Literature DB >> 25683520

Random field assessment of inhomogeneous bone mineral density from DXA scans can enhance the differentiation between postmenopausal women with and without hip fractures.

Xuanliang Neil Dong1, Rajeshwar Pinninti2, Timothy Lowe3, Patricia Cussen4, Joyce E Ballard3, David Di Paolo5, Mukul Shirvaikar2.   

Abstract

Bone mineral density (BMD) measurements from Dual-energy X-ray Absorptiometry (DXA) alone cannot account for all factors associated with the risk of hip fractures. For example, the inhomogeneity of bone mineral density in the hip region also contributes to bone strength. In the stochastic assessment of bone inhomogeneity, the BMD map in the hip region is considered as a random field and stochastic predictors can be calculated by fitting a theoretical model onto the experimental variogram of the BMD map. The objective of this study was to compare the ability of bone mineral density and stochastic assessment of inhomogeneous distribution of bone mineral density in predicting hip fractures for postmenopausal women. DXA scans in the hip region were obtained from postmenopausal women with hip fractures (N=47, Age: 71.3±11.4 years) and without hip fractures (N=45, Age: 66.7±11.4 years). Comparison of BMD measurements and stochastic predictors in assessing bone fragility was based on the area under the receiver operating characteristic curves (AUC) from logistic regression analyses. Although stochastic predictors offered higher accuracy (AUC=0.675) in predicting the risk of hip fractures than BMD measurements (AUC=0.625), this difference was not statistically significant (p=0.548). Nevertheless, the combination of stochastic predictors and BMD measurements had significantly (p=0.039) higher prediction accuracy (AUC=0.748) than BMD measurements alone. This study demonstrates that stochastic assessment of bone mineral distribution from DXA scans can serve as a valuable tool in enhancing the prediction of hip fractures for postmenopausal women in addition to BMD measurements.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bone mineral density (BMD); DXA; Experimental variogram; Osteoporosis; Stochastic method

Mesh:

Year:  2015        PMID: 25683520      PMCID: PMC4380795          DOI: 10.1016/j.jbiomech.2015.01.030

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  39 in total

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Review 2.  Measuring the structural strength of bones with dual-energy X-ray absorptiometry: principles, technical limitations, and future possibilities.

Authors:  Thomas Beck
Journal:  Osteoporos Int       Date:  2003-08-29       Impact factor: 4.507

3.  Comparison of 3D finite element analysis derived stiffness and BMD to determine the failure load of the excised proximal femur.

Authors:  C M Langton; S Pisharody; J H Keyak
Journal:  Med Eng Phys       Date:  2009-02-20       Impact factor: 2.242

4.  Spine bone texture assessed by trabecular bone score (TBS) predicts osteoporotic fractures in men: the Manitoba Bone Density Program.

Authors:  W D Leslie; B Aubry-Rozier; L M Lix; S N Morin; S R Majumdar; D Hans
Journal:  Bone       Date:  2014-07-02       Impact factor: 4.398

5.  Random field assessment of nanoscopic inhomogeneity of bone.

Authors:  X Neil Dong; Qing Luo; Daniel M Sparkman; Harry R Millwater; Xiaodu Wang
Journal:  Bone       Date:  2010-09-15       Impact factor: 4.398

6.  A retrospective case-control study assessing the role of trabecular bone score in postmenopausal Caucasian women with osteopenia: analyzing the odds of vertebral fracture.

Authors:  Renaud Winzenrieth; Rémy Dufour; Laurent Pothuaud; Didier Hans
Journal:  Calcif Tissue Int       Date:  2009-12-09       Impact factor: 4.333

Review 7.  Osteoporosis prevention, diagnosis, and therapy.

Authors: 
Journal:  NIH Consens Statement       Date:  2000 Mar 27-29

8.  Prevention and management of osteoporosis.

Authors: 
Journal:  World Health Organ Tech Rep Ser       Date:  2003

9.  Texture analysis of X-ray radiographs is a more reliable descriptor of bone loss than mineral content in a rat model of localized disuse induced by the Clostridium botulinum toxin.

Authors:  D Chappard; A Chennebault; M Moreau; E Legrand; M Audran; M F Basle
Journal:  Bone       Date:  2001-01       Impact factor: 4.398

10.  A multicentre, retrospective case-control study assessing the role of trabecular bone score (TBS) in menopausal Caucasian women with low areal bone mineral density (BMDa): Analysing the odds of vertebral fracture.

Authors:  Bénédicte Rabier; Alain Héraud; Catherine Grand-Lenoir; Renaud Winzenrieth; Didier Hans
Journal:  Bone       Date:  2009-09-10       Impact factor: 4.398

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  5 in total

1.  Semivariogram Analysis of Bone Images Implemented on FPGA Architectures.

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2.  Variogram-based evaluations of DXA correlate with vertebral strength, but do not enhance the prediction compared to aBMD alone.

Authors:  Xuanliang Neil Dong; Yongtao Lu; Matthias Krause; Gerd Huber; Yan Chevalier; Huijie Leng; Ghislain Maquer
Journal:  J Biomech       Date:  2018-07-25       Impact factor: 2.712

3.  Hip Fracture Discrimination Based on Statistical Multi-parametric Modeling (SMPM).

Authors:  Julio Carballido-Gamio; Aihong Yu; Ling Wang; Yongbin Su; Andrew J Burghardt; Thomas F Lang; Xiaoguang Cheng
Journal:  Ann Biomed Eng       Date:  2019-05-31       Impact factor: 3.934

4.  Prevalent role of porosity and osteonal area over mineralization heterogeneity in the fracture toughness of human cortical bone.

Authors:  Mathilde Granke; Alexander J Makowski; Sasidhar Uppuganti; Jeffry S Nyman
Journal:  J Biomech       Date:  2016-06-15       Impact factor: 2.712

5.  Stochastic predictors from the DXA scans of human lumbar vertebrae are correlated with the microarchitecture parameters of trabecular bone.

Authors:  Xuanliang Neil Dong; Rajeshwar Pinninti; Amy Tvinnereim; Timothy Lowe; David Di Paolo; Mukul Shirvaikar
Journal:  J Biomech       Date:  2015-08-12       Impact factor: 2.712

  5 in total

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