Patient-Specific Mitral Valve CAD Modeling for Clip Placement Simulation
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Solution Overview
Problem
Existing methods for treating mitral regurgitation (MR) do not effectively simulate the dynamics of the mitral valve and blood flow, limiting the customization and efficacy of transcatheter edge-to-edge treatments.
Innovation Solution
A patient-specific CAD model is generated using a multi-physics approach combining a CAD model of the mitral valve with a lumped parameter hemodynamics model, calibrated to match physiological and anatomical parameters, allowing for simulation of clip placement and adjustment to improve post-operative outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-physics model combining CAD model of mitral valve with lumped parameter hemodynamics model is used, then the accuracy of simulating mitral valve dynamics and blood flow is improved, but the device complexity increases
Solution Approach 1:
The system segments the complex hemodynamics simulation into a lumped parameter model that separates blood flow dynamics from structural valve dynamics. The hemodynamics model computes pressures and flows at key locations (left atrium, left ventricle, aorta, pulmonary artery) independently, which are then applied as boundary conditions to the CAD model of the mitral valve. This segmentation allows accurate multi-physics simulation while managing computational complexity through modular architecture.
2Reliability
If patient-specific calibration is performed to match physiological and anatomical parameters, then the reliability of treatment prediction is improved, but the time and computational resources required increase
Solution Approach 1:
The system performs preliminary calibration of the multi-physics model using patient-specific anatomical parameters obtained from medical imaging (CT or MRI scans) before treatment simulation. The calibration process adjusts model parameters such as annulus dimensions, leaflet geometry, and chordae tendineae configuration to match the patient's actual anatomy. This preliminary action ensures that subsequent treatment predictions are reliable and patient-specific, reducing the need for iterative adjustments during actual treatment planning.
3Object-affected harmful factors
If in silico clinical trials are conducted to assess treatment efficacy before actual treatment, then the risk to patient safety is reduced, but the complexity of treatment planning increases
Solution Approach 1:
The system creates a virtual copy of the patient's mitral valve and cardiovascular system using the multi-physics model and patient-specific anatomical data. This digital twin allows clinicians to perform in silico clinical trials by simulating different treatment scenarios (e.g., various clip positions, different numbers of clips) on the virtual model before committing to actual treatment. The virtual copy accurately reproduces hemodynamic responses and valve mechanics, enabling safe assessment of treatment efficacy without exposing the actual patient to risks.
Data Source
AI summary
Systems and method for generating a patient specific CAD model of a mitral valve include receiving digital images of a mitral valve of a patient and segmenting the digital images to identify structures of the mitral valve. A CAD model of the mitral valve is generated including modeled structures representing the identified structures. The modeled structures in the CAD model are connected at multiple locations. First loading conditions for the modeled structures are determined using a first hemodynamics model. Movement of the modeled structures are simulated based on the first loading conditions. A specified area is determined based on the CAD model. Second loading conditions are determined using a second hemodynamics model that receives the specified area as an input. The CAD model is calibrated by modifying a configuration of the modeled structures in the CAD model based on the loading conditions and movement of the modeled structures.