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

Yin Ding, Brian Spund, Sofya Glazman, Eric M. Shrier, Shahnaz Miri, Ivan Selesnick, Ivan Bodis-Wollner

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1367-1376
Number of pages10
JournalJournal of Neural Transmission
Issue number11
StatePublished - Apr 20 2014
Externally publishedYes


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

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health
  • Biological Psychiatry


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