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Prediction of healthy mitral valve hemodynamics in children and adults : validation of fluid-structure interaction simulations against echocardiography and magnetic resonance imaging

Christierson, Lea LU ; Frieberg, Petter LU ; Liuba, Petru LU ; Hedström, Erik LU orcid ; Revstedt, Johan LU ; Isaksson, Hanna LU orcid and Hakacova, Nina LU (2025) In Computers in Biology and Medicine 194.
Abstract

Background: The mitral valve is essential for proper heart function. Patient-specific simulations may provide insights into valve function and provide hemodynamic information for treatment planning. This study presents a framework for patient-specific mitral valve hemodynamic prediction and the validation of the simulation model against echocardiographic and MRI data. Methods: Ten healthy volunteers (age range/median: 1–37/13 years) underwent echocardiographic exams, of which five also underwent cardiac MRI. Patient-specific mitral valve geometries were segmented from 3D echocardiograms, while mass flow boundary conditions were derived from left ventricular volume data obtained via echocardiography and MRI. The mitral apparatus,... (More)

Background: The mitral valve is essential for proper heart function. Patient-specific simulations may provide insights into valve function and provide hemodynamic information for treatment planning. This study presents a framework for patient-specific mitral valve hemodynamic prediction and the validation of the simulation model against echocardiographic and MRI data. Methods: Ten healthy volunteers (age range/median: 1–37/13 years) underwent echocardiographic exams, of which five also underwent cardiac MRI. Patient-specific mitral valve geometries were segmented from 3D echocardiograms, while mass flow boundary conditions were derived from left ventricular volume data obtained via echocardiography and MRI. The mitral apparatus, including the chordae, was modeled in a simplified left heart and simulated in a computational model using fluid-structure interaction. Results: The simulations captured the valvular behavior and hemodynamics of the left heart throughout the cardiac cycle. We found an average difference of 3.6 ± 29 % and 8.3 ± 22 % in the maximum and mean transvalvular velocity compared to Doppler data. Echocardiography underestimated end-systolic and end-diastolic volumes by 1.8 ± 20 % and 19 ± 3.8 % compared to MRI. The average maximum principal strain over the mitral valve was 5.8 % during systole and 6.7 % during diastole, consistent with literature. Conclusions: A computational framework for clinically feasible patient-specific prediction of mitral valve hemodynamics was developed and validated in vivo in the largest cohort presented to date. Computational time was acceptable for clinical planning. This is a step towards personalized surgical planning of valve repair and an increased understanding of the hemodynamics and mitral valve function after intervention.

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author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Fluid-structure interaction, Hemodynamics, Mitral valve, Patient-specific, Prediction, Validation
in
Computers in Biology and Medicine
volume
194
article number
110455
publisher
Elsevier
external identifiers
  • scopus:105007011819
  • pmid:40460569
ISSN
0010-4825
DOI
10.1016/j.compbiomed.2025.110455
language
English
LU publication?
yes
id
bbe32085-3efd-4b48-8189-92f404be16d5
date added to LUP
2025-07-16 13:45:07
date last changed
2025-07-17 03:04:32
@article{bbe32085-3efd-4b48-8189-92f404be16d5,
  abstract     = {{<p>Background: The mitral valve is essential for proper heart function. Patient-specific simulations may provide insights into valve function and provide hemodynamic information for treatment planning. This study presents a framework for patient-specific mitral valve hemodynamic prediction and the validation of the simulation model against echocardiographic and MRI data. Methods: Ten healthy volunteers (age range/median: 1–37/13 years) underwent echocardiographic exams, of which five also underwent cardiac MRI. Patient-specific mitral valve geometries were segmented from 3D echocardiograms, while mass flow boundary conditions were derived from left ventricular volume data obtained via echocardiography and MRI. The mitral apparatus, including the chordae, was modeled in a simplified left heart and simulated in a computational model using fluid-structure interaction. Results: The simulations captured the valvular behavior and hemodynamics of the left heart throughout the cardiac cycle. We found an average difference of 3.6 ± 29 % and 8.3 ± 22 % in the maximum and mean transvalvular velocity compared to Doppler data. Echocardiography underestimated end-systolic and end-diastolic volumes by 1.8 ± 20 % and 19 ± 3.8 % compared to MRI. The average maximum principal strain over the mitral valve was 5.8 % during systole and 6.7 % during diastole, consistent with literature. Conclusions: A computational framework for clinically feasible patient-specific prediction of mitral valve hemodynamics was developed and validated in vivo in the largest cohort presented to date. Computational time was acceptable for clinical planning. This is a step towards personalized surgical planning of valve repair and an increased understanding of the hemodynamics and mitral valve function after intervention.</p>}},
  author       = {{Christierson, Lea and Frieberg, Petter and Liuba, Petru and Hedström, Erik and Revstedt, Johan and Isaksson, Hanna and Hakacova, Nina}},
  issn         = {{0010-4825}},
  keywords     = {{Fluid-structure interaction; Hemodynamics; Mitral valve; Patient-specific; Prediction; Validation}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Computers in Biology and Medicine}},
  title        = {{Prediction of healthy mitral valve hemodynamics in children and adults : validation of fluid-structure interaction simulations against echocardiography and magnetic resonance imaging}},
  url          = {{http://dx.doi.org/10.1016/j.compbiomed.2025.110455}},
  doi          = {{10.1016/j.compbiomed.2025.110455}},
  volume       = {{194}},
  year         = {{2025}},
}