Perfusion Imaging Data Processor for Circulatory Sub-system Differentiation
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Solution Overview
Problem
Current perfusion imaging techniques face challenges in differentiating between various circulatory sub-systems within the same region, leading to inconsistent results and inaccuracies due to signal noise and interference, which complicates the analysis of blood flow characteristics in cancer diagnostics.
Innovation Solution
A perfusion imaging data processor is developed to determine agent peak characteristic-times and arguments for multiple circulatory sub-systems, generating perfusion maps that visually represent the relationships or differences between these sub-systems, thereby improving the accuracy of perfusion imaging data analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional perfusion imaging techniques are used to collect time-series data from multiple time points, then blood flow characteristics can be measured, but the results are inconsistent and inaccurate due to signal noise and interference from multiple circulatory sub-systems
Solution Approach 1:
The patent segments the mixed signal from multiple circulatory sub-systems into distinct components by identifying separate agent peak characteristic-times for each sub-system. This segmentation allows individual analysis of arterial, capillary, and venous phases, improving measurement precision by isolating specific physiological processes from the composite signal.
Solution Approach 2:
The patent introduces an intermediary computational framework that processes the time-series perfusion data to separate and characterize different circulatory sub-systems. This intermediary processing layer transforms the complex mixed signal into distinct, interpretable parameters for each sub-system, resolving the contradiction between accuracy and complexity.
2Reliability
If repeated scans are performed to cover the transit of contrast agent through tissue, then perfusion parameters can be calculated, but the imaging time is extended and motion artifacts increase
Solution Approach 1:
The patent applies preliminary deconvolution processing to the time-series data to extract agent peak characteristic-times and arguments before full perfusion parameter calculation. This preliminary action separates the contribution of different circulatory sub-systems early in the processing pipeline, improving the reliability of subsequent parameter calculations while enabling more efficient scanning protocols.
Solution Approach 2:
The patent changes the approach from measuring overall perfusion parameters to measuring specific temporal parameters (agent peak characteristic-times and arguments) that directly characterize different circulatory phases. This parameter transformation allows reliable differentiation of arterial, capillary, and venous contributions with reduced imaging time.
3Loss of information
If contrast enhanced imaging is used to suggest tumor malignancy, then anatomical features are visualized, but the degree of contrast enhancement is not a reliable indicator of tumor grade
Solution Approach 1:
The patent segments the perfusion signal into distinct circulatory sub-systems (arterial, capillary, venous) and calculates separate agent peak characteristics for each. This segmentation provides specific functional information about tumor vascularity and perfusion dynamics that goes beyond simple contrast enhancement, improving the reliability of tumor grade characterization.
Solution Approach 2:
The patent adds a temporal dimension to the analysis by measuring agent peak characteristic-times and arguments across multiple time points. This transforms the static contrast enhancement measurement into dynamic temporal profiles that reveal functional characteristics of tumor vasculature, providing more reliable information about tissue function and malignancy.
Data Source
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AI summary
A perfusion imaging data processor (122) includes an agent peak characteristic-time determiner (206) configured to determine two or more agent peak characteristic-times respectively for two or more circulatory sub-systems represented in a same sub-set of voxels of a set of time-series data of perfusion imaging data, an agent peak argument determiner (210)configured to determine an agent peak argument for each of the two or more agent peak characteristic-times,an agent peak argument relation determiner (212) configured to determine a relationship between the agent peak arguments of the two or more agent peak characteristic-times, and a perfusion map generator (214) configured to generate, based on the determined relationship and the perfusion imaging data, at least one perfusion map, wherein the at least one perfusion map includes volumetric image data visually presenting at least one of a relationship or a difference between the two or more circulatory sub-systems.