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Proceedings Paper

Changes in quantitative 3D shape features of the optic nerve head associated with age
Author(s): Mark Christopher; Li Tang; John H. Fingert; Todd E. Scheetz; Michael D. Abramoff
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Paper Abstract

Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

Paper Details

Date Published: 28 February 2013
PDF: 9 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86700O (28 February 2013); doi: 10.1117/12.2006908
Show Author Affiliations
Mark Christopher, The Univ. of Iowa (United States)
Li Tang, The Univ. of Iowa (United States)
John H. Fingert, The Univ. of Iowa (United States)
Todd E. Scheetz, The Univ. of Iowa (United States)
Michael D. Abramoff, The Univ. of Iowa (United States)
U. S. Dept. of Veterans Affairs (United States)

Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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