Computational Model for Noninvasive Coronary 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 direct information on the functional significance of coronary lesions and blood flow, leading to unnecessary invasive procedures and healthcare costs.
Innovation Solution
A computer-implemented method and system that creates a patient-specific three-dimensional model of coronary blood flow, allowing noninvasive assessment of fractional flow reserve (FFR) and other metrics like coronary flow reserve (CFR) and instantaneous wave-free ratio (IFR), using imaging data and computational analysis to determine the functional significance of coronary lesions without invasive pressure measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If diagnostic cardiac catheterization with pressure wire measurement is performed to obtain accurate FFR data, then measurement precision is improved, but device complexity and invasiveness increase
Solution Approach 1:
The patent creates a virtual copy of the patient's coronary artery system using 3D modeling from CCTA images. This computational model replicates the anatomical structure and hemodynamic properties, allowing FFR calculation without physical wire insertion. The model serves as a digital twin that preserves measurement accuracy while eliminating invasive procedures
Solution Approach 2:
The patent replaces the mechanical pressure wire measurement system with a computational fluid dynamics approach. Instead of physically inserting a wire to measure pressure gradients, the system uses numerical simulations based on patient-specific 3D models and blood flow equations to calculate FFR, substituting mechanical measurement with computational analysis
2Measurement precision
If invasive pressure wire measurement is performed to assess coronary lesion function, then measurement precision is improved, but loss of time increases due to procedural duration
Solution Approach 1:
The patent performs preliminary 3D modeling and anatomical reconstruction from CCTA images before the diagnostic decision is needed. By pre-processing the anatomical data and creating the computational model in advance, the system reduces the time required during the actual FFR assessment, as the modeling framework is already established and ready for simulation
3Ease of operation
If CCTA is used to obtain coronary anatomy, then ease of operation is improved as noninvasive imaging, but measurement precision deteriorates due to inability to provide direct functional information
Solution Approach 1:
The patent merges anatomical imaging (CCTA) with functional assessment (FFR calculation) into a single integrated system. The 3D model derived from CCTA images is combined with computational hemodynamics to simultaneously provide both structural and functional information, eliminating the need for separate invasive procedures while maintaining diagnostic accuracy
Solution Approach 2:
The patent creates a multi-functional system where the same 3D computational model serves multiple purposes: visualizing coronary anatomy, calculating FFR values, assessing lesion function, and potentially evaluating treatment options. This universal model replaces multiple separate diagnostic tools, providing both anatomical and functional data through a single noninvasive approach
Data Source
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AI summary
Embodiments include a system for determining cardiovascular information for a patient which may include at least one computer system configured to receive patient-specific data regarding a geometry of an anatomical structure of a patient; create a model representing at least a portion of the anatomical structure; create a physics-based model relating to a blood flow characteristic within the anatomical structure; determine a first blood flow rate at at least one point of interest in the model; modify the model; determine a second blood flow rate at a point in the modified model corresponding to the at least one point of interest in the model; and determine a fractional flow reserve value as a ratio of the second blood flow rate to the first blood flow rate.