Correlation of Retinal Nerve Fiver Layer Thickness and X-linked Dystonia Parkinsonism Measured by Spectral-Domain Optical Coherence Tomography

Erwin  Palisoc,

Correlation of Retinal Nerve Fiver Layer Thickness and X-linked Dystonia Parkinsonism Measured by Spectral-Domain Optical Coherence Tomography

Abstract:

Background: Studies have detected reduction of RNFL thickness in neurodegenerative disorders however, there are no reports on the correlation of retinal findings and vision of X-linked Dystonia Parkinsonism (XDP) patients. Objective: This pilot study aimed to determine the association between Retinal Nerve Fiber Layer (RNFL) thickness using Spectral Domain – Optical Coherence Tomography (SD-OCT) and the duration and type of the disease correlate among XDP patients. Methods: Clinically and genetically confirmed cases of XDP from Panay, Philippines were compared with their agematched controls. Disease severity was measured using the X-linked dystonia-parkinsonism-Movement Disorder Society of the Philippines (XDP-MDSP) rating scale. Disease duration (years), type (dystonia-dominant or parkinsonism-dominant or mixed) were recorded. Structural analysis of the RNFL was performed using spectral domain optical coherence tomography (SD-OCT). The average RNFL thickness and RNFL thickness per 6 sector (superonasal, inferonasal, superotemporal, inferotemporal, temporal, nasal) were reported. Sub-analysis of the relationship of the duration of the disease, MDSP rating, and types of XPD to RNFL thickness were also done. Results: There was a statistically significant thinning of the RNFL thickness of all sectors among XDP cases compared with the controls, except the superotemporal sector. A cut-off value of RNFL thickness per sector, predictive of XDP, was generated however, with poor sensitivity and specificity. Duration of the disease, type of XDP, and severity of disease did not significantly correlate with RNFL thickness. Conclusion: XDP patients have significantly reduced RNFL thickness. Measurement of RNFL thickness can be a promising non-invasive and cost-effective biomarker for the diagnosis of PD and for evaluation of the effect of future therapies.

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