Development of a prediction tool for low bone mass based on clinical data and periapical radiography

Detalhes bibliográficos
Autor(a) principal: Licks, Renata
Data de Publicação: 2010
Outros Autores: Licks, V., Ourique, F., Bittencourt, Helio Radke, Fontanella, Vania Regina Camargo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/115777
Resumo: Objectives: This study aimed to develop and test a tool for low bone mass pre-screening by combining periapical radiographs with clinical risk factors. Methods: The study sample consisted of 60 post-menopausal women over 40 years of age who were referred for dental radiographs. These patients also had their bone mineral density measured at the lumbar spine and proximal femur using dual-energy X-ray absorptiometry. Radiographic density measurements and 14 morphological features were obtained from each dental radiograph using digital image processing software. The clinical variables considered were age and bone mass index. Classification and regression tree analysis (CART) was used to test the predictive power of clinical and radiographic risk factors for classifying individuals. Results: CART indicated that the most important variables for classifying patients were age, number of terminal points/periphery, periphery/trabecular area, radiographic density and bone mass index. Conclusion: A combination of clinical and radiographic factors can be used to identify individuals with low bone mineral density, with higher accuracy than any one of these factors taken individually.
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spelling Licks, RenataLicks, V.Ourique, F.Bittencourt, Helio RadkeFontanella, Vania Regina Camargo2015-05-05T01:58:25Z20100250-832Xhttp://hdl.handle.net/10183/115777000952405Objectives: This study aimed to develop and test a tool for low bone mass pre-screening by combining periapical radiographs with clinical risk factors. Methods: The study sample consisted of 60 post-menopausal women over 40 years of age who were referred for dental radiographs. These patients also had their bone mineral density measured at the lumbar spine and proximal femur using dual-energy X-ray absorptiometry. Radiographic density measurements and 14 morphological features were obtained from each dental radiograph using digital image processing software. The clinical variables considered were age and bone mass index. Classification and regression tree analysis (CART) was used to test the predictive power of clinical and radiographic risk factors for classifying individuals. Results: CART indicated that the most important variables for classifying patients were age, number of terminal points/periphery, periphery/trabecular area, radiographic density and bone mass index. Conclusion: A combination of clinical and radiographic factors can be used to identify individuals with low bone mineral density, with higher accuracy than any one of these factors taken individually.application/pdfengDentomaxillofacial radiology. Oxford, UK. Vol. 39, no. 4 (May 2010), p. 224-230RadiografiaOsteoporoseOdontologiaBone densityOsteoporosisDental radiographyDevelopment of a prediction tool for low bone mass based on clinical data and periapical radiographyEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSORIGINAL000952405.pdf000952405.pdfTexto completo (inglês)application/pdf213342http://www.lume.ufrgs.br/bitstream/10183/115777/1/000952405.pdf48b4346fc88a0bba47f18f00b2e046e4MD51TEXT000952405.pdf.txt000952405.pdf.txtExtracted Texttext/plain29623http://www.lume.ufrgs.br/bitstream/10183/115777/2/000952405.pdf.txtbe0e8d2c5ef01754b80fd1997da85323MD52THUMBNAIL000952405.pdf.jpg000952405.pdf.jpgGenerated Thumbnailimage/jpeg1809http://www.lume.ufrgs.br/bitstream/10183/115777/3/000952405.pdf.jpg34f04ccab6561e3e7509afb7edbfcf63MD5310183/1157772018-10-22 07:42:37.22oai:www.lume.ufrgs.br:10183/115777Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2018-10-22T10:42:37Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Development of a prediction tool for low bone mass based on clinical data and periapical radiography
title Development of a prediction tool for low bone mass based on clinical data and periapical radiography
spellingShingle Development of a prediction tool for low bone mass based on clinical data and periapical radiography
Licks, Renata
Radiografia
Osteoporose
Odontologia
Bone density
Osteoporosis
Dental radiography
title_short Development of a prediction tool for low bone mass based on clinical data and periapical radiography
title_full Development of a prediction tool for low bone mass based on clinical data and periapical radiography
title_fullStr Development of a prediction tool for low bone mass based on clinical data and periapical radiography
title_full_unstemmed Development of a prediction tool for low bone mass based on clinical data and periapical radiography
title_sort Development of a prediction tool for low bone mass based on clinical data and periapical radiography
author Licks, Renata
author_facet Licks, Renata
Licks, V.
Ourique, F.
Bittencourt, Helio Radke
Fontanella, Vania Regina Camargo
author_role author
author2 Licks, V.
Ourique, F.
Bittencourt, Helio Radke
Fontanella, Vania Regina Camargo
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Licks, Renata
Licks, V.
Ourique, F.
Bittencourt, Helio Radke
Fontanella, Vania Regina Camargo
dc.subject.por.fl_str_mv Radiografia
Osteoporose
Odontologia
topic Radiografia
Osteoporose
Odontologia
Bone density
Osteoporosis
Dental radiography
dc.subject.eng.fl_str_mv Bone density
Osteoporosis
Dental radiography
description Objectives: This study aimed to develop and test a tool for low bone mass pre-screening by combining periapical radiographs with clinical risk factors. Methods: The study sample consisted of 60 post-menopausal women over 40 years of age who were referred for dental radiographs. These patients also had their bone mineral density measured at the lumbar spine and proximal femur using dual-energy X-ray absorptiometry. Radiographic density measurements and 14 morphological features were obtained from each dental radiograph using digital image processing software. The clinical variables considered were age and bone mass index. Classification and regression tree analysis (CART) was used to test the predictive power of clinical and radiographic risk factors for classifying individuals. Results: CART indicated that the most important variables for classifying patients were age, number of terminal points/periphery, periphery/trabecular area, radiographic density and bone mass index. Conclusion: A combination of clinical and radiographic factors can be used to identify individuals with low bone mineral density, with higher accuracy than any one of these factors taken individually.
publishDate 2010
dc.date.issued.fl_str_mv 2010
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dc.relation.ispartof.pt_BR.fl_str_mv Dentomaxillofacial radiology. Oxford, UK. Vol. 39, no. 4 (May 2010), p. 224-230
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