A multi-regression framework to improve diagnostic ability of optical coherence tomography retinal biomarkers to discriminate mild cognitive impairment and Alzheimer’s disease

Abstract

Background Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer’s disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD. Methods This cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements. Results Participants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p < 0.05). Compensated RNFL outperformed measured RNFL for discrimination of MCI/AD (AUC = 0.74 vs 0.69; p = 0.026). Combining macular and compensated cpRNFL parameters provided the best detection of MCI/AD (AUC = 0.80 vs 0.69; p < 0.001). Conclusions and relevance Accounting for interindividual variations of ocular anatomical features in cpRNFL measurements and incorporating macular information may improve the identification of high-risk individuals with early cognitive impairment.

A two-year longitudinal study of retinal vascular impairment in patients with amnestic mild cognitive impairment

“…Despite many effort, further studies are need to identify a biomarker able to diagnose and monitor clinical progression of dementia, even if a recent study developed a multiregression framework to improve diagnostic ability of OCT to discriminate MCI and Alzheimer’s disease ( Chua et al, 2022 ).…”

Combining retinal structural and vascular measurements improves discriminative power for multiple sclerosis patients

“…The compensation model enhanced the discriminative power of RNFL by reducing the nondisease variability in the RNFL, thereby allowing the detection of a smaller amount of disease‐related thinning in a patient's RNFL with improved specificity. Apart from MS, 4 the compensation model also enhanced the detection of early glaucoma 36 and Alzheimer's disease 35 …”

“…We compensated the RNFL thickness for numerous factors (optic disc [ratio, orientation, and area], fovea [distance and angle], retinal vessel density, refractive error, and age) using a previously described multivariate linear regression-based model. 28,[34][35][36] Optic disc ratio refers to the quotient between major and minor axis, and orientation refers to the angle between the horizontal axis and the major axis of the optic disc. Briefly, RNFL thickness measurements were extracted from the optic disc OCT scans using the Cirrus Review Software (Carl Zeiss Meditec, version 11.0.0.29946).…”

“…Apart from MS, 4 the compensation model also enhanced the detection of early glaucoma 36 and Alzheimer's disease. 35…”

Glaucoma detection based on optical coherence tomography imaging

“…Excitingly, early detection of cognitive impairment may be achievable through OCT imaging of the eyes. In our study, we have undertaken preliminary statistical analyses and the compensation model to investigate this relationship (70). Looking ahead, we plan to extend our research by employing similar DL and ML algorithms utilizing OCT images of the eyes which are described in this thesis.…”