Microvascular Architecture Determination from Dynamic Contrast-Enhanced MRI
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Solution Overview
Problem
Current methods for determining micro-vascular architecture from dynamic contrast-enhanced image data are limited in accuracy and require estimation of the arterial input function, which adds complexity and operator dependency.
Innovation Solution
A method that computes leakage and dispersion parameters from dynamic contrast-enhanced magnetic resonance data without requiring arterial input function estimation, using a modified local density random walk model and a simplified dispersion model to characterize micro-vascular architecture, enabling simultaneous computation of these parameters and reducing computational burden.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the arterial input function estimation is used in current methods, then the micro-vascular architecture can be determined, but the complexity and operator dependency increase
Solution Approach 1:
The patent extracts and eliminates the arterial input function estimation step from the analysis pipeline. By formulating a method that directly computes leakage and dispersion parameters from dynamic contrast-enhanced MRI data without requiring separate arterial input function measurement or estimation, the complexity and operator dependency are removed while maintaining the ability to determine micro-vascular architecture
Solution Approach 2:
The method enables the system to self-determine the necessary parameters for micro-vascular architecture analysis using only the dynamic contrast-enhanced MRI data itself. The arterial input function information is effectively derived self-consistently from the tissue time-concentration curves through the proposed modeling approach, eliminating the need for external arterial sampling or estimation procedures
2Measurement precision
If the arterial input function estimation is performed, then kinetic parameters can be computed, but the operator dependency increases
Solution Approach 1:
The analysis method performs self-calibration by deriving all necessary kinetic information directly from the dynamic contrast-enhanced MRI time-concentration curves. The system automatically determines leakage and dispersion parameters through mathematical modeling without requiring operator intervention for arterial input function selection or estimation, thereby eliminating operator dependency while maintaining computational accuracy
3Measurement precision
If traditional dispersion models are used, then the analysis can be performed, but the computational burden is high
Solution Approach 1:
The patent transforms the traditional dispersion modeling approach by changing the parameter representation from requiring full arterial input function characterization to using simplified time-concentration curve parameters. This parameter transformation enables analytical or semi-analytical solutions that significantly reduce computational burden while preserving the accuracy of dispersion parameter computation through the proposed mathematical framework
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 provides a quantitative analysis of microvascular structure, improving the accuracy of vascularity assessment and distinguishing between cancerous and healthy tissue, with enhanced classification performance and reduced operator dependency.
Implementation Method 1
taking into account effects of both convective dispersion and extravasation kinetics of contrast agent
Implementation Method 2
leakage of the contrast agent out of the blood vessels into the extravascular tissue provides a major contribution to the transport dynamics
Data Source
AI summary
A method of determining microvascular architecture is disclosed. Dynamic contrast-enhanced magnetic resonance data acquired from a contrast agent administered to at least a part of a subject to be examined. From the dynamic contrast-enhanced magnetic resonance data a leakage parameter (kep) and a dispersion parameter (k) are computed. Effects of both convective dispersion and extravasation kinetics of contrast agent are taken into account.