Sectoral segmentation of retinal amyloid imaging in subjects with cognitive decline. Issue 1 (28th September 2020)

• Record Type: Journal Article
• Authors: Dumitrascu, Oana M.; Lyden, Patrick D.; Torbati, Tania; Sheyn, Julia; Sherzai, Ayesha; Sherzai, Dean; Sherman, Dale S.; Rosenberry, Ryan; Cheng, Susan; Johnson, Kenneth O.; Czeszynski, Alan D.; Verdooner, Steven; Frautschy, Sally; Black, Keith L.; Koronyo, Yosef; Koronyo‐Hamaoui, Maya
• Is Part Of: Alzheimer's & dementia. Volume 12:Issue 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-09-28
• Subjects: Alzheimer's disease -- amyloid beta -- brain volumetric analysis -- confocal scanning ophthalmoscope -- neurodegenerative disease -- Retia -- retina; Alzheimer's disease -- Periodicals; Alzheimer's disease -- Diagnosis -- Periodicals; Dementia -- Periodicals; Dementia -- Diagnosis -- Periodicals; 616.831
• DOI: 10.1002/dad2.12109
• Languages: English
• ISSNs: 2352-8729

Abstract

Abstract: Introduction: Despite advances in imaging retinal amyloidosis, a quantitative and topographical investigation of retinal amyloid beta burden in patients with cognitive decline has never been reported. Methods: We used the specific amyloid‐binding fluorophore curcumin and laser ophthalmoscopy to assess retinal amyloid imaging (RAI) in 34 patients with cognitive decline. We automatically quantified retinal amyloid count (RAC) and area in the superotemporal retinal sub‐regions and performed correlation analyses with cognitive and brain volumetric parameters. Results: RAC significantly and inversely correlated with hippocampal volume (HV; r = ‐0.39, P = .04). The proximal mid‐periphery (PMP) RAC and RA areas were significantly greater in patients with Montreal Cognitive Assessment (MOCA) score < 26 ( P = .01; Cohen d = 0.83 and 0.81, respectively). PMP showed significantly more RAC and area in subjects with amnestic mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared to cognitively normal ( P = .04; Cohen d = 0.83). Conclusion: Quantitative RAI is a feasible technique and PMP RAC may predict HV. Future larger studies should determine RAI's potential as a biomarker of early AD.