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CT-Based Analysis of Left Ventricular Hemodynamics Using Statistical Shape Modeling and Computational Fluid Dynamics.

Leonid Goubergrits1,2, Katharina Vellguth1, Lukas Obermeier1

  • 1Institute of Computer-Assisted Cardiovascular Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany.

Frontiers in Cardiovascular Medicine
|July 22, 2022
PubMed
Summary

This study introduces a new method combining cardiac computed tomography (CCT) with computational fluid dynamics (CFD) and statistical shape modeling (SSM) to analyze intracardiac blood flow. The approach reveals how heart shape and function impact blood flow, aiding in diagnosing heart diseases.

Keywords:
cardiac computed tomographycomputational fluid dynamicsfluid-structure interactionintraventricular hemodynamicsleft ventricle aneurysmsmitral regurgitationstatistical shape modeling

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Area of Science:

  • Cardiovascular Imaging and Hemodynamics
  • Computational Biology and Medical Simulation

Background:

  • Intracardiac flow analysis is crucial for early heart disease detection and treatment planning.
  • High variability in heart shape and contractility presents challenges in understanding intracardiac flow.
  • Statistical Shape Modeling (SSM) combined with Computational Fluid Dynamics (CFD) offers a potential solution for analyzing complex intracardiac flow patterns.

Purpose of the Study:

  • To demonstrate the usability of a novel approach integrating CCT, CFD, and SSM for analyzing intracardiac hemodynamics across diverse patient cohorts.
  • To investigate the impact of left ventricular (LV) aneurysm and mitral regurgitation (MR) on intracardiac flow characteristics.

Main Methods:

  • Generation of SSMs from CCT data of 125 patients, representing aneurysmatic and non-aneurysmatic LVs.
  • Creation of seven group-averaged LV shapes and contraction fields based on aneurysm status, MR severity, and LV contractility.
  • Simulation of intracardiac flow using prescribed motion CFD, analyzing features like kinetic energy, washout, and pressure gradients.

Main Results:

  • SSMs captured significant variations in LV shape and contractility, with approximately 30 modes describing 90% of the shape variance.
  • Hemodynamic analysis revealed shape-, contractility-, and MR-dependent differences in blood flow.
  • Disturbed apical blood washout was observed in aneurysmatic cases, with globally hypokinetic LVs showing the poorest overall washout.

Conclusions:

  • The CCT-based CFD and SSM approach shows promise for facilitating intracardiac flow analysis, enhancing the diagnostic value of CCT.
  • This methodology has the potential to be integrated into clinical workflows to support diagnostic and treatment decisions for heart diseases.
  • Further computational enhancements could lead to widespread clinical adoption and improved patient care.