Using Radon transform of standard radiographs of the hip to differentiate between post-menopausal women with and without fracture of the proximal femur
Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting t...
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Published in | Osteoporosis international Vol. 20; no. 2; pp. 323 - 333 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
London : Springer-Verlag
01.02.2009
Springer-Verlag Springer Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 0937-941X 1433-2965 1433-2965 |
DOI | 10.1007/s00198-008-0663-6 |
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Abstract | Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. Introduction The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). Methods The study comprised 50 post-menopausal women (78.6 ± 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. Results For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Conclusion Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. |
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AbstractList | Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. Introduction The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). Methods The study comprised 50 post-menopausal women (78.6 ± 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. Results For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Conclusion Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable.UNLABELLEDTexture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable.The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD).INTRODUCTIONThe aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD).The study comprised 50 post-menopausal women (78.6 +/- 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods.METHODSThe study comprised 50 post-menopausal women (78.6 +/- 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods.For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%.RESULTSFor correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%.Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture.CONCLUSIONIdentification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. Introduction: The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). Methods: The study comprised 50 post-menopausal women (78.6 plus or minus 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. Results: For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Conclusion: Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. Introduction The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). Methods The study comprised 50 post-menopausal women (78.6 ± 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. Results For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Conclusion Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). The study comprised 50 post-menopausal women (78.6 +/- 11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analysed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to identify patients with fracture of the proximal femur and may provide an alternative to measuring bone mineral density in predicting the fracture-risk in osteoporosis, especially where densitometry is regionally unavailable. The aim of this study is to introduce an algorithm for differentiation between patients with and without fracture of the hip using parameters based on the Radon transform (RT) and applied to standard radiographs of the proximal femur and to compare the results with bone mineral density (BMD). The study comprised 50 post-menopausal women (78.6±11.5 years of age), including 25 patients with hip fracture and 25 age-matched controls. We obtained lumbar and femoral BMD and standard femoral radiographs. In the radiographs we analyzed trabecular patterns of the hip in a region-of-interest of 57 x 29 mm using the RT. From the histogram-representation of the RT, we extracted several characteristic parameters. By ROC and discriminant-analysis, we assessed the statistical power of both methods. For correct differentiation between fracture and non-fracture cases by femoral BMD, area-under-the-curve (AUC) was 0.78; AUC for the RT-based parameters ranged from 0.73 to 0.8. By combination of densitometric and textural information in a multivariate model the fracture status of 84% of subjects was predicted correctly, identification of fracture cases rose to 88%. Identification of fracture patients by RT applied to femoral radiographs was feasible and seemed to have a discriminative potential comparable to that of standard densitometry. In the future, the new method may provide an alternative to DXA or in conjunction with conventional densitometry may enhance the detection of patients with elevated risk of hip fracture. [PUBLICATION ABSTRACT] |
Author | Körner, M Mutschler, W Lutz, J Boehm, H. F Pfeifer, K.-J Reiser, M |
Author_xml | – sequence: 1 fullname: Boehm, H. F – sequence: 2 fullname: Lutz, J – sequence: 3 fullname: Körner, M – sequence: 4 fullname: Mutschler, W – sequence: 5 fullname: Reiser, M – sequence: 6 fullname: Pfeifer, K.-J |
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CitedBy_id | crossref_primary_10_7763_IJCTE_2013_V5_760 crossref_primary_10_1007_s00330_012_2722_9 crossref_primary_10_1148_radiol_14131390 crossref_primary_10_1016_j_bone_2011_04_016 crossref_primary_10_1002_jbmr_1987 |
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Keywords | Radon transform In vivo Osteoporosis Radiographic texture analysis Fracture risk Proximal femur Human Proximal Femur Radiodiagnosis Radon Diseases of the osteoarticular system Rheumatology Exploration Fracture Trauma Texture Hip Radiography Risk factor Woman |
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Snippet | Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed... Summary Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed... Texture features based on the Radon transform were extracted from clinical radiographs of the hip in post-menopausal women. The novel algorithm allowed us to... |
SourceID | proquest pubmed pascalfrancis crossref springer fao |
SourceType | Aggregation Database Index Database Enrichment Source Publisher |
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SubjectTerms | Aged Aged, 80 and over Area Under Curve Biological and medical sciences Bone Density Case-Control Studies Diagnosis, Differential Discriminant Analysis Diseases of the osteoarticular system Endocrinology Female Femur Femur - diagnostic imaging Femur - physiopathology Fracture risk Fractures Fractures, Spontaneous Fractures, Spontaneous - diagnostic imaging Fractures, Spontaneous - physiopathology Hip Hip - diagnostic imaging Hip Fractures Hip Fractures - diagnostic imaging Hip Fractures - physiopathology Hip joint Humans In vivo Injuries of the limb. Injuries of the spine Legs Lumbar Vertebrae Lumbar Vertebrae - physiopathology Medical sciences Medicine Medicine & Public Health methods Older people Original Article Orthopedics Osteoporosis Osteoporosis. Osteomalacia. Paget disease physiopathology Proximal femur Radiographic texture analysis Radiography Radon transform Rheumatology Risk Assessment Risk Assessment - methods Risk factors Sensitivity and Specificity Traumas. Diseases due to physical agents Womens health |
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Title | Using Radon transform of standard radiographs of the hip to differentiate between post-menopausal women with and without fracture of the proximal femur |
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