Reflectance-Based Projection-Resolved OCTA Algorithm
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Solution Overview
Problem
Optical coherence tomography angiography (OCTA) faces challenges in distinguishing between real blood flow and projection artifacts, particularly due to the depth resolution limitations caused by shadowgraphic flow projection artifacts, which complicate the interpretation of 3D vascular networks and hinder the detection of deeper vascular abnormalities.
Innovation Solution
The reflectance-based projection-resolved (rbPR) OCTA algorithm utilizes OCT reflectance information to differentiate between real vessels and flow projection artifacts, employing non-linear models for vascular contrast enhancement and probability distribution mapping, and analyzing 2D images slice by slice to separate in situ flow and projection artifacts, thereby improving projection resolution and preserving vascular continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional OCTA is used to detect blood flow, then flow detection capability is provided, but depth resolution deteriorates due to shadowgraphic flow projection artifacts
Solution Approach 1:
The algorithm segments the 3D OCTA volume into multiple 2D en face slices at different depths. By processing and analyzing each slice separately, the system can identify and remove projection artifacts that appear as discontinuous signals across slices, while preserving genuine vascular structures that maintain continuity. This segmentation approach directly addresses the depth resolution limitation by enabling artifact differentiation at each depth level.
Solution Approach 2:
The invention transitions from analyzing single 2D cross-sections to evaluating 3D volumetric data by examining multiple 2D en face slices stacked in the depth dimension. This dimensional approach allows the system to distinguish projection artifacts (which appear in multiple slices due to shadowing) from true vessels (which maintain consistent anatomical positioning across slices), thereby improving depth resolution and eliminating the harmful projection effects.
2Loss of information
If 3D OCTA imaging is performed to visualize vascular networks, then comprehensive vascular information is obtained, but interpretation difficulty increases due to projection artifacts
Solution Approach 1:
The algorithm extracts and removes projection artifacts from the 3D OCTA volume by identifying characteristic artifact patterns across multiple en face slices. Genuine vascular information is preserved while the harmful projection components are selectively extracted and eliminated. This process maintains complete vascular information while removing the elements that cause interpretation difficulty.
Solution Approach 2:
The system introduces an intermediate processing step that analyzes the spatial and depth relationships across multiple 2D en face slices. This intermediary analysis acts as a mediator between the raw 3D OCTA data and the final interpreted images, using algorithms to distinguish true vessels from projection artifacts based on their different spatial characteristics across the depth dimension.
3Measurement precision
If deeper vascular layers are imaged, then detection of deep vascular abnormalities is enabled, but image quality deteriorates due to shadowgraphic artifacts
Solution Approach 1:
The algorithm segments the volumetric data into multiple depth-resolved en face slices, allowing separate analysis of superficial and deep vascular layers. By examining each slice independently and comparing artifact patterns across slices, the system can identify projection artifacts that contaminate deep layer images and remove them, thereby improving the accuracy of deep vascular abnormality detection without sacrificing image quality.
Data Source
AI summary
Embodiments provide systems and methods associated with a reflectance-based projection-resolved (rbPR) optical coherence tomography angiography (OCTA) algorithm which uses optical coherence tomography (OCT) reflectance to enhance the flow signal and suppress the projection artifacts in 3-dimensional OCTA. rbPR improves the vascular connectivity and improved the discrimination of the deeper plexus angiograms in healthy eyes, compared to prior PR-OCTA method. Additionally, rbPR removes flow projection artifacts more completely from the outer retinal slab in the eyes with age-related macular degeneration, and preserves vascular integrity of the intermediate and deep capillary plexuses in the eyes with diabetic retinopathy. Additionally, the rbPR method improves the resolution of the choriocapillaris and demonstrates details comparable to scanning electron microscopy.