Plaque Progression Modeling for Coronary Flow Treatment Planning
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Solution Overview
Problem
Current methods for diagnosing and treating coronary artery disease lack accurate data on plaque characteristics, geometry, and functional significance, leading to unnecessary invasive treatments and suboptimal treatment planning.
Innovation Solution
Systems and methods for treatment planning based on plaque progression and regression curves, using computational models to analyze patient-specific data, predict plaque geometry changes, and calculate blood flow characteristics, generating graphical displays to inform treatment decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive catheterization is used to measure FFR, then measurement accuracy is improved, but patient risk and procedure complexity increase
Solution Approach 1:
The patent replaces the mechanical invasive catheterization system with a non-invasive computational modeling system that uses CT scan data and blood flow modeling algorithms to calculate FFR, eliminating the need for physical catheter insertion while maintaining measurement capability
Solution Approach 2:
The patent introduces computational blood flow modeling as an intermediary between the CT scan images and the FFR measurement, using mathematical models to simulate blood flow dynamics and derive FFR values without direct arterial access
2Measurement precision
If more accurate plaque data is collected, then treatment planning quality is improved, but diagnostic complexity and cost increase
Solution Approach 1:
The patent creates a multi-functional system that simultaneously performs plaque detection, geometry characterization, blood flow modeling, and FFR calculation from a single CT scan dataset, allowing multiple diagnostic objectives to be achieved through one integrated platform
Solution Approach 2:
The patent performs preliminary computational modeling and simulation during the diagnostic planning phase, calculating various scenarios and outcomes before treatment decisions are made, allowing clinicians to evaluate multiple treatment pathways in advance
3Productivity
If computational modeling is used to predict plaque progression, then treatment planning is optimized, but calculation time and processing requirements increase
Solution Approach 1:
The patent performs preliminary computational modeling during the initial diagnostic phase, establishing baseline blood flow models and plaque characteristics that can be used for treatment planning before the actual treatment decision requires final calculations
Solution Approach 2:
The patent implements dynamic adaptive modeling that adjusts calculation complexity based on clinical needs, using simplified models for routine cases and more complex simulations only when clinically indicated, optimizing the balance between accuracy and computation time
Data Source
AI summary
Systems and methods are disclosed for evaluating a patient with vascular disease. One method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of a location of disease in the patient's vasculature based on the received patient-specific data; identifying one or more changes in geometry of the anatomic model based on a modeled progression or regression of disease at the location; calculating one or more values of a blood flow characteristic within the patient's vasculature using a computational model based on the identified one or more changes in geometry of the anatomic model; and generating an electronic graphical display of a relationship between the one or more values of the calculated blood flow characteristic and the identified one or more changes in geometry of the anatomic model.