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EMR-Radiological Phenotypes in Diseases of the Optic Nerve and Their Association with Visual Function

  • Shikha Chaganti
  • Jamie R. Robinson
  • Camilo Bermudez
  • Thomas Lasko
  • Louise A. Mawn
  • Bennett A. Landman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10553)

Abstract

Multi-modal analyses of diseases of the optic nerve, that combine radiological imaging with other electronic medical records (EMR), improve understanding of visual function. We conducted a study of 55 patients with glaucoma and 32 patients with thyroid eye disease (TED). We collected their visual assessments, orbital CT imaging, and EMR data. We developed an image-processing pipeline that segmented and extracted structural metrics from CT images. We derived EMR phenotype vectors with the help of PheWAS (from diagnostic codes) and ProWAS (from treatment codes). Next, we performed a principal component analysis and multiple-correspondence analysis to identify their association with visual function scores. We found that structural metrics derived from CT imaging are significantly associated with functional visual score for both glaucoma (R2 = 0.32) and TED (R2 = 0.4). Addition of EMR phenotype vectors to the model significantly improved (p < 1E−04) the R2 to 0.4 for glaucoma and 0.54 for TED.

Keywords

CT imaging EMR Regression Optic nerve MCA PCA 

Notes

Acknowledgements

This research was supported by NSF CAREER 1452485 and NIH grants 5R21EY024036. This research was conducted with the support from Intramural Research Program, National Institute on Aging, NIH. This study was in part using the resources of the Advanced Computing Center for Research and Education (ACCRE) at Vanderbilt University, Nashville, TN. This project was supported in part by ViSE/VICTR VR3029 and the National Center for Research Resources, Grant UL1 RR024975-01, and is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceVanderbilt UniversityNashvilleUSA
  2. 2.Vanderbilt University Medical CenterNashvilleUSA
  3. 3.Department of Biomedical EngineeringVanderbilt UniversityNashvilleUSA
  4. 4.Department of Biomedical InformaticsVanderbilt UniversityNashvilleUSA
  5. 5.Vanderbilt Eye InstituteNashvilleUSA
  6. 6.Department of Electrical EngineeringVanderbilt UniversityNashvilleUSA

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