Coronary Plaque Vulnerability Prediction Using Multi-Physics Imaging
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Solution Overview
Problem
Current medical imaging technologies lack effective systems and methods for predicting coronary plaque vulnerability from patient-specific anatomic image data, which is crucial for assessing coronary artery disease and preventing adverse cardiac events.
Innovation Solution
A system and method that utilizes patient-specific anatomic image data to perform image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis to predict coronary plaque vulnerability, incorporating machine learning and rule-based methods to calculate adverse plaque characteristics and cardiac risk, and provide treatment recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple analysis methods (image characteristics, geometrical, computational fluid dynamics, structural mechanics) are combined to predict coronary plaque vulnerability, then prediction accuracy is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple analysis methods (image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis) into a single integrated system for predicting coronary plaque vulnerability. This merging of different analytical approaches enables comprehensive assessment of plaque characteristics while maintaining system coordination through a unified processing framework.
Solution Approach 2:
The prediction system is divided into distinct modular components: image characteristics analysis module, geometrical analysis module, computational fluid dynamics analysis module, and structural mechanics analysis module. Each module processes specific aspects of plaque vulnerability independently, then integrates results to provide comprehensive predictions, reducing overall system complexity through functional segmentation.
2Measurement precision
If comprehensive analysis including computational fluid dynamics and structural mechanics is performed, then adverse plaque characteristic calculation accuracy is improved, but computational time increases
Solution Approach 1:
The system performs preliminary image characteristics analysis and geometrical analysis before conducting computationally intensive computational fluid dynamics and structural mechanics analyses. This preliminary processing prepares and refines the input data, reducing the computational burden and time required for the more complex subsequent analyses while maintaining overall accuracy.
Data Source
AI summary
Systems and methods are disclosed for predicting coronary plaque vulnerability, using a computer system. One method includes acquiring anatomical image data of at least part of the patient's vascular system; performing, using a processor, one or more image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical image data; predicting, using the processor, a coronary plaque vulnerability present in the patient's vascular system, wherein predicting the coronary plaque vulnerability includes calculating an adverse plaque characteristic based on results of the one or more of image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of the anatomical image data; and reporting, using the processor, the calculated adverse plaque characteristic.