Background: Recent developments in the retinal hyperspectral imaging method have indicated its potential in addressing challenges posed by neurodegenerative disorders, such as Alzheimer's disease. This human clinical study is the first to assess reflectance spectra obtained from this imaging as a tool for diagnosing patients with Parkinson's disease (PD).
Methods: Retinal hyperspectral imaging was conducted on a total of 40 participants, including 20 patients with PD and 20 controls. Following preprocessing, retinal reflectance spectra were computed for the macular retina defined by four rectangular regions. Linear discriminant analysis classifiers underwent training to discern patients with PD from control participants. To assess the performance of the selected features, nested leave-one-out cross-validation was employed using machine learning. The indicated values include the area under the curve (AUC) and the corresponding 95% confidence interval (CI).
Results: Retinal reflectance spectra of PD patients exhibited variations in the spectral regions, particularly at shorter wavelengths (superonasal retina, wavelength < 490 nm; inferonasal retina, wavelength < 510 nm) when compared to those of controls. Retinal reflectance spectra yielded an AUC of 0.60 (95% CI: 0.43-0.78) and 0.60 (95% CI: 0.43-0.78) for the superonasal and inferonasal retina, respectively, distinguishing individuals with and without PD.
Conclusion: Reflectance spectra obtained from retinal hyperspectral imaging tended to decrease at shorter wavelengths across a broad spectral range in PD patients. Further investigations building upon these preliminary findings are imperative to focus on the retinal spectral signatures associated with PD pathological hallmarks, including α-synuclein.
Keywords: Parkinson's disease; Reflectance spectra; Retina; Retinal hyperspectral imaging; α-Synuclein.
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