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Correlations Between Oculometric Measures and Traditional Clinical Assessments in Multiple Sclerosis
S Levy1, I B Katz Sand1, O Berkman2
1Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Background:
Oculomotor abnormalities are common in multiple sclerosis (MS) but are not quantitatively evaluated in clinical practice. Oculometric measures (OMs) are characteristics of eye movements captured while performing a visual task, e.g., the latency of saccadic and anti-saccadic metrics. Physical and cognitive deficits are prevalent among persons with MS, including disease-related oculomotor dysfunction. Recently, we have implemented a novel software-based platform enabling the extraction of OMs using a PC and a webcam.
Objective:
The objective of this study is to investigate the relationships between OMs and traditional outcome measures of physical and cognitive dysfunction in MS.
Methods:
Oculometric evaluation using a novel software-based platform (NeuraLight, Israel) was performed in patients with relapsing-remitting MS (n = 57; 36 females, age 41.4 ± 8.6). Physical disability was assessed by an MS-specific neurologic exam (Expanded Disability Status Scale; EDSS) and quantitative measures of cognitive and sensorimotor function (Symbol Digit Modalities Test; SDMT and Nine Hole Peg Test; NHPT). Various OMs were calculated out of multiple measures: Saccadic latency, gain and gaze during fixation, as well as error rate of saccades. Spearman's rank correlation was computed for each OM to assess the relationship with clinical scores.
Results:
Various OMs were correlated with EDSS scores, as pro- and anti-saccadic latency (OM1 r = 0.36, OM2 r = 0.50, OM3 r = 0.39, OM4 r = 0.49; P-values<0.0001), initial gain during saccades (OM6 r = 0.47, OM7 r = 0.30, OM8 r = 0.59; p < 0.0001), stability of gaze during fixation (OM9 r = 0.48, OM10 r = 0.41; p < 0.0001) and error rate of anti-saccades (OM11 r = 0.59; p < 0.0001). Similar correlations were found between these OMs and NHPT scores (OM1 r = 0.41, OM2 r = 0.46, OM3 r = 0.31, OM4 r = 0.50; P-values<0.0001), initial gain (OM6 r = 0.40, OM7 r = 0.39, OM8 r = 0.58; Ps<0.0001) and error rate (OM11 r = 0.36; p < 0.0001). Finally, OMs were correlated with SDMT scores: OM1 and OM2 r=-0.31, OM3 r=-0.26, SD r=-0.38; p < 0.05), OM7 r=-0.36, OM8 r=-0.45; Ps<0.0001) and fixation stability (OM9 r=-0.36, Om10 r=-0.45; p < 0.05).
Conclusions:
OMs captured using a novel software-based platform were found to be associated with physical and cognitive function, suggesting that they can be used as a relevant tool in MS clinical assessment. Further studies will include larger cohorts and assess participants longitudinally to determine the potential value of OMs as predictors of future MS-related disability.
