Prosthetic Valve Sizing via 3D Hemodynamic Simulation
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Solution Overview
Problem
Current methods for transcatheter heart valve replacement face challenges in accurately sizing and positioning prosthetic valves, leading to complications such as paravalvular regurgitation due to reliance on two-dimensional imaging, which may not provide precise anatomic information, resulting in high incidence of adverse clinical events.
Innovation Solution
A computer-implemented method and system for modeling and simulation that uses patient-specific anatomic, geometric, and hemodynamic data to create a digital model of the heart valve and surrounding vasculature, allowing for accurate sizing and deployment planning, incorporating sensitivity and uncertainty analyses to minimize risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If two-dimensional imaging is used for valve sizing and positioning, then the imaging process is simple and quick, but the anatomic information precision is insufficient leading to inaccurate valve sizing
Solution Approach 1:
The patent transitions from two-dimensional imaging to three-dimensional modeling and simulation, adding spatial dimensions to the analysis. This enables accurate representation of complex cardiac anatomy including valve structure, vessel geometry, and blood flow patterns, thereby improving measurement precision without being constrained by planar limitations
Solution Approach 2:
The patent introduces computational modeling and simulation as an intermediary between imaging and clinical decision-making. This intermediary process transforms raw imaging data into comprehensive three-dimensional anatomical models, allowing clinicians to visualize and measure complex structures more accurately before making treatment decisions
2Manufacturing precision
If accurate three-dimensional modeling and simulation are implemented, then valve sizing and positioning precision is improved, but the system complexity and computational requirements increase
Solution Approach 1:
The patent performs comprehensive three-dimensional modeling, sensitivity analysis, and uncertainty analysis before the actual valve implantation procedure. By conducting virtual simulations in advance, the system allows clinicians to optimize valve sizing and positioning decisions without adding complexity during the actual surgical procedure, thereby improving placement precision while managing overall system complexity
Solution Approach 2:
The patent creates virtual three-dimensional copies of the patient's specific cardiac anatomy through computational modeling. These digital twins allow for repeated simulation and analysis without requiring additional physical imaging or increasing surgical complexity, enabling precise pre-planning of valve placement
3Reliability
If comprehensive sensitivity and uncertainty analyses are performed, then the reliability of treatment planning is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs sensitivity and uncertainty analyses as preliminary steps before final treatment decisions are made. By completing these computationally intensive analyses in advance, the system ensures reliable treatment planning while allowing clinicians to make informed decisions without time pressure during the actual procedure
Solution Approach 2:
The computational model automatically performs sensitivity and uncertainty analyses using the collected imaging and patient data. The system self-evaluates the reliability of its own predictions by systematically varying input parameters and assessing their impact on outcomes, thereby improving treatment planning reliability through automated rather than manual analysis
Data Source
AI summary
A computer-implemented method for simulating blood flow through one or more coronary blood vessels may first involve receiving patient-specific data, including imaging data related to one or more coronary blood vessels, and at least one clinically measured flow parameter. Next, the method may involve generating a digital model of the one or more coronary blood vessels, based at least partially on the imaging data, discretizing the model, applying boundary conditions to a portion of the digital model that contains the one or more coronary blood vessels, and initializing and solving mathematical equations of blood flow through the model to generate computerized flow parameters. Finally, the method may involve comparing the computerized flow parameters with the at least one clinically measured flow parameter.