3D Coronary Blood Flow Modeling for Noninvasive FFR Assessment
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Solution Overview
Problem
Current methods for assessing coronary artery disease, such as coronary computed tomographic angiography (CCTA) and diagnostic cardiac catheterization, fail to provide accurate, noninvasive data on the functional significance of coronary lesions, leading to unnecessary invasive procedures and healthcare costs.
Innovation Solution
A system and method for creating a patient-specific three-dimensional model of coronary blood flow using noninvasive imaging data, coupled with computational analysis to determine functional parameters like fractional flow reserve (FFR), allowing for noninvasive assessment of lesion significance and prediction of treatment outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noninvasive imaging methods like CCTA are used to assess coronary lesions, then patient safety and comfort are improved, but functional significance assessment capability deteriorates
Solution Approach 1:
The patent creates a virtual copy of the patient's coronary anatomy through 3D reconstruction from CCTA images. This digital model replicates the vascular structure, allowing computational simulation of blood flow and pressure without physical intrusion. The virtual model enables FFR calculation by simulating physiological conditions that would otherwise require invasive wire insertion.
Solution Approach 2:
The patent replaces the mechanical invasive measurement system (pressure wires, catheters) with a computational fluid dynamics system. Instead of physically inserting devices into vessels to measure pressure gradients, the system uses numerical simulations based on Navier-Stokes equations to calculate FFR from noninvasive imaging data, substituting mechanical measurement with computational analysis.
2Measurement precision
If invasive diagnostic cardiac catheterization is performed to obtain functional data, then measurement accuracy is improved, but patient risk and procedure complexity increase
Solution Approach 1:
The patent creates a virtual replica of the coronary vasculature from noninvasive CCTA images. This 3D reconstructed model captures the anatomical geometry, including lesions and vessel characteristics, enabling computational simulation that replaces invasive catheter-based measurements while maintaining diagnostic accuracy for functional significance assessment.
Solution Approach 2:
The patent introduces computational fluid dynamics simulation as an intermediary between noninvasive imaging and functional assessment. Rather than directly measuring pressure with invasive wires, the system uses CFD algorithms as a mediator to translate anatomical images into functional data (FFR values), bridging the gap between structural imaging and physiological evaluation.
3Ease of operation
If traditional imaging methods are used to visualize coronary anatomy, then anatomical data acquisition is simplified, but blood flow dynamics assessment capability is lost
Solution Approach 1:
The patent merges anatomical imaging (CCTA) with hemodynamic simulation (CFD) into a unified diagnostic workflow. The 3D reconstruction from CCTA images is combined with computational blood flow modeling, allowing simultaneous visualization of both anatomy and flow dynamics. This integration enables extraction of FFR and other hemodynamic parameters from standard anatomical imaging without requiring separate procedures.
Solution Approach 2:
The patent transitions from 2D anatomical images to 3D volumetric models, then to 4D simulations that incorporate temporal dynamics of blood flow. By adding the dimension of time and flow physics to static anatomical data, the system extracts dynamic hemodynamic information (velocity, pressure, FFR) from conventional imaging, revealing functional characteristics beyond anatomical structure.
Data Source
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AI summary
A system for determining cardiovascular information for a patient comprises: at least one computer system configured to: obtain and pre-process patient-specific anatomical data (100); create a three-dimensional model representing at least a portion of the patient's anatomy based on the obtained anatomical data (200); prepare said model for analysis and determine boundary conditions of the model (300), said boundary conditions providing information about the three-dimensional model at its boundaries; and perform a computational analysis using the prepared three-dimensional model and the determined boundary conditions (400) and output the results.