Circular functional analysis of OCT data for precise identification of structural phenotypes in the eye

M.H. Ali*, B. Wainwright, A. Petersen, G.B. Jonnadula, M. Desai, H.L. Rao, M.B. Srinivas, S.R. Jammalamadaka, S. Senthil, S. Pyne*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Progressive optic neuropathies such as glaucoma are major causes of blindness globally. Multiple sources of subjectivity and analytical challenges are often encountered by clinicians in the process of early diagnosis and clinical management of these diseases. In glaucoma, the structural damage is often characterized by neuroretinal rim (NRR) thinning of the optic nerve head, and other clinical parameters. Baseline structural heterogeneity in the eyes can play a key role in the progression of optic neuropathies, and present challenges to clinical decision-making. We generated a dataset of Optical Coherence Tomography (OCT) based high-resolution circular measurements on NRR phenotypes, along with other clinical covariates, of 3973 healthy eyes as part of an established clinical cohort of Asian Indian participants. We introduced CIFU, a new computational pipeline for CIrcular FUnctional data modeling and analysis. We demonstrated CIFU by unsupervised circular functional clustering of the OCT NRR data, followed by meta-clustering to characterize the clusters using clinical covariates, and presented a circular visualization of the results. Upon stratification by age, we identified a healthy NRR phenotype cluster in the age group 40-49 years with predictive potential for glaucoma. Our dataset also addresses the disparity of representation of this particular population in normative OCT databases.
Original languageEnglish
Article number23336
Number of pages13
JournalScientific Reports
Volume11
Issue number1
DOIs
Publication statusPublished - 2 Dec 2021

Keywords

  • OPTIC-NERVE HEAD
  • FIBER LAYER THICKNESS
  • COHERENCE TOMOGRAPHY
  • SIGNAL STRENGTH
  • MIXTURE MODEL
  • GLAUCOMA
  • PARAMETERS
  • ACCURACY
  • NUMBER
  • SIZE

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