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

M S Kavitha,Takio Kurita,Mitsuhiro Sanada,Akira Asano,Akira Taguchi

doi:10.1186/1471-2342-12-1

M S Kavitha, Takio Kurita + Show 3 more

Open Access

https://doi.org/10.1186/1471-2342-12-1

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Abstract

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.

Highlights

Diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality of life
Many studies have shown a correlation between the mandibular cortical width (MCW) on dental panoramic radiographs and bone mineral density (BMD) at the hip [7], lumbar spine [8] and forearm [9], the most common sites of fracture related to osteoporosis in postmenopausal women
The sensitivity and specificity for the combined data of both the lumbar spine and femoral neck BMD using support vector machine (SVM) method processed with 130 training and 70 testing sets were 90.6% and 80.9% respectively (Table 2)

Summary

Introduction

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. The incidence is higher in developed countries, primarily because they have a large elderly population. Many studies have shown a correlation between the mandibular cortical width (MCW) on dental panoramic radiographs and BMD at the hip [7], lumbar spine [8] and forearm [9], the most common sites of fracture related to osteoporosis in postmenopausal women. The costs associated with advanced imaging techniques and distribution of the equipment limit their accessibility for large segments of populations and broadbased screening examinations

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