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...

Full description

Saved in:
Bibliographic Details
Published inOsteoporosis international Vol. 20; no. 2; pp. 323 - 333
Main Authors Boehm, H. F, Lutz, J, Körner, M, Mutschler, W, Reiser, M, Pfeifer, K.-J
Format Journal Article
LanguageEnglish
Published London London : Springer-Verlag 01.02.2009
Springer-Verlag
Springer
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN0937-941X
1433-2965
1433-2965
DOI10.1007/s00198-008-0663-6

Cover

More Information
Summary: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.
Bibliography:http://dx.doi.org/10.1007/s00198-008-0663-6
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0937-941X
1433-2965
1433-2965
DOI:10.1007/s00198-008-0663-6