Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
Open Access
- 16 January 2012
- journal article
- research article
- Published by Springer Nature in BMC Medical Imaging
- Vol. 12 (1) , 1
Abstract
Background: Early 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.Methods: We 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.Results: The 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.Conclusion: Our results suggest that the newly developed system with the SVM method would be useful for identifying postmenopausal women with low skeletal BMD.Keywords
This publication has 29 references indexed in Scilit:
- JICD mattersJournal of Investigative and Clinical Dentistry, 2011
- Triage screening for osteoporosis in dental clinics using panoramic radiographsOral Diseases, 2010
- Diagnosis of osteoporosis in oral health careJournal of Oral Rehabilitation, 2008
- Automated osteoporosis risk assessment by dentists: A new pathway to diagnosisBone, 2007
- SVM-based prediction of caspase substrate cleavage sitesBMC Bioinformatics, 2006
- Fracture Prediction From Bone Mineral Density in Japanese Men and WomenJournal of Bone and Mineral Research, 2003
- The relationships between two indices of mandibular bone quality and bone mineral density measured by dual energy X-ray absorptiometry.Dentomaxillofacial Radiology, 1998
- Texture analysis of direct magnification radiographs of vertebral specimens: Correlation with bone mineral density and biomechanical propertiesAcademic Radiology, 1997
- Pantomography in assessment of the osteoporosis risk groupEuropean Journal of Oral Sciences, 1994
- The radiographic trabecular bone pattern during menopauseBone, 1993