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

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...

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Autores principales: Kavitha, M S, Asano, Akira, Taguchi, Akira, Kurita, Takio, Sanada, Mitsuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269982/
https://www.ncbi.nlm.nih.gov/pubmed/22248480
http://dx.doi.org/10.1186/1471-2342-12-1
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author Kavitha, M S
Asano, Akira
Taguchi, Akira
Kurita, Takio
Sanada, Mitsuhiro
author_facet Kavitha, M S
Asano, Akira
Taguchi, Akira
Kurita, Takio
Sanada, Mitsuhiro
author_sort Kavitha, M S
collection PubMed
description 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.
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spelling pubmed-32699822012-02-13 Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system Kavitha, M S Asano, Akira Taguchi, Akira Kurita, Takio Sanada, Mitsuhiro BMC Med Imaging Research Article 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. BioMed Central 2012-01-16 /pmc/articles/PMC3269982/ /pubmed/22248480 http://dx.doi.org/10.1186/1471-2342-12-1 Text en Copyright ©2012 Kavitha et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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.
spellingShingle Research Article
Kavitha, M S
Asano, Akira
Taguchi, Akira
Kurita, Takio
Sanada, Mitsuhiro
Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title_full Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title_fullStr Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title_full_unstemmed Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title_short Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
title_sort diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269982/
https://www.ncbi.nlm.nih.gov/pubmed/22248480
http://dx.doi.org/10.1186/1471-2342-12-1
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