Study participants with a clinical diagnosis of choroideremia were recruited at the Casey Eye Institute. We then evaluated the trained classifier using a different group of scans.Ģ.1 Optical coherence tomography angiography We developed a random forest classifier which was trained to evaluate en face structural OCT and OCTA information along with spatial information derived from standard deviation and Gabor directional filters. Here, we explored using supervised machine learning to leverage manual grading in development of a more automated approach to assessing intact choriocapillaris. Furthermore, because of projection, larger choroidal vessels beneath the choriocapillaris are not observed when there is intact choriocapillaris.īecause of these artifacts, manual grading of OCTA has sometimes been necessary. However, if shadowing reduces the OCT reflectance signal below the minimum threshold set by the OCTA algorithm to reduce noise, no flow signal will be detected. This means that vessels in superficial layers project deeper and thus may also be seen in deeper layers. Because red blood cells are highly scattering, flowing blood in vessels reduces light penetration deeper into the tissue and casts time-varying shadows which are also picked up by the OCTA algorithm as flow signal. Shadowing and projection artifacts are related, and the interplay between the two complicates the interpretation of choroidal angiograms derived from OCTA. When assessing the choriocapillaris using OCTA, we found that shadowing and projection artifacts made it challenging to identify and quantify intact choriocapillaris. OCTA identifies vasculature by detecting the blood flow-induced change in the OCT reflectance signal over time. It uses backscattered light to create depth-resolved reflectance profiles of the structure of interest. OCT is an interferometric imaging technique that is analogous to ultrasound. Optical coherence tomography (OCT) and its functional extension OCT angiography (OCTA) were two of the main tools. To better understand the pathophysiology of retinal degeneration, we previously used a multimodal imaging approach to assess the integrity of photoreceptors, RPE, and choriocapillaris in cases of choroideremia, a rare hereditary chorioretinal disease characterized by poor night vision and progressive loss of peripheral vision. Loss of these structures in degenerative diseases leads to vision loss. The retinal pigment epithelium (RPE) and choroidal vascular network in the eye are responsible for supporting the metabolic demands of the photoreceptors, which convert light to neural signals.
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