Computational Fluid Dynamics Model for Non-Invasive FFR Estimation
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Solution Overview
Problem
Current methods for calculating the functional index parameter, such as fractional flow reserve (FFR), using non-invasive imaging techniques are less accurate due to reliance on non-patient specific data and mathematical relationships, leading to inefficiencies in identifying physiologically significant stenotic lesions and requiring invasive measurements.
Innovation Solution
A system and method that utilize patient-specific nuclear medicine imaging data to calculate functional index parameters like FFR, improving accuracy by using dynamic SPECT imaging and computational fluid dynamics models, reducing the need for invasive procedures and enhancing computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If non-invasive imaging methods are used to estimate FFR, then the procedure is less invasive and faster, but the accuracy is reduced due to reliance on population data and mathematical relationships
Solution Approach 1:
The patent creates a virtual copy of the patient's coronary vasculature using CT angiography data to build a 3D computational model. This digital twin allows non-invasive FFR calculation by simulating blood flow physics in the patient-specific anatomy, eliminating the need for invasive pressure wire measurements while maintaining accuracy through patient-specific geometric modeling
Solution Approach 2:
The patent replaces the mechanical invasive pressure wire measurement system with a computational fluid dynamics simulation system. Instead of physically inserting sensors into the blood vessel, the system uses numerical simulations based on the Navier-Stokes equations to calculate pressure drops and FFR values from CT angiography data, achieving both non-invasiveness and accuracy
2Measurement precision
If invasive FFR measurement is performed, then the accuracy is improved, but the procedure becomes more complex and time-consuming
Solution Approach 1:
The patent replaces the invasive mechanical pressure wire measurement system with a computational fluid dynamics simulation system. Instead of physically inserting sensors into the blood vessel, the system uses numerical simulations based on the Navier-Stokes equations to calculate pressure drops and FFR values from CT angiography data, achieving both non-invasiveness and accuracy
3Device complexity
If population-based data is used for FFR estimation, then the procedure is simplified, but the accuracy decreases for individual patients
Solution Approach 1:
The patent creates a virtual copy of the patient's coronary vasculature using CT angiography data to build a 3D computational model. This digital twin allows non-invasive FFR calculation by simulating blood flow physics in the patient-specific anatomy, eliminating the need for invasive pressure wire measurements while maintaining accuracy through patient-specific geometric modeling
Solution Approach 2:
The patent applies patient-specific anatomical geometry from CT angiography to create localized, individualized computational models of the coronary vasculature. This allows the simulation to capture unique patient characteristics such as vessel tortuosity, stenosis morphology, and branching patterns, providing accurate FFR values tailored to each patient's specific anatomy rather than using generic population averages
Data Source
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AI summary
There is provided a method for calculation of a functional index parameter in at least one blood vessel of a patient, comprises: receiving a dataset of registered functional image data and anatomical image data, wherein the functional image data and the anatomical image data include data indicative of anatomical and functional data for at least one blood vessel of a certain patient; calculating at least one value for at least one functional index parameter for at least one of: (i) at least one blood vessel, and (ii) for the anatomical region of the at least one blood vessel, wherein the at least one value of the at least one functional index parameter is computed based on the functional image data of the dataset; and outputting the calculated at least one value for the at least one functional index parameter for the at least one blood vessel of the certain patient.