Neurology and Preclinical Neurological Studies - Original Article

Journal of Neural Transmission

, Volume 121, Issue 11, pp 1367-1376

Application of an OCT data-based mathematical model of the foveal pit in Parkinson disease

  • Yin DingAffiliated withDepartment of Electrical and Computer Engineering, Polytechnic Institute of New York University
  • , Brian SpundAffiliated withNorth Shore University Hospital
  • , Sofya GlazmanAffiliated withDepartment of Neurology, SUNY Downstate Medical Center
  • , Eric M. ShrierAffiliated withDepartment of Ophthalmology, SUNY Downstate Medical CenterSUNY Eye Institute
  • , Shahnaz MiriAffiliated withDepartment of Neurology, SUNY Downstate Medical Center
  • , Ivan SelesnickAffiliated withDepartment of Electrical and Computer Engineering, Polytechnic Institute of New York UniversityThe School of Graduate Studies, SUNY Downstate Medical Center
  • , Ivan Bodis-WollnerAffiliated withDepartment of Neurology, SUNY Downstate Medical CenterDepartment of Ophthalmology, SUNY Downstate Medical CenterSUNY Eye InstituteThe School of Graduate Studies, SUNY Downstate Medical Center Email author 

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Abstract

Spectral-domain Optical coherence tomography (OCT) has shown remarkable utility in the study of retinal disease and has helped to characterize the fovea in Parkinson disease (PD) patients. We developed a detailed mathematical model based on raw OCT data to allow differentiation of foveae of PD patients from healthy controls. Of the various models we tested, a difference of a Gaussian and a polynomial was found to have “the best fit”. Decision was based on mathematical evaluation of the fit of the model to the data of 45 control eyes versus 50 PD eyes. We compared the model parameters in the two groups using receiver-operating characteristics (ROC). A single parameter discriminated 70 % of PD eyes from controls, while using seven of the eight parameters of the model allowed 76 % to be discriminated. The future clinical utility of mathematical modeling in study of diffuse neurodegenerative conditions that also affect the fovea is discussed.

Keywords

Fovea Retinal imaging Optical coherence tomography (OCT) Parkinson disease (PD) Mathematical modeling