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Proceedings Paper

Computerized method for detection of vertebral fractures on lateral chest radiographs based on morphometric data
Author(s): Satoshi Kasai; Feng Li; Junji Shiraishi; Qiang Li; Christopher Straus; Tamara Vokes; Heber MacMahon; Kunio Doi
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Paper Abstract

Vertebral fractures are the most common osteoporosis-related fractures. It is important to detect vertebral fractures, because they are associated with increased risk of subsequent fractures, and because pharmacologic therapy can reduce the risk of subsequent fractures. Although vertebral fractures are often not clinically recognized, they can be visualized on lateral chest radiographs taken for other purposes. However, only 15-60% of vertebral fractures found on lateral chest radiographs are mentioned in radiology reports. The purpose of this study was to develop a computerized method for detection of vertebral fractures on lateral chest radiographs in order to assist radiologists' image interpretation. Our computerized method is based on the automated identification of upper and lower vertebral edges. In order to develop the scheme, radiologists provided morphometric data for each identifiable vertebra, which consisted of six points for each vertebra, for 25 normals and 20 cases with severe fractures. Anatomical information was obtained from morphometric data of normal cases in terms of vertebral heights, heights of vertebral disk spaces, and vertebral centerline. Computerized detection of vertebral fractures was based on the reduction in the heights of fractured vertebrae compared to adjacent vertebrae and normal reference data. Vertebral heights from morphometric data on normal cases were used as reference. On 138 chest radiographs (20 with fractures) the sensitivity of our method for detection of fracture cases was 95% (19/20) with 0.93 (110/118) false-positives per image. In conclusion, the computerized method would be useful for detection of potentially overlooked vertebral fractures on lateral chest radiographs.

Paper Details

Date Published: 30 March 2007
PDF: 9 pages
Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141N (30 March 2007);
Show Author Affiliations
Satoshi Kasai, The Univ. of Chicago (United States)
Feng Li, The Univ. of Chicago (United States)
Junji Shiraishi, The Univ. of Chicago (United States)
Qiang Li, The Univ. of Chicago (United States)
Christopher Straus, The Univ. of Chicago (United States)
Tamara Vokes, The Univ. of Chicago (United States)
Heber MacMahon, The Univ. of Chicago (United States)
Kunio Doi, The Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 6514:
Medical Imaging 2007: Computer-Aided Diagnosis
Maryellen L. Giger; Nico Karssemeijer, Editor(s)

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