A novel retinal biomarker for Parkinson's disease: Quantifying the foveal pit with optical coherence tomography

Samantha Slotnick; Yin Ding; Sofya Glazman; Mary Durbin; Shahnaz Miri; Ivan Selesnick; Jerome Sherman; Ivan Bodis-Wollner

doi:10.1002/mds.26411

A novel retinal biomarker for Parkinson's disease: Quantifying the foveal pit with optical coherence tomography

Samantha Slotnick, Yin Ding, Sofya Glazman, Mary Durbin, Shahnaz Miri, Ivan Selesnick, Jerome Sherman, Ivan Bodis-Wollner

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

Background: Optical coherence tomography offers a potential biomarker tool in Parkinson's disease (PD). A mathematical model quantifying symmetry, breadth, and depth of the fovea was applied. Methods: Nintey-six subjects (72 PD and 24 healthy controls) were included in the study. Macular scans of each eye were obtained on two different optical coherence tomography devices: Cirrus and RTVue. Results: The variables corresponding to the cardinal gradients of the fovea were the most sensitive indicators of PD for both devices. Principal component analysis distinguished 65% of PD patients from controls on Cirrus, 57% on RTVue. Conclusion: Parkinson's disease shallows the superior/inferior and to a lesser degree nasal-temporal foveal slope. The symmetry, breadth, and depth model fits optical coherence tomography data derived from two different devices, and it is proposed as a diagnostic tool in PD.

Original language	English (US)
Pages (from-to)	1692-1695
Number of pages	4
Journal	Movement Disorders
Volume	30
Issue number	12
DOIs	https://doi.org/10.1002/mds.26411
State	Published - Oct 2015

Keywords

Foveal pit
Optical coherence tomography
Parkinson's disease
Principal component analysis
SBD model

ASJC Scopus subject areas

Neurology
Clinical Neurology

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10.1002/mds.26411

Cite this

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title = "A novel retinal biomarker for Parkinson's disease: Quantifying the foveal pit with optical coherence tomography",

abstract = "Background: Optical coherence tomography offers a potential biomarker tool in Parkinson's disease (PD). A mathematical model quantifying symmetry, breadth, and depth of the fovea was applied. Methods: Nintey-six subjects (72 PD and 24 healthy controls) were included in the study. Macular scans of each eye were obtained on two different optical coherence tomography devices: Cirrus and RTVue. Results: The variables corresponding to the cardinal gradients of the fovea were the most sensitive indicators of PD for both devices. Principal component analysis distinguished 65% of PD patients from controls on Cirrus, 57% on RTVue. Conclusion: Parkinson's disease shallows the superior/inferior and to a lesser degree nasal-temporal foveal slope. The symmetry, breadth, and depth model fits optical coherence tomography data derived from two different devices, and it is proposed as a diagnostic tool in PD.",

keywords = "Foveal pit, Optical coherence tomography, Parkinson's disease, Principal component analysis, SBD model",

author = "Samantha Slotnick and Yin Ding and Sofya Glazman and Mary Durbin and Shahnaz Miri and Ivan Selesnick and Jerome Sherman and Ivan Bodis-Wollner",

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year = "2015",

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AU - Glazman, Sofya

AU - Durbin, Mary

AU - Miri, Shahnaz

AU - Selesnick, Ivan

AU - Sherman, Jerome

AU - Bodis-Wollner, Ivan

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A novel retinal biomarker for Parkinson's disease: Quantifying the foveal pit with optical coherence tomography

Abstract

Keywords

ASJC Scopus subject areas

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