of California San Fransisco, San Fransisco, California, United States.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    In-Vitro Turbulence Mapping in Prosthetic Heart Valves using Generalized Phase-Contrast MRI2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 3941-Conference paper (Refereed)
  • 32.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Gårdhagen, Roland
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics . Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology.
    Ebbers, Tinno
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, The Institute of Technology. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    MRI Turbulence Quantification2009In: Proc. Intl. Soc. Mag. Reson. Med., 2009, p. 1858-Conference paper (Refereed)
  • 33.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Gårdhagen, Roland
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    On MRI turbulence quantification2009In: Magnetic Resonance Imaging, ISSN 0730-725X, E-ISSN 1873-5894, Vol. 27, no 7, p. 913-922Article in journal (Refereed)
    Abstract [en]

    Turbulent flow, characterized by velocity fluctuations, accompanies many forms of cardiovascular disease and may contribute to their progression and hemodynamic consequences. Several studies have investigated the effects of turbulence on the magnetic resonance imaging (MRI) signal. Quantitative MRI turbulence measurements have recently been shown to have great potential for application both in human cardiovascular flow and in engineering flow. In this article, potential pitfalls and sources of error in MRI turbulence measurements are theoretically and numerically investigated. Data acquisition strategies suitable for turbulence quantification are outlined. The results show that the sensitivity of MRI turbulence measurements to intravoxel mean velocity variations is negligible, but that noise may degrade the estimates if the turbulence encoding parameter is set improperly. Different approaches for utilizing a given amount of scan time were shown to influence the dynamic range and the uncertainty in the turbulence estimates due to noise. The findings reported in this work may be valuable for both in vitro and in vivo studies employing MRI methods for turbulence quantification.

  • 34.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology.
    Quantification of intravoxel velocity standard deviation and turbulence intensity by generalizing phase-contrast MRI2006In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 56, no 4, p. 850-858Article in journal (Refereed)
    Abstract [en]

    Turbulent flow, characterized by velocity fluctuations, is a contributing factor to the pathogenesis of several cardiovascular diseases. A clinical noninvasive tool for assessing turbulence is lacking, however. It is well known that the occurrence of multiple spin velocities within a voxel during the influence of a magnetic gradient moment causes signal loss in phase-contrast magnetic resonance imaging (PC-MRI). In this paper a mathematical derivation of an expression for computing the standard deviation (SD) of the blood flow velocity distribution within a voxel is presented. The SD is obtained from the magnitude of PC-MRI signals acquired with different first gradient moments. By exploiting the relation between the SD and turbulence intensity (TI), this method allows for quantitative studies of turbulence. For validation, the TI in an in vitro flow phantom was quantified, and the results compared favorably with previously published laser Doppler anemometry (LDA) results. This method has the potential to become an important tool for the noninvasive assessment of turbulence in the arterial tree.

  • 35.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Thoracic and Vascular Surgery.
    Ebbers, Tino
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Quantification of Turbulance Intensity by Generalizing Phase-Contrast MRI2006Conference paper (Refereed)
  • 36.
    Dyverfeldt, Petter
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Centre of Surgery and Oncology, Department of Surgery in Östergötland.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Quantification of Turbulence Intensity by Generalizing Phase-Contrast MRI2006In: Proc. Intl. Soc. Mag. Reson. Med. 14,2006, 2006, p. 870-870Conference paper (Refereed)
    Abstract [en]

      

  • 37.
    Dyverfeldt, Petter
    et al.
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Sigfridsson, Andreas
    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 Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    A Novel MRI Framework for the Quantification of Any Moment of Arbitrary Velocity Distributions.2010In: Proc. Intl. Soc. Mag. Reson. Med. 18 (2010), ISMRM , 2010, p. 1359-1359Conference paper (Other academic)
    Abstract [en]

    Under the assumption that the intravoxel velocity distribution is symmetric about its mean, the well-known MRI phase-difference method permits an estimation of the mean velocity of a voxel. The mean velocity corresponds to the first moment of the velocity distribution. Here, a novel framework for the quantification of any moment of arbitrary spin velocity distributions is presented. Simulations on realistic velocity distributions demonstrate its application. The presented moment framework may assist in improving the understanding of existing MRI methods for the quantification of flow and motion and serve as a basis for the development of new methods.

  • 38.
    Dyverfeldt, Petter
    et al.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics.
    A novel MRI framework for the quantification of any moment of arbitrary velocity distributions2011In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 65, no 3, p. 725-731Article in journal (Refereed)
    Abstract [en]

    MRI can measure several important hemodynamic parameters but might not yet have reached its full potential. The most common MRI method for the assessment of flow is phase-contrast MRI velocity mapping that estimates the mean velocity of a voxel. This estimation is precise only when the intravoxel velocity distribution is symmetric. The mean velocity corresponds to the first raw moment of the intravoxel velocity distribution. Here, a generalized MRI framework for the quantification of any moment of arbitrary velocity distributions is described. This framework is based on the fact that moments in the function domain (velocity space) correspond to differentials in the Fourier transform domain (kv-space). For proof-of-concept, moments of realistic velocity distributions were estimated using finite difference approximations of the derivatives of the MRI signal. In addition, the framework was applied to investigate the symmetry assumption underlying phase-contrast MRI velocity mapping; we found that this assumption can substantially affect phase-contrast MRI velocity estimates and that its significance can be reduced by increasing the velocity encoding range.

  • 39.
    Dyverfeldt, Petter
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Knutsson, Hans
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    MR flow imaging beyond the mean velocity: Estimation of the skew  and kurtosis of intravoxel velocity distributions2011In: ISMRM 2011, International Society for Magnetic Resonance in Medicine ( ISMRM ) , 2011Conference paper (Other academic)
  • 40.
    Ebbers, Tino
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care. Linköping University, Faculty of Health Sciences.
    Cardiovascular fluid dynamics: methods for flow and pressure field analysis from magnetic resonance imaging2001Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cardiovascular blood flow is highly complex and incompletely understood. Blood flow patterns are expected to influence the opening and closing of normal and prosthetic heart valves, the efficiency of cardiac filling and ejection, and the resistance to thrombus formation within the heart. Conventional diagnostic techniques are poorly suited to the study of the three-dimensional (3D) blood flow patterns in the heart chambers and large vessels. Noninvasive methods have also been inadequate in studying intracardiac pressure differences, which are the driving force of flow and are critical in the evaluation of many cardiovascular abnormalities.

    This thesis focuses on the development of non-invasive methods for analysis of 3D cardiovascular blood flow. Simultaneous study of cardiovascular fluid dynamics allowed knowledge exchange across the two disciplines, facilitating the development process and broadening the applicability of the methods.

    A time-resolved 3D phase-contrast Magnetic Resonance lrnaging (MRI) technique was used to acquire the velocity vector field in a 3D volume encompassing the entire heart or a large vessel. Cardiovascular blood flow patterns were visualized by use of particle traces, which revealed, for instance, vortical flow patterns in the left atrium.

    By applying the Navier-Stokes equation along a user-defined line in the 3D velocity vector field, the relative pressure could be obtained as an excellent supplement to the flow pattern visualization. Using a delineation of the blood pool, the time-varying 3D relative pressure field in the human left ventricle was obtained from the velocity field by use of the pressure Poisson equation.

    A delineation of the heart muscle, a task that is almost impossible to perform on 3D MRI either automatically or manually, was also achieved by usage of particle traces. This segmentation allows automatic calculation of the 3D relative pressure field, as well as calculation of well-established parameters such as ventricle volume and mass.

    Simultaneous 3D assessment of cardiovascular pressure and flow phenomena throughout the cardiac cycle offers an opportunity to expand our understanding of the basic determinants of time-varying flow in healthy and sick hearts, with the potential for improving our methods for diagnosis, medical treatment and surgical correction of cardiovascular diseases.

    List of papers
    1. Particle trace visualization of intracardiac flow using time-resolved 3D phase contrast MRI
    Open this publication in new window or tab >>Particle trace visualization of intracardiac flow using time-resolved 3D phase contrast MRI
    Show others...
    1999 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 41, no 4, p. 793-799Article in journal (Refereed) Published
    Abstract [en]

    The flow patterns in the human heart are complex and difficult to visualize using conventional two-dimensional (2D) modalities, whether they depict a single velocity component (Doppler echocardiography) or all three components in a few slices (2D phase contrast MRI). To avoid these shortcomings, a temporally resolved 3D phase contrast technique was used to derive data describing the intracardiac velocity fields in normal volunteers. The MRI data were corrected for phase shifts caused by eddy currents and concomitant gradient fields, with improvement in the accuracy of subsequent flow visualizations. Pathlines describing the blood pathways through the heart were generated from the temporally resolved velocity data, starting from user-specified locations and time frames. Flow trajectories were displayed as 3D particle traces, with simultaneous demonstration of morphologic 2D slices. This type of visualization is intuitive and interactive and may extend our understanding of dynamic and previously unrecognized patterns of intracardiac flow.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-26701 (URN)10.1002/(SICI)1522-2594(199904)41:4<793::AID-MRM19>3.0.CO;2-2 (DOI)11291 (Local ID)11291 (Archive number)11291 (OAI)
    Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2017-12-13
    2. Three-dimensional flow in the human left atrium
    Open this publication in new window or tab >>Three-dimensional flow in the human left atrium
    Show others...
    2001 (English)In: Heart, ISSN 1355-6037, Vol. 86, no 4, p. 448-455Article in journal (Refereed) Published
    Abstract [en]

    BACKGROUND: Abnormal flow patterns in the left atrium in atrial fibrillation or mitral stenosis are associated with an increased risk of thrombosis and systemic embolisation; the characteristics of normal atrial flow that avoid stasis have not been well defined.

    OBJECTIVES: To present a three dimensional particle trace visualisation of normal left atrial flow in vivo, constructed from flow velocities in three dimensional space.

    METHODS: Particle trace visualisation of time resolved three dimensional magnetic resonance imaging velocity measurements was used to provide a display of intracardiac flow without the limitations of angle sensitivity or restriction to imaging planes. Global flow patterns of the left atrium were studied in 11 healthy volunteers.

    RESULTS: In all subjects vortical flow was observed in the atrium during systole and diastolic diastasis (mean (SD) duration of systolic vortex, 280 (77) ms; and of diastolic vortex, 256 (118) ms). The volume incorporated and recirculated within the vortices originated predominantly from the left pulmonary veins. Inflow from the right veins passed along the vortex periphery, constrained between the vortex and the atrial wall.

    CONCLUSIONS: Global left atrial flow in the normal human heart comprises consistent patterns specific to the phase of the cardiac cycle. Separate paths of left and right pulmonary venous inflow and vortex formation may have beneficial effects in avoiding left atrial stasis in the normal subject in sinus rhythm.

    Keywords
    atrium, blood flow, magnetic resonance imaging, haemodynamics
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-14554 (URN)10.1136/heart.86.4.448 (DOI)
    Available from: 2007-06-04 Created: 2007-06-04 Last updated: 2016-03-14
    3. Estimation of relative cardiovascular pressures using time-resolved three-dimensional phase contrast MRI
    Open this publication in new window or tab >>Estimation of relative cardiovascular pressures using time-resolved three-dimensional phase contrast MRI
    Show others...
    2001 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 45, no 5, p. 872-879Article in journal (Refereed) Published
    Abstract [en]

    Accurate, easy-to-use, noninvasive cardiovascular pressure registration would be an important addition to the diagnostic armamentarium for assessment of cardiac function. A novel noninvasive and three-dimensional (3D) technique for estimation of relative cardiovascular pressures is presented. The relative pressure is calculated using the Navier-Stokes equations along user-defined lines placed within a time-resolved 3D phase contrast MRI dataset. The lines may be either straight or curved to follow an actual streamline. The technique is validated in an in vitro model and tested on in vivo cases of normal and abnormal transmitral pressure differences and intraaortic flow. The method supplements an intuitive visualization technique for cardiovascular flow, 3D particle trace visualization, with a quantifiable diagnostic parameter estimated from the same dataset.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-26700 (URN)10.1002/mrm.1116 (DOI)11290 (Local ID)11290 (Archive number)11290 (OAI)
    Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2017-12-13
    4. Noninvasive measurement of time-varying three-dimensional relative pressure fields within the human heart
    Open this publication in new window or tab >>Noninvasive measurement of time-varying three-dimensional relative pressure fields within the human heart
    Show others...
    2002 (English)In: Journal of Biomechanical Engineering, ISSN 0148-0731, E-ISSN 1528-8951, Vol. 124, no 3, p. 288-293Article in journal (Refereed) Published
    Abstract [en]

    Understanding cardiac blood flow patterns is important in the assessment of cardiovascular function. Three-dimensional flow and relative pressure fields within the human left ventricle are demonstrated by combining velocity measurements with computational fluid mechanics methods. The velocity field throughout the left atrium and ventricle of a normal human heart is measured using time-resolved three-dimensional phase-contrast MRL. Subsequently, the time-resolved three-dimensional relative pressure is calculated from this velocity field using the pressure Poisson equation. Noninvasive simultaneous assessment of cardiac pressure and flow phenomena is an important new tool for studying cardiac fluid dynamics.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-26710 (URN)10.1115/1.1468866 (DOI)11304 (Local ID)11304 (Archive number)11304 (OAI)
    Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2017-12-13
    5. Myocordial segmentation of time-resolved 3D phase-contrast MRI
    Open this publication in new window or tab >>Myocordial segmentation of time-resolved 3D phase-contrast MRI
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Time-resolved three-dimensional (3D) phase-contrast MRI can be used to study 3D cardiac blood flow patterns and myocardial motion. The image contrast between myocardium and blood in 3D MRl is often inadequate for clear orientation and border delineation, however. To improve the accuracy and ease of segmentation, we developed a method based on a particle trace technique for time-resolved 3D cardiac velocity vector fields. A particle trace trajectory that follows the blood flow and the myocardial motion is obtained by integration of the velocity field over time. The myocardium can be differentiated by using the magnitude image data in combination with the trajectory's velocities and the expected behavior of the myocardial particle traces, that is, that traces starting in the myocardium will return to their starting point at the end of a cardiac cycle. The myocardial probability obtained in this way can be used for visualization, which eliminates the need for acquiring additional two-dimensional images. It also serves as the basis for border delineation, allowing quantification of important clinical parameters such as ventricular volume and mass.

    Keywords
    MR velocity imaging, three-dimensional visualization, particle trace, trajectory, heart, border delineation, contrast enhancement
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-89144 (URN)
    Available from: 2013-02-22 Created: 2013-02-22 Last updated: 2013-09-03
  • 41.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, The Institute of Technology. Östergötlands Läns Landsting, Heart and Medicine Centre, Department of Clinical Physiology UHL.
    Flow Imaging: Cardiac Applications of 3D Cine Phase-Contrast MRI2011In: Current Cardiovascular Imaging Reports, ISSN 1941-9074, Vol. 4, no 2, p. 127-133Article, review/survey (Refereed)
    Abstract [en]

    Global and regional blood flow dynamics are of pivotal importance to cardiac function. Fluid mechanical forces can affect hemolysis and platelet aggregation, as well as myocardial remodeling. In recent years, assessment of blood flow patterns based on time-resolved, three-dimensional, three-directional phase-contrast MRI (3D cine PC MRI) has become possible and rapidly gained popularity. Initially, this technique was mainly known for its intuitive and appealing visualizations of the cardiovascular blood flow. Most recently, the technique has begun to go beyond compelling images toward comprehensive and quantitative assessment of blood flow. In this article, cardiac applications of 3D cine PC MRI data are discussed, starting with a review of the acquisition and analysis techniques, and including descriptions of promising applications of cardiac 3D cine PC MRI for the clinical evaluation of myocardial, valvular, and vascular disorders.

  • 42.
    Ebbers, Tino
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Brandt, Einar
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Wigström, Lars
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, The Institute of Technology.
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Myocordial segmentation of time-resolved 3D phase-contrast MRIManuscript (preprint) (Other academic)
    Abstract [en]

    Time-resolved three-dimensional (3D) phase-contrast MRI can be used to study 3D cardiac blood flow patterns and myocardial motion. The image contrast between myocardium and blood in 3D MRl is often inadequate for clear orientation and border delineation, however. To improve the accuracy and ease of segmentation, we developed a method based on a particle trace technique for time-resolved 3D cardiac velocity vector fields. A particle trace trajectory that follows the blood flow and the myocardial motion is obtained by integration of the velocity field over time. The myocardium can be differentiated by using the magnitude image data in combination with the trajectory's velocities and the expected behavior of the myocardial particle traces, that is, that traces starting in the myocardium will return to their starting point at the end of a cardiac cycle. The myocardial probability obtained in this way can be used for visualization, which eliminates the need for acquiring additional two-dimensional images. It also serves as the basis for border delineation, allowing quantification of important clinical parameters such as ventricular volume and mass.

  • 43.
    Ebbers, Tino
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dyverfeldt, Petter
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Escobar Kvitting, John-Peder
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences.
    Quantification of Mean and Fluctuating Flow2006Conference paper (Refereed)
  • 44.
    Ebbers, Tino
    et al.
    Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Farneback, Gunnar
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Improving Computation of Cardiovascular Relative Pressure Fields From Velocity MRI2009In: JOURNAL OF MAGNETIC RESONANCE IMAGING, ISSN 1053-1807, Vol. 30, no 1, p. 54-61Article in journal (Refereed)
    Abstract [en]

    Purpose: To evaluate a multigrid-based solver for the pressure Poisson equation (PPE) with Galerkin coarsening, which works directly on the specified domain, for the computation of relative pressure fields from velocity MRI data. Materials and Methods: We compared the proposed structure-defined Poisson solver to other popular Poisson solvers working on unmodified rectangular and modified quasirectangular domains using synthetic and in vitro phantoms in which the mathematical solution of the pressure field is known, as well as on in vivo MRI velocity measurements of aortic blood flow dynamics. Results: All three PPE solvers gave accurate results for convex computational domains. Using a rectangular or quasirectangular domain on a more complicated domain, like a c-shape, revealed a systematic underestimation of the pressure amplitudes, while the proposed PPE solver, working directly on the specified domain, provided accurate estimates of the relative pressure fields. Conclusion: Popular iterative approaches with quasirectangular computational domains can lead to significant systematic underestimation of the pressure amplitude. We suggest using a multigrid-based PPE solver with Galerkin coarsening, which works directly on the structure-defined computational domain. This solver provides accurate estimates of the relative pressure fields for both simple and complex geometries with additional significant improvements with respect to execution speed.

  • 45.
    Ebbers, Tino
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Fyrenius, Anna
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology.
    Wigström, Lars
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Modelling and Simulation .
    Calculation of relative cardiac pressure along streamlines using time-resolved 3D phase contrast MRI1999In: Journal of Cardiovascular Magnetic Resonance,1999, 1999, p. 290-291Conference paper (Other academic)
  • 46.
    Ebbers, Tino
    et al.
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Haraldsson, Henrik
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Dyverfeldt, Petter
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Sigfridsson, Andreas
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Warntjes, Marcel Jan Bertus
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Wigström, Lars
    Linköping University, Center for Medical Image Science and Visualization, CMIV. Linköping University, Department of Medicine and Health Sciences, Clinical Physiology . Linköping University, Faculty of Health Sciences.
    Higher order weighted least-squares phase offset correction for improved accuracy in phase-contrast MRI2008Conference paper (Refereed)
    Abstract [en]

    Phase-contrast magnetic resonance imaging has the ability to accurately measure blood flow and myocardial velocities in the human body. Unwanted spatially varying phase offsets are, however, always present and may deteriorate the measurements significantly. Some of these phase offsets can be estimated based on the pulse sequence (1), but effects caused by eddy currents are more difficult to predict. A linear fit of the phase values is often estimated from either a number of manually defined areas containing stationary tissue or by semi-automatic detection of stationary tissue using the

  • 47.
    Ebbers, Tino
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Wigström, Lars
    Linköping University, Department of Biomedical Engineering. Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Bolger, Ann
    Department of Medicine, University of California−San Francisco, San Francisco, CA.
    Engvall, Jan
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology.
    Estimation of relative cardiovascular pressures using time-resolved three-dimensional phase contrast MRI2001In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 45, no 5, p. 872-879Article in journal (Refereed)
    Abstract [en]

    Accurate, easy-to-use, noninvasive cardiovascular pressure registration would be an important addition to the diagnostic armamentarium for assessment of cardiac function. A novel noninvasive and three-dimensional (3D) technique for estimation of relative cardiovascular pressures is presented. The relative pressure is calculated using the Navier-Stokes equations along user-defined lines placed within a time-resolved 3D phase contrast MRI dataset. The lines may be either straight or curved to follow an actual streamline. The technique is validated in an in vitro model and tested on in vivo cases of normal and abnormal transmitral pressure differences and intraaortic flow. The method supplements an intuitive visualization technique for cardiovascular flow, 3D particle trace visualization, with a quantifiable diagnostic parameter estimated from the same dataset.

  • 48.
    Ebbers, Tino
    et al.
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
    Wigström, Lars
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
    Bolger, Ann
    Department of Medicine, University of California, San Francisco, CA.
    Wranne, Bengt
    Linköping University, Department of Medicine and Care, Clinical Physiology. Linköping University, Faculty of Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.
    Noninvasive measurement of time-varying three-dimensional relative pressure fields within the human heart2002In: Journal of Biomechanical Engineering, ISSN 0148-0731, E-ISSN 1528-8951, Vol. 124, no 3, p. 288-293Article in journal (Refereed)
    Abstract [en]

    Understanding cardiac blood flow patterns is important in the assessment of cardiovascular function. Three-dimensional flow and relative pressure fields within the human left ventricle are demonstrated by combining velocity measurements with computational fluid mechanics methods. The velocity field throughout the left atrium and ventricle of a normal human heart is measured using time-resolved three-dimensional phase-contrast MRL. Subsequently, the time-resolved three-dimensional relative pressure is calculated from this velocity field using the pressure Poisson equation. Noninvasive simultaneous assessment of cardiac pressure and flow phenomena is an important new tool for studying cardiac fluid dynamics.

  • 49.
    Ebbers, Tino
    et al.
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Wigström, Lars
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Fyrenius, Anna
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology.
    Bolger, Ann F
    Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Clinical Physiology. Östergötlands Läns Landsting, Heart Centre, Department of Clinical Physiology.
    Karlsson, Matts
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Biomedical Modelling and Simulation .
    Particle trace visualization of cardiac flow patterns using 3D phase contrast MRI: an in vitro comparison with streamlines created using dye.1999In: Proc Intl Soc Magn Reson Med 7,1999, 1999, p. 2025-2025Conference paper (Other academic)
  • 50.
    Eriksson, Jonatan
    et al.
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Cardiology. Linköping University, Faculty of Health Sciences.
    Bolger, Ann F.
    Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Carlhäll, Carl-Johan
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Clinical Physiology. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping.
    Ebbers, Tino
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Physiology. Linköping University, Faculty of Health Sciences. Linköping University, Department of Science and Technology, Media and Information Technology.
    Spatial heterogeneity of 4D relative pressure fields in the human left ventricle2013Manuscript (preprint) (Other academic)
    Abstract [en]

    Blood flow throughout the cardiovascular system is driven by pressure differences generated by the contraction and relaxation of the heart, where blood accelerates from high to low pressure areas. Absolute intracardiac pressure cannot be measured noninvasively, but relative pressure can be calculated. The aim of this study was to assess the spatial heterogeneity of the 4D relative pressure fields in the human left ventricle (LV).

    Twelve healthy subjects underwent MRI examination where 4D flow as well as morphological data were acquired. The morphological data were segmented, and the segmentation used as boundary condition when computing relative pressure fields from the pressure Poisson equation using a multi grid solver. The LV lumen was divided according to a seventeen segment model in order to assess spatial heterogeneity and present the extensive amount of data in a comprehensive manner.

    The basal anteroseptal segment shows a significantly lower median pressure than the opposite basal inferolateral segment during both early and late diastolic filling (p<0.0005 and p=0.0024, respectively). Along the long axis, the relative pressure in the apical segments are significantly higher relative to the basal segments (p<0.0005) along both the anteroseptal and inferolateral sides at and after the peaks of E-wave and A-wave.

    During diastole the main pressure differences in the LV occur along the basal-apical axis. However, pressure differences can also be found in the short-axis direction, and may also reflect important aspects of atrioventricular coupling.

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