Lesion Graph Interface for Crosstalk-Aware Vascular Index Measurement
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Solution Overview
Problem
Existing software-based techniques for assessing vascular health during percutaneous coronary intervention (PCI) fail to accurately account for crosstalk effects between lesions, leading to inaccurate determination of vascular function indices.
Innovation Solution
A system and method that generates an adjustable lesion graph allowing medical professionals to null specific lesions in a cardiac model, considering crosstalk effects to accurately determine vascular function indices by simulating the effects of lesion removal on blood flow using user interface elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing software-based techniques are used to assess vascular health, then the assessment process is simple and quick, but the accuracy of vascular function index determination is poor due to failure to account for crosstalk effects between lesions
Solution Approach 1:
The system segments the vascular assessment by individually modeling each lesion's impact on vascular function indices while separately accounting for crosstalk effects between lesions. This allows precise determination of each lesion's contribution to overall vascular dysfunction, resolving the technical contradiction by enabling accurate measurement through systematic decomposition of the assessment process into discrete lesion-level analyses.
2Measurement precision
If a detailed cardiac model with multiple lesions is analyzed, then the assessment becomes more accurate, but the user interface becomes complex and difficult to operate
Solution Approach 1:
The system creates a virtual copy of the cardiac model with all lesions and their interactions, allowing clinicians to perform what-if analyses without manipulating the actual patient data. The virtual model replicates the complex physiological relationships, enabling accurate assessment while keeping the user interface simple, as clinicians only need to interact with high-level controls rather than complex model parameters.
Solution Approach 2:
The system introduces an intermediary computational layer that automatically handles the complex calculations of crosstalk effects between lesions. This intermediary process translates simple user selections into comprehensive vascular function assessments, resolving the contradiction by shielding users from computational complexity while maintaining high measurement precision through sophisticated underlying algorithms.
3Measurement precision
If crosstalk effects between lesions are accounted for, then the vascular function index is more accurate, but the computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary computational work by pre-calculating the crosstalk effect matrices and lesion interaction parameters during system initialization or model creation. This preliminary action stores the complex interaction data in optimized data structures, allowing rapid querying and assessment during actual clinical use. The technique resolves the time-accuracy contradiction by shifting computational burden to an offline preparation phase, enabling fast real-time assessments with high precision.
Data Source
AI summary
Systems and methods for enhanced user interface and crosstalk analysis for cardiac index determination. An example method includes accessing a cardiac model of a portion of a patient's heart, the portion including one or more vessels of the patient's heart, and the cardiac model indicating a plurality of lesions along a length of at least one of the vessels; obtaining, based on the cardiac model for the lesions, respective positions along the length for which the lesions are associated with index drops, wherein the index drops are with respect to an index indicative of vascular function; and causing presentation of a user interface, wherein the user interface: presents a graph mapping the length to the index indicative of vascular function, presents individual toggles enabling nulling of individual lesions, and updates the graph in response to received user input to one or more of the toggles, wherein the user input nulls effects of one or more lesions.