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Evaluation of low bone mass and prediction of fracture risk using metacarpal radiogrammetry method: a comparative study with DXA and X‐ray phantom.

Authors :
Ashok Kumar, Devaraj
Anburajan, Mariamicheal
Snekhalatha, Umapathy
Source :
International Journal of Rheumatic Diseases; Jul2018, Vol. 21 Issue 7, p1350-1371, 22p
Publication Year :
2018

Abstract

Abstract: Objectives: (i) To predict the future risk of osteoporotic fracture in women using a simple forearm radiograph. (ii) To assess osteoporosis in southern Indian women by using radiogrammetric technique in comparison with dual‐energy X‐ray absorptiometry (DXA) and X‐ray phantom study. Methods: The bone mineral density (BMD) of the right proximal femur by DXA and the X‐ray measurements were acquired from the right forearm. The combined cortical thickness at the second to fourth metacarpal region (M‐CCT), radius (R‐CCT) and ulna (U‐CCT) were derived in all the studied population. The aluminium phantom study was conducted by varying the X‐ray source to film distance at 100 cm and 150 cm, respectively. The feed forward back propagation neural network was used for classification of low bone mass group and normal. Results: The combined cortical thickness of M‐CCT, R‐CCT and U‐CCT of the total studied population was strongly correlated with DXA femur Th.BMD measurements (r = 0.77, r = 0.61 and r = 0.59 [P < 0.01]). The predicted future osteoporotic fracture risk for the low bone mass group, post‐menopausal women and old‐aged women population was found to be 92%, 62.8%, and 64.7%, respectively. The accuracy of neural network classifier for training set, testing set was found to be 97.5% and 87.5% in the studied population. Conclusion: The results suggested that M‐CCT and M‐CCT (%) at the second metacarpal region are useful in predicting the future risk of osteoporotic fracture in women. The aluminium phantom study with an X‐ray tube to film distance of 100 cm mimics an exact condition of forearm radiogrammetry. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17561841
Volume :
21
Issue :
7
Database :
Complementary Index
Journal :
International Journal of Rheumatic Diseases
Publication Type :
Academic Journal
Accession number :
130483879
Full Text :
https://doi.org/10.1111/1756-185X.13326