Vascular Characteristic Determination with Correspondence Modeling
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Solution Overview
Problem
Current methods for assessing vascular flow and stenosis severity, such as fractional flow reserve (FFR) measurements, are invasive and rely on geometrical or hemodynamic parameters, which may not accurately predict ischemia or guide percutaneous coronary intervention.
Innovation Solution
A method for calculating fractional flow reserve using 2-D images, specifically X-ray angiography images, by determining vascular characteristics such as width and resistance, and grouping image regions to identify common vascular segments, allowing for non-invasive assessment of vascular flow and stenosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive FFR measurements are used to assess vascular flow and stenosis severity, then measurement precision is improved, but ease of operation deteriorates due to the invasive nature of the procedure
Solution Approach 1:
The patent creates a virtual model that copies the essential geometric and hemodynamic characteristics of the coronary vasculature from medical imaging data. This virtual copy allows FFR calculation without physical catheter insertion, maintaining measurement precision while eliminating the invasive procedure. The model reconstructs vascular geometry and simulates blood flow to generate FFR values that correlate with invasive measurements.
Solution Approach 2:
The patent replaces the mechanical invasive measurement system (pressure wires and catheters) with a computational hemodynamic simulation system. Instead of physically measuring pressure gradients through catheter-based wires, the system uses numerical simulation of blood flow based on vascular geometry to calculate FFR, substituting mechanical intervention with computational analysis.
2Ease of operation
If simple geometrical parameters are used to assess stenosis, then ease of operation is improved, but measurement precision deteriorates as geometrical parameters may not accurately predict ischemia
Solution Approach 1:
The patent transforms the assessment from simple geometric parameters (stenosis diameter, percent narrowing) to hemodynamic parameters (pressure gradients, flow rates, FFR values) through computational simulation. This parameter transformation maintains ease of operation since it uses the same imaging data, but improves precision by evaluating actual blood flow consequences rather than just anatomical appearance.
Solution Approach 2:
The patent introduces computational hemodynamic simulation as an intermediary between geometric imaging data and clinical decision-making. Instead of directly using simple geometric measurements, the system processes imaging data through flow simulation to generate hemodynamic parameters that better predict ischemia, acting as a mediator that translates anatomy into functional assessment.
3Ease of operation
If 2-D images are used for vascular assessment, then ease of operation is improved, but measurement precision deteriorates due to projection effects and lack of 3-D information
Solution Approach 1:
The patent performs dimensional transformation by reconstructing 3-D vascular geometry from 2-D angiographic projections. Using knowledge of projection geometry and vessel orientation, the system infers three-dimensional positions and dimensions of coronary segments, enabling accurate measurement of vascular characteristics despite starting from 2-D images.
Solution Approach 2:
The patent introduces a 3-D geometric model as an intermediary between 2-D images and vascular measurements. Rather than attempting to measure directly from projected 2-D images where foreshortening and overlap distort dimensions, the system creates an intermediate 3-D representation that accounts for projection effects, then extracts accurate measurements from this corrected model.
Data Source
AI summary
Automated image analysis used in vascular state modeling. Coronary vasculature in particular is modeled in some embodiments. Methods of “virtual revascularization” of a presently stenotic vasculature are described; useful, for example, as a reference in disease state determinations. Structure and uses of a model which relates records comprising acquired images or other structured data to a vascular tree representation are described.