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 < 1Eā04) the R2 to 0.4 for glaucoma and 0.54 for TED.
CITATION STYLE
Chaganti, S., Robinson, J. R., Bermudez, C., Lasko, T., Mawn, L. A., & Landman, B. A. (2017). EMR-radiological phenotypes in diseases of the optic nerve and their association with visual function. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10553 LNCS, pp. 373ā381). Springer Verlag. https://doi.org/10.1007/978-3-319-67558-9_43
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