Share Email Print
cover

Proceedings Paper

Hip fracture risk estimation based on principal component analysis of QCT atlas: a preliminary study
Author(s): Wenjun Li; John Kornak; Tamara Harris; Ying Lu; Xiaoguang Cheng; Thomas Lang
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We aim to capture and apply 3-dimensional bone fragility features for fracture risk estimation. Using inter-subject image registration, we constructed a hip QCT atlas comprising 37 patients with hip fractures and 38 age-matched controls. In the hip atlas space, we performed principal component analysis to identify the principal components (eigen images) that showed association with hip fracture. To develop and test a hip fracture risk model based on the principal components, we randomly divided the 75 QCT scans into two groups, one serving as the training set and the other as the test set. We applied this model to estimate a fracture risk index for each test subject, and used the fracture risk indices to discriminate the fracture patients and controls. To evaluate the fracture discrimination efficacy, we performed ROC analysis and calculated the AUC (area under curve). When using the first group as the training group and the second as the test group, the AUC was 0.880, compared to conventional fracture risk estimation methods based on bone densitometry, which had AUC values ranging between 0.782 and 0.871. When using the second group as the training group, the AUC was 0.839, compared to densitometric methods with AUC values ranging between 0.767 and 0.807. Our results demonstrate that principal components derived from hip QCT atlas are associated with hip fracture. Use of such features may provide new quantitative measures of interest to osteoporosis.

Paper Details

Date Published: 27 February 2009
PDF: 8 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72621M (27 February 2009); doi: 10.1117/12.811743
Show Author Affiliations
Wenjun Li, Univ. of California, San Francisco (United States)
John Kornak, Univ. of California, San Francisco (United States)
Tamara Harris, National Institute of Health (United States)
Ying Lu, Univ. of California, San Francisco (United States)
Xiaoguang Cheng, Beijing Ji Shui Tan Hospital (China)
Thomas Lang, Univ. of California, San Francisco (United States)


Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

© SPIE. Terms of Use
Back to Top