2023Translational BiophotonicsOpen access

Ratiometric analysis of in vivo optical coherence tomography retinal layer thicknesses for detection of changes in Alzheimer's disease

Shonit Nair Sharma, Jordan W. Marsh, Michael Tsipursky, Stephen A. Boppart

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Abstract

We analyzed ophthalmic retinal optical coherence tomography (OCT) images from patients with Alzheimer's disease (AD) to identify retinal layer thickness and ratio changes that may serve as image-based biomarkers for the disease. One three-dimensional volume before and one after diagnosis for each of 48 patients were segmented to identify retinal layer and total retinal thicknesses. Between before- and after-diagnosis retinal OCT images, there were significant thickness changes in six of ten (60%) retinal layers across all 48 patients. Through a comparison with age-matched healthy subjects, the significant changes were attributed to AD only (NFL and PR2 layers), age only (GCL, IPL, and RPE layers), or both AD and age (OPL layer). Analyzing ratios of retinal layer thicknesses, 53 of 90 (58.89%) ratios had significant changes. The four independently non-significant layers were assessed to be affected by neither AD nor age (INL layer) or both AD and age (ELM, PR1, and BM layers). The demonstrated image segmentation, measurement, and ratiometric analysis of retinal layers in AD patients may yield a noninvasive OCT image-based retinal biomarker that can be used to detect retinal changes associated with this disease.

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What this paper is about

We analyzed ophthalmic retinal optical coherence tomography (OCT) images from patients with Alzheimer's disease (AD) to identify retinal layer thickness and ratio changes that may serve as image-based biomarkers for the disease. One three-dimensional volume before and one after diagnosis for each of 48 patients were segmented to identify retinal layer and total retinal thicknesses. Between before- and after-diagnosis retinal OCT images, there were significant thickness changes in six of ten (60%) retinal layers across all 48 patients. Through a comparison with age-matched healthy subjects, the significant changes were attributed to AD only (NFL and PR2 layers), age only (GCL, IPL, and RPE layers), or both AD and age (OPL layer). Analyzing ratios of retinal layer thicknesses, 53 of 90 (58.89%) ratios had significant changes. The four independently non-significant layers were assessed to be affected by neither AD nor age (INL layer) or both AD and age (ELM, PR1, and BM layers). The demonstrated image segmentation, measurement, and ratiometric analysis of retinal layers in AD patients may yield a noninvasive OCT image-based retinal biomarker that can be used to detect retinal changes associated with this disease.

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Available abstract

We analyzed ophthalmic retinal optical coherence tomography (OCT) images from patients with Alzheimer's disease (AD) to identify retinal layer thickness and ratio changes that may serve as image-based biomarkers for the disease. One three-dimensional volume before and one after diagnosis for each of 48 patients were segmented to identify retinal layer and total retinal thicknesses. Between before- and after-diagnosis retinal OCT images, there were significant thickness changes in six of ten (60%) retinal layers across all 48 patients. Through a comparison with age-matched healthy subjects, the significant changes were attributed to AD only (NFL and PR2 layers), age only (GCL, IPL, and RPE layers), or both AD and age (OPL layer). Analyzing ratios of retinal layer thicknesses, 53 of 90 (58.89%) ratios had significant changes. The four independently non-significant layers were assessed to be affected by neither AD nor age (INL layer) or both AD and age (ELM, PR1, and BM layers). The demonstrated image segmentation, measurement, and ratiometric analysis of retinal layers in AD patients may yield a noninvasive OCT image-based retinal biomarker that can be used to detect retinal changes associated with this disease.

Key concepts: Retinal, Optical coherence tomography, Ophthalmology, Retina, Medicine, Nerve fiber layer, Pathology, Biology

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