Automated Plaque Quantification in CCTA Scans
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Solution Overview
Problem
Current methods for analyzing coronary artery plaques in CCTA scans are limited by the need for manual tracing and are prone to variability, lacking standardized and automated quantification of non-calcified and calcified components, which is crucial for accurate cardiovascular risk assessment.
Innovation Solution
A computer-implemented method that uses CCTA scan data to determine attenuation thresholds and classify components, automatically identifying non-calcified and calcified plaque volumes by generating centerlines, detecting epicardial fat, and segmenting the coronary artery, thereby providing standardized and reproducible quantification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tracing methods are used to analyze plaque components, then flexibility in analysis is maintained, but processing time increases and measurement precision deteriorates due to variability
Solution Approach 1:
The patent replaces manual mechanical tracing operations with an automated computer-based system that uses algorithmic processing of CT scan data. The system automatically identifies and quantifies non-calcified and calcified plaque components through computational analysis, eliminating manual intervention while maintaining measurement precision and reducing processing time.
Solution Approach 2:
The system performs self-service by automatically generating its own analysis results without requiring manual operator input for each measurement. The automated algorithm processes the CT scan data independently, producing standardized quantification of plaque components that is consistent and reproducible across different analyses.
2Reliability
If manual tracing is used for plaque analysis, then adaptability to different cases is maintained, but reliability deteriorates due to operator variability
Solution Approach 1:
The patent employs parameter changes by adjusting attenuation thresholds dynamically based on the specific characteristics of each CT scan and patient case. The system modifies measurement parameters adaptively to accommodate different plaque types, contrast conditions, and imaging protocols, ensuring reliable and consistent quantification across diverse clinical scenarios while maintaining measurement accuracy.
3Productivity
If automated threshold determination is implemented, then productivity increases, but measurement precision may worsen if thresholds are not accurately calibrated
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor and adjust attenuation threshold values based on the actual CT scan data characteristics. The automated algorithm analyzes the scan images and modifies threshold parameters in real-time to maintain optimal separation between different tissue densities, ensuring both high productivity through automation and precise measurement through adaptive calibration.
Data Source
AI summary
A method of quantifying plaques imaged by cardiac computed tomography angiography (“CCTA”) scan data. Calcified and non-calcified component thresholds are determined based at least in part on attenuation values of a pool of blood in the CCTA scan data. An epicardial fat threshold is determined and used to classify epicardial fat in the CCTA scan data. A portion of CCTA scan data positioned between a detected outer boundary of the coronary artery and a portion classified as lumen is classified as arterial wall. NCP and CP seeds are identified in the arterial wall portion. Portions of the CCTA scan data continuous with a NCP seed and having attenuation values greater than an artery wall value and less than the NCP threshold are classified as NCP, and portions of the CCTA scan data continuous with the CP seed and having attenuation values greater than the CP threshold are classified as CP.