Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image-based CFD

Vellguth, Katharina; Brüning, Jan; Goubergrits, Leonid; Tautz, Lennart; Hennemuth, Anja; Kertzscher, Ulrich; Degener, F.; Kelm, Marcus; Sündermann, Simon H.; Küehne, Titus

doi:10.1007/s11548-018-1821-8

Cited by 19 publications

(18 citation statements)

References 28 publications

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“…Vellguth et al [21] developed an efficient pipeline using semiautomatic segmentation and geometric modeling packages but applied the pipelines to only one set of patient data. These recent approaches, while accelerating some part of the model construction process, still require various operator-dependent steps, employ closed-source software packages, or have been tested with very few examples.…”

Section: Introductionmentioning

confidence: 99%

Automating Model Generation for Image-Based Cardiac Flow Simulation

Kong

Shadden

2020

Journal of Biomechanical Engineering

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Computational fluid dynamics (CFD) modeling of left ventricle (LV) flow combined with patient medical imaging data has shown great potential in obtaining patient-specific hemodynamics information for functional assessment of the heart. A typical model construction pipeline usually starts with segmentation of the LV by manual delineation followed by mesh generation and registration techniques using separate software tools. However, such approaches usually require significant time and human efforts in the model generation pro-cess, limiting large-scale analysis. In this study, we propose an approach towards fully automating the model generation process for CFD simulation of LV flow to significantly reduce LV CFD model generation time. Our modeling framework leverages a novel combination of techniques including deep-learning based segmentation, geometry processing, and image registration to reliably reconstruct CFD-suitable LV models with little-to-no user intervention. We utilized an ensemble of 2D convolutional neural networks (CNNs) for automatic segmentation of cardiac structures from 3D patient images and our segmentation approach outperformed recent state-of-the-art segmentation techniques when evaluated on benchmark data containing both MR and CT cardiac scans. We demonstrate that through a combination of segmentation and geometry processing, we were able to robustly create CFD-suitable LV meshes from segmentations for 78 out of 80 test cases. Although the focus on this study is on image-to-mesh generation, we demonstrate the feasibility of this framework in supporting LV hemodynamics modeling by performing CFD simulations from two representative time-resolved patient-specific image data sets.

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Section: Introductionmentioning

confidence: 99%

Automating Model Generation for Image-Based Cardiac Flow Simulation

Kong

Shadden

2020

Journal of Biomechanical Engineering

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“…Hemodynamics inside the left heart can now be simulated using patient-specific data, providing unique opportunities for disease diagnosis or the treatment of individuals [31]. Virtual surgery with different surgical scenarios [64] could be tested before the actual operation, thus, helping surgeons evaluate a wide range of options prior to entering the operation room [50]. Therefore, the development of versatile and efficient numerical methods for solving the patient-specific hemodynamic problems, especially problems involving fluid-structure interaction with prosthetic valves, remains a frontier research problem and is at the center of much of the ongoing research in the field today [7,54,65].…”

Section: Patient-specific Anatomy and The Dynamics Of γ LVmentioning

confidence: 99%

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

Usta

Aidun

et al. 2022

Fluids

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Given the complexity of human left heart anatomy and valvular structures, the fluid–structure interaction (FSI) simulation of native and prosthetic valves poses a significant challenge for numerical methods. In this review, recent numerical advancements for both fluid and structural solvers for heart valves in patient-specific left hearts are systematically considered, emphasizing the numerical treatments of blood flow and valve surfaces, which are the most critical aspects for accurate simulations. Numerical methods for hemodynamics are considered under both the continuum and discrete (particle) approaches. The numerical treatments for the structural dynamics of aortic/mitral valves and FSI coupling methods between the solid Ωs and fluid domain Ωf are also reviewed. Future work toward more advanced patient-specific simulations is also discussed, including the fusion of high-fidelity simulation within vivo measurements and physics-based digital twining based on data analytics and machine learning techniques.

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“…The results regarding the possible interaction between ventricular flow fields and mechano-energetics substantiate further studies to delineate the underlying mechanisms. Eventually, the isolated heart setup may contribute to the development and validation of computer assisted therapy planning tools [6].…”

Section: Cardiac Mechano-energeticsmentioning

confidence: 99%

“…Hereby motivated, the aim of this study was to establish an isolated beating porcine heart setup which permits the investigation of the complex relationship between flow structures, hemodynamic parameters and cardiac mechano-energetics under defined conditions following selected mitral valve interventions. This setup may not only contribute to fundamental insights into postinterventional cardiac physiology, but also function as a validation tool for numerical methods [6], approaching the need for improved therapy planning support.…”

Section: Introductionmentioning

confidence: 99%

Intraventricular flow features and cardiac mechano-energetics after mitral valve interventions – feasibility of an isolated heart model

Vellguth

Sündermann

Escher

et al. 2020

Current Directions in Biomedical Engineering

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The aim of this work was the development of an isolated heart setup to delineate the interactions between intraventricular flow features, hemodynamic parameters and mechano-energetics after certain mitral valve therapies. Five porcine hearts were explanted and prepared for (i) edge-to-edge mitral valve repair, (ii) implantation of a rotatable biscupid mechanical valve prosthesis. Flow structures were visualized using echocardiography while hemodynamics was recorded in terms of pressures, flow rates and ventricular volume. Hemodynamic and cardiac mechano-energetics implied a marginal effect (<5%) of alternating leaflet orientation on ventricular pre-load and stroke work. After edge-to-edge repair, substantial variations in flow structures were observed. Beside promoting profound insights into fundamental physiologic mechanisms, the setup may be used for validation of computer aided therapy planning tools.

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Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image-based CFD

Abstract: The presented approach allows fast simulation of the diastolic hemodynamic situation before and after treatment of a mitral valve insufficiency. However, this approach is limited to the early diastolic phase of the cardiac cycle and needs to be validated using a larger sample size.

Cited by 19 publications

References 28 publications

Automating Model Generation for Image-Based Cardiac Flow Simulation

Automating Model Generation for Image-Based Cardiac Flow Simulation

Computational Methods for Fluid-Structure Interaction Simulation of Heart Valves in Patient-Specific Left Heart Anatomies

Intraventricular flow features and cardiac mechano-energetics after mitral valve interventions – feasibility of an isolated heart model

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