Retinal Venular Tortuosity Jointly with Retinal Amyloid Burden Correlates with Verbal Memory Loss: A Pilot Study.

INTRODUCTION: Retinal imaging is a non-invasive tool to study both retinal vasculature and neurodegeneration. In this exploratory retinal curcumin-fluorescence imaging (RFI) study, we sought to determine whether retinal vascular features combined with retinal amyloid burden correlate with the neurocognitive status. METHODS: We used quantitative RFI in a cohort of patients with cognitive impairment to automatically compute retinal amyloid burden. Retinal blood vessels were segmented, and the vessel tortuosity index (VTI), inflection index, and branching angle were quantified. We assessed the correlations between retinal vascular and amyloid parameters, and cognitive domain Z-scores using linear regression models. RESULTS: Thirty-four subjects were enrolled and twenty-nine (55% female, mean age 64 ± 6 years) were included in the combined retinal amyloid and vascular analysis. Eleven subjects had normal cognition and 18 had impaired cognition. Retinal VTI was discriminated among cognitive scores. The combined proximal mid-periphery amyloid count and venous VTI index exhibited significant differences between cognitively impaired and cognitively normal subjects (0.49 ± 1.1 vs. 0.91 ± 1.4, p = 0.006), and correlated with both the Wechsler Memory Scale-IV and SF-36 mental component score Z-scores (p < 0.05). CONCLUSION: This pilot study showed that retinal venular VTI combined with the proximal mid-periphery amyloid count could predict verbal memory loss. Future research is needed to finesse the clinical application of this retinal imaging-based technology.

Sectoral segmentation of retinal amyloid imaging in subjects with cognitive decline.

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.