Non-Invasive Plaque Imaging for AI-Based Risk Determination
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Solution Overview
Problem
Current methods for diagnosing and treating cardiovascular diseases, such as coronary artery disease, often rely on invasive procedures like angiography and stent implantation, which may not be effective for all patients, and non-invasive methods like blood chemistry analysis fail to accurately identify high-risk plaque areas, leading to potential misdiagnosis and ineffective treatment.
Innovation Solution
Non-invasive image-based systems and methods using machine learning and artificial intelligence to analyze coronary plaque from medical images, such as CT scans, to quantify plaque characteristics, assess cardiovascular risk, and generate personalized treatment plans, including the use of normalized image analysis and allometric scaling laws to derive fractional flow reserve and ischemia.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If invasive procedures like angiography are used for diagnosis, then diagnostic accuracy is improved, but patient risk and procedure complexity increase
Solution Approach 1:
The patent replaces invasive mechanical procedures (angiography with catheters) with non-invasive imaging systems (CT, MRI, ultrasound) combined with AI analysis. The system uses external imaging devices to capture vascular data without penetrating the body, then applies machine learning algorithms to analyze the images and assess plaque characteristics, thereby eliminating procedural risks while maintaining diagnostic capability
Solution Approach 2:
The patent introduces an AI-based image analysis system as an intermediary between non-invasive imaging and clinical diagnosis. The AI system processes medical images to extract plaque characteristics, calculate vulnerability scores, and generate diagnostic recommendations, serving as a bridge that translates non-invasive imaging data into clinically actionable information with accuracy approaching invasive methods
2Reliability
If invasive procedures are used for treatment, then treatment effectiveness is improved, but procedure complexity and patient risk increase
Solution Approach 1:
The patent performs preliminary risk assessment using non-invasive imaging and AI analysis before treatment decisions are made. The system identifies high-risk plaque characteristics and vulnerability scores in advance, allowing clinicians to stratify patients and select appropriate treatment intensities, thereby avoiding unnecessary invasive procedures for low-risk patients while ensuring timely intervention for high-risk cases
Solution Approach 2:
The patent transforms treatment decision-making from binary (invasive vs. non-invasive) to a continuous spectrum based on quantified plaque vulnerability parameters. The AI system calculates multiple parameters including plaque composition, cap thickness, necrotic core volume, and inflammation markers, allowing treatment intensity to be matched precisely to disease severity, thereby reducing overall procedural complexity while maintaining effectiveness
3Ease of operation
If non-invasive methods like blood chemistry analysis are used, then patient comfort is improved, but diagnostic accuracy deteriorates
Solution Approach 1:
The patent transitions from one-dimensional blood chemistry markers to multi-dimensional vascular imaging data. The system captures spatial information (plaque location, volume, morphology), compositional information (calcified, fibrous, lipid components), and functional information (vessel wall stress, flow dynamics), creating a comprehensive multidimensional assessment that far exceeds the informational content of blood tests while remaining non-invasive
Solution Approach 2:
The patent creates a multi-functional non-invasive platform that simultaneously performs multiple diagnostic functions: plaque detection, characterization, vulnerability assessment, and treatment monitoring. The same imaging and AI system that identifies plaque presence also quantifies its composition, calculates rupture risk, and tracks changes over time, replacing multiple separate tests including blood chemistry while providing superior diagnostic accuracy
4Device complexity
If traditional imaging analysis is used, then simplicity is maintained, but measurement precision and risk assessment capability deteriorate
Solution Approach 1:
The patent segments the complex task of plaque assessment into multiple analytical components: image acquisition, pre-processing, plaque detection, characterization (composition, morphology), vulnerability scoring, and reporting. The AI system processes each component separately through specialized algorithms, then integrates results into a comprehensive assessment. This modular approach manages computational complexity while achieving high measurement precision through dedicated analysis for each parameter
Data Source
AI summary
Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.