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  • 1. Order onlineBuy this publication >>
    Casas Garcia, Belén
    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).
    Towards Personalized Models of the Cardiovascular System Using 4D Flow MRI2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Current diagnostic tools for assessing cardiovascular disease mostly focus on measuring a given biomarker at a specific spatial location where an abnormality is suspected. However, as a result of the dynamic and complex nature of the cardiovascular system, the analysis of isolated biomarkers is generally not sufficient to characterize the pathological mechanisms behind a disease. Model-based approaches that integrate the mechanisms through which different components interact, and present possibilities for system-level analyses, give us a better picture of a patient’s overall health status.

    One of the main goals of cardiovascular modelling is the development of personalized models based on clinical measurements. Recent years have seen remarkable advances in medical imaging and the use of personalized models is slowly becoming a reality. Modern imaging techniques can provide an unprecedented amount of anatomical and functional information about the heart and vessels. In this context, three-dimensional, three-directional, cine phase-contrast (PC) magnetic resonance imaging (MRI), commonly referred to as 4D Flow MRI, arises as a powerful tool for creating personalized models. 4D Flow MRI enables the measurement of time-resolved velocity information with volumetric coverage. Besides providing a rich dataset within a single acquisition, the technique permits retrospective analysis of the data at any location within the acquired volume.

    This thesis focuses on improving subject-specific assessment of cardiovascular function through model-based analysis of 4D Flow MRI data. By using computational models, we aimed to provide mechanistic explanations of the underlying physiological processes, derive novel or improved hemodynamic markers, and estimate quantities that typically require invasive measurements. Paper I presents an evaluation of current markers of stenosis severity using advanced models to simulate flow through a stenosis. Paper II presents a framework to personalize a reduced-order, mechanistic model of the cardiovascular system using exclusively non-invasive measurements, including 4D Flow MRI data. The modelling approach can unravel a number of clinically relevant parameters from the input data, including those representing the contraction and relaxation patterns of the left ventricle, and provide estimations of the pressure-volume loop. In Paper III, this framework is applied to study cardiovascular function at rest and during stress conditions, and the capability of the model to infer load-independent measures of heart function based on the imaging data is demonstrated. Paper IV focuses on evaluating the reliability of the model parameters as a step towards translation of the model to the clinic.

    List of papers
    1. 4D Flow MRI-Based Pressure Loss Estimation in Stenotic Flows: Evaluation Using Numerical Simulations
    Open this publication in new window or tab >>4D Flow MRI-Based Pressure Loss Estimation in Stenotic Flows: Evaluation Using Numerical Simulations
    2016 (English)In: Magnetic Resonance in Medicine, ISSN 0740-3194, E-ISSN 1522-2594, Vol. 75, no 4, p. 1808-1821Article in journal (Refereed) Published
    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) > 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.

    Place, publisher, year, edition, pages
    WILEY-BLACKWELL, 2016
    Keywords
    pressure loss; phase contrast magnetic resonance imaging; aortic valve disease; aortic coarctation
    National Category
    Clinical Medicine
    Identifiers
    urn:nbn:se:liu:diva-127426 (URN)10.1002/mrm.25772 (DOI)000372910900043 ()26016805 (PubMedID)
    Note

    Funding Agencies|European Research Council [310612]; Swedish Research Council

    Available from: 2016-05-01 Created: 2016-04-26 Last updated: 2018-10-10
    2. Bridging the gap between measurements and modelling: a cardiovascular functional avatar
    Open this publication in new window or tab >>Bridging the gap between measurements and modelling: a cardiovascular functional avatar
    Show others...
    2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 6214Article in journal (Refereed) Published
    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.

    Place, publisher, year, edition, pages
    Nature Publishing Group, 2017
    National Category
    Biomedical Laboratory Science/Technology
    Identifiers
    urn:nbn:se:liu:diva-140069 (URN)10.1038/s41598-017-06339-0 (DOI)000406260100018 ()28740184 (PubMedID)2-s2.0-85025821468 (Scopus ID)
    Note

    Funding Agencies|European Research Council [310612]; Swedish Research Council [2014-6191]

    Available from: 2017-08-28 Created: 2017-08-28 Last updated: 2018-10-10Bibliographically approved
  • 2.
    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) > 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.

  • 3.
    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.

  • 4.
    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).
    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. Univ Calif San Francisco, CA USA.
    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).
    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).
    Non-invasive Assessment of Systolic and Diastolic Cardiac Function During Rest and Stress Conditions Using an Integrated Image-Modeling Approach2018In: Frontiers in Physiology, ISSN 1664-042X, E-ISSN 1664-042X, Vol. 9, article id 1515Article in journal (Refereed)
    Abstract [en]

    Background: The possibility of non-invasively assessing load-independent parameters characterizing cardiac function is of high clinical value. Typically, these parameters are assessed during resting conditions. However, for diagnostic purposes, the parameter behavior across a physiologically relevant range of heart rate and loads is more relevant than the isolated measurements performed at rest. This study sought to evaluate changes in non-invasive estimations of load-independent parameters of left-ventricular contraction and relaxation patterns at rest and during dobutamine stress. Methods: We applied a previously developed approach that combines non-invasive measurements with a physiologically-based, reduced-order model of the cardiovascular system to provide subject-specific estimates of parameters characterizing left ventricular function. In this model, the contractile state of the heart at each time point along the cardiac cycle is modeled using a time-varying elastance curve. Non-invasive data, including four-dimensional magnetic resonance imaging (4D Flow MRI) measurements, were acquired in nine subjects without a known heart disease at rest and during dobutamine stress. For each of the study subjects, we constructed two personalized models corresponding to the resting and the stress state. Results: Applying the modeling framework, we identified significant increases in the left ventricular contraction rate constant [from 1.5 +/- 0.3 to 2 +/- 0.5 (p = 0.038)] and relaxation constant [from 37.2 +/- 6.9 to 46.1 +/- 12 (p = 0.028)]. In addition, we found a significant decrease in the elastance diastolic time constant from 0.4 +/- 0.04 s to 0.3 +/- 0.03 s = 0.008). Conclusions: The integrated image-modeling approach allows the assessment of cardiovascular function given as model-based parameters. The agreement between the estimated parameter values and previously reported effects of dobutamine demonstrates the potential of the approach to assess advanced metrics of pathophysiology that are otherwise difficult to obtain non-invasively in clinical practice.

  • 5.
    Ha, Hojin
    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.
    Haraldsson, Henrik
    University of Calif San Francisco, CA 94143 USA.
    Casas Garcia, Belén
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Ziegler, Magnus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Saloner, David
    University of Calif San Francisco, CA 94143 USA.
    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, 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).
    Assessment of turbulent viscous stress using ICOSA 4D Flow MRI for prediction of hemodynamic blood damage2016In: SCIENTIFIC REPORTS, ISSN 2045-2322, Vol. 6, article id 39773Article in journal (Refereed)
    Abstract [en]

    Flow-induced blood damage plays an important role in determining the hemodynamic impact of abnormal blood flow, but quantifying of these effects, which are dominated by shear stresses in highly fluctuating turbulent flow, has not been feasible. This study evaluated the novel application of turbulence tensor measurements using simulated 4D Flow MRI data with six-directional velocity encoding for assessing hemodynamic stresses and corresponding blood damage index (BDI) in stenotic turbulent blood flow. The results showed that 4D Flow MRI underestimates the maximum principal shear stress of laminar viscous stress (PLVS), and overestimates the maximum principal shear stress of Reynolds stress (PRSS) with increasing voxel size. PLVS and PRSS were also overestimated by about 1.2 and 4.6 times at medium signal to noise ratio (SNR) = 20. In contrast, the square sum of the turbulent viscous shear stress (TVSS), which is used for blood damage index (BDI) estimation, was not severely affected by SNR and voxel size. The square sum of TVSS and the BDI at SNR amp;gt;20 were underestimated by less than 1% and 10%, respectively. In conclusion, this study demonstrated the feasibility of 4D Flow MRI based quantification of TVSS and BDI which are closely linked to blood damage.

  • 6.
    Ha, Hojin
    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.
    Ziegler, Magnus
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Casas Garcia, Belén
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Karlsson, Matts
    Linköping University, Department of Management and Engineering, Applied Thermodynamics and Fluid Mechanics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Dyverfeldt, Petter
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Clinical Physiology in Linköping. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    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).
    Estimating the irreversible pressure drop across a stenosis by quantifying turbulence production using 4D Flow MRI2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 46618Article in journal (Refereed)
    Abstract [en]

    The pressure drop across a stenotic vessel is an important parameter in medicine, providing a commonly used and intuitive metric for evaluating the severity of the stenosis. However, non-invasive estimation of the pressure drop under pathological conditions has remained difficult. This study demonstrates a novel method to quantify the irreversible pressure drop across a stenosis using 4D Flow MRI by calculating the total turbulence production of the flow. Simulation MRI acquisitions showed that the energy lost to turbulence production can be accurately quantified with 4D Flow MRI within a range of practical spatial resolutions (1-3 mm; regression slope = 0.91, R-2 = 0.96). The quantification of the turbulence production was not substantially influenced by the signal-to-noise ratio (SNR), resulting in less than 2% mean bias at SNR amp;gt; 10. Pressure drop estimation based on turbulence production robustly predicted the irreversible pressure drop, regardless of the stenosis severity and post-stenosis dilatation (regression slope = 0.956, R-2 = 0.96). In vitro validation of the technique in a 75% stenosis channel confirmed that pressure drop prediction based on the turbulence production agreed with the measured pressure drop (regression slope = 1.15, R-2 = 0.999, Bland-Altman agreement = 0.75 +/- 3.93 mmHg).

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