Personalized Coronary Flow Model Using Contrast Agent Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current non-invasive methods for estimating coronary flow and fractional flow reserve are limited by assumptions such as coronary flow being proportional to myocardial mass, which are not valid for patients with rest angina, restricting their applicability to those with coronary artery disease.
Innovation Solution
A non-invasive methodology that generates patient-specific coronary flow models using contrast-enhanced images and computational fluid dynamics, without relying on myocardial mass, by analyzing spatial contrast agent concentration distribution in coronary vasculature to tune parameters of a generalized coronary model, allowing for non-invasive estimation of coronary flow and fractional flow reserve.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional invasive approaches are used to measure fractional flow reserve, then measurement precision is improved, but patient harm increases due to invasive procedures
Solution Approach 1:
The patent replaces the mechanical/invasive wire-based pressure measurement system with a non-invasive imaging-based computational model. Contrast-enhanced CT images are used to generate 3D coronary models, and computational fluid dynamics simulate blood flow to estimate fractional flow reserve without physical wire insertion into the patient's vasculature.
Solution Approach 2:
The patent introduces computational modeling and contrast agent concentration analysis as intermediary steps between non-invasive imaging and fractional flow reserve estimation. The contrast agent distribution serves as a mediator that provides flow information without requiring direct pressure measurement, bridging the gap between non-invasive imaging and functional assessment.
2Object-affected harmful factors
If non-invasive methods using myocardial mass assumptions are used, then patient harm is reduced, but measurement precision deteriorates for patients with rest angina
Solution Approach 1:
The patent changes the underlying parameters used for coronary flow estimation from myocardial mass-based assumptions to contrast agent concentration-based measurements. Instead of assuming flow is proportional to myocardial mass, the method directly measures contrast concentration in the coronary vessels and uses computational models to derive flow parameters, making the estimation valid for patients with rest angina who violate the proportional assumption.
Solution Approach 2:
The patent applies local quality by measuring contrast agent concentration specifically within the coronary vasculature rather than using global myocardial mass. The 3D coronary models allow for localized flow estimation in specific vessel segments, providing patient-specific information that accounts for local pathological conditions rather than applying uniform assumptions across the entire myocardium.
3Measurement precision
If patient-specific measurements are used to personalize blood flow models, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing the contrast-enhanced CT images to extract coronary vessel geometry and generating 3D models before flow simulation. The computational framework is prepared in advance with predefined boundary conditions and material properties, allowing patient-specific parameters to be integrated systematically without ad-hoc complexity during the measurement process.
Solution Approach 2:
The patent creates a universal computational framework that can handle multiple patient-specific parameters (anatomy, flow conditions, boundary conditions) through a single integrated model. The generalized coronary model serves as a multi-functional platform that accommodates various input data types and produces comprehensive flow estimates, reducing the need for separate specialized procedures for each parameter.
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
This approach enables more accurate and applicable non-invasive estimation of coronary flow and fractional flow reserve, reducing patient risk and healthcare costs by personalizing blood flow models based on patient-specific measurements, thus overcoming previous limitations.
Implementation Method 1
computed tomography (CT), including coronary computed tomography angiography (CCTA) devices and techniques, is an imaging technology based on the observed transmission of X-rays through the patient
Implementation Method 2
an X-ray source and X-ray detector configured to generate X-ray attenuation data for an imaging volume
Implementation Method 3
analyze the contrast-enhanced images to determine spatial contrast agent concentration distribution in each vessel segment of interest
Data Source
AI summary
The present approach provides a non-invasive methodology for estimation of coronary flow and/or fractional flow reserve. In certain implementations, various approaches for personalizing blood flow models of the coronary vasculature are described. The described personalization approaches involve patient-specific measurements and do not assume or rely on the resting coronary flow being proportional to myocardial mass. Consequently, there are fewer limitations in using these approaches to obtain coronary flow and/or fractional flow reserve estimates non-invasively.