Paper
24 February 2017 Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments
Author Affiliations +
Abstract
Eye diseases and visual impairment affect millions of Americans and induce billions of dollars in annual economic burdens. Expounding upon existing knowledge of eye diseases could lead to improved treatment and disease prevention. This research investigated the relationship between structural metrics of the eye orbit and visual function measurements in a cohort of 470 patients from a retrospective study of ophthalmology records for patients (with thyroid eye disease, orbital inflammation, optic nerve edema, glaucoma, intrinsic optic nerve disease), clinical imaging, and visual function assessments. Orbital magnetic resonance imaging (MRI) and computed tomography (CT) images were retrieved and labeled in 3D using multi-atlas label fusion. Based on the 3D structures, both traditional radiology measures (e.g., Barrett index, volumetric crowding index, optic nerve length) and novel volumetric metrics were computed. Using stepwise regression, the associations between structural metrics and visual field scores (visual acuity, functional acuity, visual field, functional field, and functional vision) were assessed. Across all models, the explained variance was reasonable (R2 ~ 0.1-0.2) but highly significant (p < 0.001). Instead of analyzing a specific pathology, this study aimed to analyze data across a variety of pathologies. This approach yielded a general model for the connection between orbital structural imaging biomarkers and visual function.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiuya Yao, Shikha Chaganti, Kunal P. Nabar, Katrina Nelson, Andrew Plassard, Rob L. Harrigan, Louise A. Mawn, and Bennett A. Landman "Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments", Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 101331F (24 February 2017); https://doi.org/10.1117/12.2254613
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Cited by 5 scholarly publications.
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KEYWORDS
Visualization

Eye

Magnetic resonance imaging

Computed tomography

Eye models

Image segmentation

Optic nerve

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