OCT Angiography Quantitative Analysis for Vascular Abnormality Detection
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Solution Overview
Problem
Current methods for evaluating vascular image data from optical coherence tomography angiography (OCTA) are limited, as individual indices like vessel area density (VAD) and vessel skeleton density (VSD) provide incomplete information about vascular abnormalities, and OCTA struggles to convey information about vascular leakage, which is crucial for diagnosing and monitoring ocular diseases.
Innovation Solution
A comprehensive quantitative analysis system that combines vessel area density (VAD), vessel skeleton density (VSD), vessel diameter index (VDI), vessel perimeter index (VPI), and vessel complexity index (VCI) to provide a multi-perspective interpretation of OCTA images, enabling objective assessment of disease progression and treatment monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple quantitative indices (VAD, VSD, VDI, VPI, VCI) are combined for comprehensive analysis, then the completeness of vascular information is improved, but the complexity of the evaluation system increases
Solution Approach 1:
The patent segments the vascular assessment into five distinct quantitative indices: Vessel Area Density (VAD), Vessel Skeleton Density (VSD), Vessel Diameter Index (VDI), Vessel Perimeter Index (VPI), and Vessel Complexity Index (VCI). Each index independently evaluates a specific aspect of vascular structure, allowing comprehensive information extraction while maintaining clear, modular analysis categories that simplify the overall evaluation process.
Solution Approach 2:
The patent creates a multi-functional evaluation system where a single OCTA image can be analyzed through multiple quantitative indices simultaneously. This universal approach allows the same imaging modality to provide diverse vascular information (area, skeleton, diameter, perimeter, complexity) without requiring additional imaging equipment or procedures, thereby improving information completeness while avoiding proportional increases in system complexity.
2Measurement precision
If conventional single-index methods are used, then the simplicity of analysis is maintained, but the ability to detect pathological changes is insufficient
Solution Approach 1:
The patent applies local quality assessment by evaluating different specific aspects of vascular structure through dedicated indices: VAD for area-based assessment, VSD for skeleton-based assessment, VDI for diameter measurement, VPI for perimeter analysis, and VCI for complexity evaluation. This localized specialization of each index to specific vascular features enables precise detection of localized pathological changes that would be missed by general single-index methods.
Solution Approach 2:
The patent utilizes multiple varying parameters (area, skeleton density, diameter, perimeter, complexity) to characterize vascular structure from different perspectives. By monitoring changes across these diverse parameters rather than relying on a single parameter, the system achieves superior sensitivity to pathological changes while transforming the complexity challenge into a structured multi-parameter analysis framework.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for a more comprehensive and objective evaluation of vascular features, improving the ability to detect pathological changes and monitor treatment responses in ocular diseases, particularly in conditions like age-related macular degeneration and diabetic retinopathy, by providing detailed vascular information that was previously difficult to obtain.
Implementation Method 1
an OCT imaging module configured to transmit light toward a region of interest (ROI) in the tissue and detect backscattered light received from the ROI
Implementation Method 2
transmit light toward a region of interest (ROI) in the tissue and detect backscattered light received from the ROI
Implementation Method 3
a processing subsystem configured to generate a binary vasculature map from the electrical signals, wherein the binary vasculature map distinguishes between vessel areas and non-vessel areas
Data Source
AI summary
A five-index quantitative analysis of OCT angiograms is disclosed. One method of analyzing an anatomical region of interest of a subject includes acquiring vascular image data from the region of interest and generating a binary vasculature map from the vascular image data. A vessel skeleton map and vessel perimeter map are generated from the binary vasculature map. Based on the three generated maps, a vessel area density, vessel skeleton density, vessel perimeter index, vessel diameter index, and vessel complexity can be determined, in addition to detection of any flow impairment zones in the region of interest. These metrics can be used to detect and assess vascular abnormalities from multiple perspectives.