Background: Early diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality\r\nof life. Detection of thin inferior cortices of the mandible on dental panoramic radiographs could be useful for\r\nidentifying postmenopausal women with low bone mineral density (BMD) or osteoporosis. The aim of our study\r\nwas to assess the diagnostic efficacy of using kernel-based support vector machine (SVM) learning regarding the\r\ncortical width of the mandible on dental panoramic radiographs to identify postmenopausal women with low\r\nBMD.\r\nMethods: We employed our newly adopted SVM method for continuous measurement of the cortical width of\r\nthe mandible on dental panoramic radiographs to identify women with low BMD or osteoporosis. The original\r\nX-ray image was enhanced, cortical boundaries were determined, distances among the upper and lower\r\nboundaries were evaluated and discrimination was performed by a radial basis function. We evaluated the\r\ndiagnostic efficacy of this newly developed method for identifying women with low BMD (BMD T-score of -1.0 or\r\nless) at the lumbar spine and femoral neck in 100 postmenopausal women (=50 years old) with no previous\r\ndiagnosis of osteoporosis. Sixty women were used for system training, and 40 were used in testing.\r\nResults: The sensitivity and specificity using RBF kernel-SVM method for identifying women with low BMD were\r\n90.9% [95% confidence interval (CI), 85.3-96.5] and 83.8% (95% CI, 76.6-91.0), respectively at the lumbar spine and\r\n90.0% (95% CI, 84.1-95.9) and 69.1% (95% CI, 60.1-78.6), respectively at the femoral neck. The sensitivity and\r\nspecificity for identifying women with low BMD at either the lumbar spine or femoral neck were 90.6% (95% CI,\r\n92.0-100) and 80.9% (95% CI, 71.0-86.9), respectively.\r\nConclusion: Our results suggest that the newly developed system with the SVM method would be useful for\r\nidentifying postmenopausal women with low skeletal BMD.
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