Coronary Artery 3D Model FFR Computation
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Solution Overview
Problem
Current non-invasive imaging technologies for coronary artery stenosis assessment lack functional significance information, leading to high false positive rates and overestimation of stenosis severity, as they primarily rely on anatomical indices without providing hemodynamic data.
Innovation Solution
A method and system for determining fractional flow reserve (FFR) from medical image data using a 3D model of the coronary artery tree, simulating blood flow, and applying an analytical model to predict pressure drops based on stenosis dimensions, allowing for real-time computation and assessment of hemodynamic significance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If non-invasive imaging technologies (CTA) are used to assess coronary artery stenosis, then medical cost and medical complications are reduced, but functional significance information is lost leading to high false positive rates
Solution Approach 1:
The patent introduces computational fluid dynamics (CFD) simulation as an intermediary between non-invasive CTA imaging and functional assessment. The CFD model acts as a mediator that transforms anatomical data from CTA into hemodynamic parameters (pressure drops, flow rates) without requiring invasive catheterization, thus preserving the benefits of non-invasive imaging while recovering the lost functional information
Solution Approach 2:
The patent creates a virtual copy of the coronary artery system through 3D reconstruction from CTA images. This digital twin allows for computational simulation of blood flow and pressure characteristics, enabling functional assessment without physical invasion. The virtual model replicates the anatomical structure and hemodynamic behavior, providing FFR-equivalent information non-invasively
2Productivity
If anatomical index (diameter stenosis) is used to assess coronary stenosis, then assessment is simple and quick, but false positive rate increases and stenosis severity is overestimated
Solution Approach 1:
The patent transitions from using a single anatomical parameter (diameter stenosis) to multiple hemodynamic parameters (pressure drops, flow rates, fractional flow reserve). By changing the assessment parameters from purely anatomical to hemodynamic, the system maintains computational efficiency while dramatically improving measurement precision and reducing false positives through physiologically relevant metrics
3Measurement precision
If invasive coronary catheterization is used to measure FFR, then functional severity assessment is accurate, but medical cost increases and medical complications occur
Solution Approach 1:
The patent creates a virtual replica of the coronary circulation system through 3D reconstruction from non-invasive CTA images. This digital twin allows CFD simulation to replicate the hemodynamic conditions that would otherwise require invasive measurement. The virtual model produces FFR values comparable to invasive gold standard while eliminating the need for catheterization and its associated risks
Solution Approach 2:
The patent replaces the mechanical invasive measurement system (catheters, pressure wires) with a computational simulation system. Instead of physically inserting devices into the coronary arteries to measure pressure, the system uses CFD algorithms to calculate pressure drops and flow rates from anatomical images, substituting mechanical intrusion with mathematical modeling
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate, non-invasive assessment of coronary artery stenosis functional significance, reducing false positives and providing hemodynamic insights comparable to invasive measurements, thus aiding in patient management.
Implementation Method 1
simulating blood flow in the three dimensional model of the coronary artery tree of the patient to determine modeled flow rates
Implementation Method 2
using an analytical model depending on the stenosis dimensions to predict a modeled pressure drop over the stenosis from the modeled flow rates
Data Source
AI summary
A medical image processing method of determining a fractional flow reserve through a stenosis of a coronary artery from medical image data is disclosed. The medical image data comprises a set of images of a coronary region of a patient. The coronary region includes the stenosis. The method comprises: reconstructing a three dimensional model of a coronary artery tree of the patient from the medical image data; determining stenosis dimensions from the three dimensional model of the coronary artery tree of the patient; simulating blood flow in the three dimensional model of the coronary artery tree of the patient to determine modeled flow rates; using an analytical model depending on the stenosis dimensions to predict a modeled pressure drop over the stenosis from the modeled flow rates; and determining the fractional flow reserve through the stenosis from the modeled pressure drop.