Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system

BMC Medical Imaging

Research Article

Akira Taguchi¹  Takio Kurita²  M S Kavitha²  Akira Asano³  Mitsuhiro Sanada⁴ 

[1] Department of Oral and Maxillofacial Radiology, Matsumoto Dental University, 1780 Hirooka-Gohara, 399-0781, Shiojiri, Nagano, Japan;Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, 739-8527, Higashi-Hiroshima, Hiroshima, Japan;Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, 739-8527, Higashi-Hiroshima, Hiroshima, Japan;Faculty of Informatics, Kansai University, 2-1-1 Ryozenji-cho, 506-1095, TakatsukiOsaka, Japan;Sanada Hospital, Minamimachi 3-13-21, 734-0007, Minami-ku, Hiroshima, Japan;

关键词: Bone Mineral Density;    Support Vector Machine;    Radial Basis Function;    Lumbar Spine Bone Mineral Density;    Femoral Neck Bone Mineral Density;   

DOI  :  10.1186/1471-2342-12-1

 received in 2011-08-25, accepted in 2012-01-16,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundEarly diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality of life. Detection of thin inferior cortices of the mandible on dental panoramic radiographs could be useful for identifying postmenopausal women with low bone mineral density (BMD) or osteoporosis. The aim of our study was to assess the diagnostic efficacy of using kernel-based support vector machine (SVM) learning regarding the cortical width of the mandible on dental panoramic radiographs to identify postmenopausal women with low BMD.MethodsWe employed our newly adopted SVM method for continuous measurement of the cortical width of the mandible on dental panoramic radiographs to identify women with low BMD or osteoporosis. The original X-ray image was enhanced, cortical boundaries were determined, distances among the upper and lower boundaries were evaluated and discrimination was performed by a radial basis function. We evaluated the diagnostic efficacy of this newly developed method for identifying women with low BMD (BMD T-score of -1.0 or less) at the lumbar spine and femoral neck in 100 postmenopausal women (≥50 years old) with no previous diagnosis of osteoporosis. Sixty women were used for system training, and 40 were used in testing.ResultsThe sensitivity and specificity using RBF kernel-SVM method for identifying women with low BMD were 90.9% [95% confidence interval (CI), 85.3-96.5] and 83.8% (95% CI, 76.6-91.0), respectively at the lumbar spine and 90.0% (95% CI, 84.1-95.9) and 69.1% (95% CI, 60.1-78.6), respectively at the femoral neck. The sensitivity and specificity for identifying women with low BMD at either the lumbar spine or femoral neck were 90.6% (95% CI, 92.0-100) and 80.9% (95% CI, 71.0-86.9), respectively.ConclusionOur results suggest that the newly developed system with the SVM method would be useful for identifying postmenopausal women with low skeletal BMD.

【 授权许可】

Unknown   
© Kavitha et al; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.