Corneal Confocal Microscopy Identifies Parkinson's Disease with More Rapid Motor Progression

Abstract

A BS TRACT: Background: Corneal confocal microscopy (CCM) is a noninvasive, reproducible ophthalmic technique to quantify corneal small nerve fiber degeneration. CCM demonstrates small nerve fiber damage in Parkinson's disease (PD), but its role as a longitudinal biomarker of PD progression has not been explored. Objective: The aim of this study was to assess corneal nerve morphology using CCM in relation to disease progression in PD. Methods: Sixty-four participants with PD were assessed at baseline and at 12-month follow-up. Participants underwent CCM with automated corneal nerve quantification and assessment of Movement Disorder Society Unified Parkinson's Disease Rating Scale, Hoehn and Yahr stage, and Montreal Cognitive Assessment. Results: Corneal nerve fiber density (CNFD), corneal nerve branch density, corneal nerve fiber length, corneal total branch density, and corneal nerve fiber area were significantly lower in participants with PD compared with healthy control subjects. Worsening of Movement Disorder Society Unified Parkinson's Disease Rating Scale part III score over 12 months was significantly greater in participants with a CNFD in the lowest compared with the highest quartile at baseline

Corneal Confocal Microscopy to Image Small Nerve Fiber Degeneration: Ophthalmology Meets Neurology

“…In a recent study from China, CNFD showed an excellent diagnostic performance with a AUC of 0.96 for PD and corneal nerve fiber parameters correlated with the severity of motor symptoms measured using the H-Y stage, UPDRS-III and UPDRS-Total ( 81 ). Furthermore, we have shown that a lower corneal nerve fiber length predicts progressive worsening of UPDRS-III over 12 months in patients with PD ( 82 ). CCM could therefore add to the diagnostic toolbox for pre-motor Parkinson's disease.…”

Corneal Confocal Microscopy and the Nervous System: Introduction to the Special Issue

“…We have confirmed corneal nerve fibre loss in PD [ 74 ], with CNFD demonstrating excellent diagnostic utility [ 75 ]. A lower CNFL predicts progressive worsening of UPDRS-III over 12 months in patients with PD [ 76 ], suggesting the application of CCM in diagnosing pre-motor PD.…”

Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson’s Disease?

“…The validation strategies used for clinical scales and questionnaires, where a new instrument must correlate with another already-validated measure, may not be sufficient for the validation of AI-generated outputs. While recognizing that the use of a “biomarker” identified from a population might not be appropriate for application to an individual [ 8 ], researchers may still need to compare AI outputs with those of established techniques such as quantitative MRI/SPECT [ 9 ], corneal confocal microscopy [ 10 ], camera tremor magnification [ 11 ], and retinal nerve fiber layer thickness [ 12 ].…”