Scaling Laws for Vascular Tree Resistance and Volume
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Solution Overview
Problem
Current methods for diagnosing diffuse coronary artery disease (DCAD) are inadequate due to the difficulty in accurately assessing diffuse narrowing of coronary arteries, as conventional angiography underestimates disease severity and invasive methods like IVUS pose risks of plaque rupture, while there is a need for a noninvasive method to determine blood volume in the vasculature.
Innovation Solution
Development of novel scaling laws that relate arterial volume, cross-sectional area, and blood flow to quantify moderate levels of DCAD, using biomimetics and microfluidics to analyze vascular tree structure, allowing for the calculation of resistance and volume within vessels, and comparing these values to model resistances to diagnose disease.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional angiography is used to assess coronary artery disease, then the procedure is noninvasive and easy to perform, but it significantly underestimates the severity of diffuse coronary artery disease
Solution Approach 1:
The patent introduces a computational model as an intermediary between conventional angiography images and disease assessment. The model uses scaling laws to calculate distal vascular tree resistance from proximal vessel measurements, providing accurate DCAD quantification without requiring direct visualization of the entire vascular tree. This intermediary computation resolves the contradiction by maintaining the simplicity of angiography while achieving accurate measurement through mathematical modeling.
2Measurement precision
If intravascular ultrasound (IVUS) is used to directly image cross-sectional area along the vessel, then measurement precision of lumen area is improved, but the risk of plaque rupture increases due to extensive interrogation of diseased segments
Solution Approach 1:
The patent extracts only the essential information needed for diagnosis from the vascular tree - specifically, the proximal vessel dimensions and branching geometry - and uses computational scaling laws to derive distal resistance characteristics. This extraction approach avoids the need for extensive IVUS interrogation of diseased segments, thereby maintaining measurement precision while eliminating the harmful effect of plaque rupture risk.
Solution Approach 2:
The patent creates a computational model that copies the essential geometric and hemodynamic characteristics of the vascular tree from proximal measurements. This virtual copy allows accurate assessment of distal resistance and disease severity without physically interrogating the distal vessels, thus avoiding plaque disruption while maintaining diagnostic accuracy.
3Object-affected harmful factors
If a noninvasive method is developed to determine blood volume in the vasculature, then patient safety is improved by avoiding invasive procedures, but device complexity increases due to the need for advanced imaging and computational analysis
Solution Approach 1:
The patent develops a computational framework that can assess multiple vascular parameters (distal resistance, blood volume, disease severity) from a single set of proximal vessel measurements obtained through conventional angiography. This multi-functional approach maintains patient safety by avoiding invasive procedures while managing device complexity through a unified computational model that handles multiple diagnostic tasks simultaneously.
Data Source
AI summary
Methods are provided for determining flow resistance within at least a portion of a vessel, whereby at least a partial biological tree image is obtained and resistance is calculated therefrom based upon at least the length of a defined vessel portion and a diameter of a stem vessel at a location proximal to a vessel crown. Methods are also provided for determining vessel volume, whereby at least a partial biological tree image is obtained and cumulative crown volume is calculated based on at least the diameter and length of the stem segment.