Literature DB >> 35748609

Quantitating Age-Related BMD Textural Variation from DXA Region-Free-Analysis: A Study of Hip Fracture Prediction in Three Cohorts.

Mohsen Farzi1,2,3, Jose M Pozo3, Eugene McCloskey1,2, Richard Eastell1,2, Nicholas C Harvey4,5, Alejandro F Frangi3, Jeremy Mark Wilkinson1,2.   

Abstract

The risk of osteoporotic fracture is inversely related to bone mineral density (BMD), but how spatial BMD pattern influences fracture risk remains incompletely understood. This study used a pixel-level spatiotemporal atlas of proximal femoral BMD in 13,338 white European women (age 20-97 years) to quantitate age-related texture variation in BMD maps and generate a "reference" map of bone aging. We introduce a new index, called Densitometric Bone Age (DBA), as the age at which an individual site-specific BMD map (the proximal femur is studied here) best matches the median aging trajectory at that site in terms of the root mean squared error (RMSE). The ability of DBA to predict incident hip fracture and hip fracture pattern over 5 years following baseline BMD was compared against conventional region-based BMD analysis in a subset of 11,899 women (age 45-97 years), for which follow-up fracture records exist. There were 208 subsequent incident hip fractures in the study populations (138 femoral necks [FNs], 52 trochanteric [TR], 18 sites unspecified). DBA had modestly better performance compared to the conventional FN-BMD, TR-BMD, and total hip (TOT)-BMD in identifying hip fractures measured as the area under the curve (AUC) using receiver operating characteristics (ROC) curve analysis by 2% (95% confidence interval [CI], -0.5% to 3.5%), 3% (95% CI, 1.0% to 4.0%), and 1% (95% CI, 0.4% to 1.6%), respectively. Compared to FN-BMD T-score, DBA improved the ROC-AUC for predicting TR fractures by ~5% (95% CI, 1.1% to 9.8%) with similar performance in identifying FN fractures. Compared to TR-BMD T-score, DBA improved the ROC-AUC for the prediction of FN fractures by ~3% (95% CI, 1.1% to 4.9%), with similar performance in identifying TR fractures. Our findings suggest that DBA may provide a spatially sensitive measure of proximal femoral fragility that is not captured by FN-BMD or TR-BMD alone.
© 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR). © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Entities:  

Keywords:  AGING; BMD; DXA; HIP FRACTURES; OSTEOPOROSIS

Mesh:

Year:  2022        PMID: 35748609      PMCID: PMC9541700          DOI: 10.1002/jbmr.4638

Source DB:  PubMed          Journal:  J Bone Miner Res        ISSN: 0884-0431            Impact factor:   6.390


  40 in total

1.  Computer-assisted bone age assessment: image preprocessing and epiphyseal/metaphyseal ROI extraction.

Authors:  E Pietka; A Gertych; S Pospiech; F Cao; H K Huang; V Gilsanz
Journal:  IEEE Trans Med Imaging       Date:  2001-08       Impact factor: 10.048

2.  Bone Radiomics Score Derived From DXA Hip Images Enhances Hip Fracture Prediction in Older Women.

Authors:  Namki Hong; Heajeong Park; Chang Oh Kim; Hyeon Chang Kim; Jin-Young Choi; Hwiyoung Kim; Yumie Rhee
Journal:  J Bone Miner Res       Date:  2021-05-24       Impact factor: 6.741

3.  Correlations between grey-level variations in 2D projection images (TBS) and 3D microarchitecture: applications in the study of human trabecular bone microarchitecture.

Authors:  Laurent Pothuaud; Pascal Carceller; Didier Hans
Journal:  Bone       Date:  2008-01-29       Impact factor: 4.398

4.  High-spatial-resolution bone densitometry with dual-energy X-ray absorptiometric region-free analysis.

Authors:  Richard M Morris; Lang Yang; Miguel A Martín-Fernández; Jose M Pozo; Alejandro F Frangi; J Mark Wilkinson
Journal:  Radiology       Date:  2014-09-15       Impact factor: 11.105

5.  The diagnosis of osteoporosis.

Authors:  J A Kanis; L J Melton; C Christiansen; C C Johnston; N Khaltaev
Journal:  J Bone Miner Res       Date:  1994-08       Impact factor: 6.741

6.  Does hip structural analysis confer additional benefit to routine BMD assessment in postmenopausal women with hip fracture? A study from a tertiary center in southern India.

Authors:  Johns T Johnson; Kripa Elizabeth Cherian; Nitin Kapoor; Felix K Jebasingh; Hesarghatta Shyamsunder Asha; Thomas Mathai; Manasseh Nithyananth; Anil Thomas Oommen; Alfred Job Daniel; Nihal Thomas; Thomas Vizhalil Paul
Journal:  Arch Osteoporos       Date:  2022-02-05       Impact factor: 2.617

7.  Femoral bone loss progresses with age: a longitudinal study in women over age 65.

Authors:  S L Greenspan; L A Maitland; E R Myers; M B Krasnow; T H Kido
Journal:  J Bone Miner Res       Date:  1994-12       Impact factor: 6.741

8.  Evaluation of a simplified hip structure analysis method for the prediction of incident hip fracture events.

Authors:  B C C Khoo; J R Lewis; K Brown; R L Prince
Journal:  Osteoporos Int       Date:  2015-08-18       Impact factor: 4.507

Review 9.  Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice.

Authors:  N C Harvey; C C Glüer; N Binkley; E V McCloskey; M-L Brandi; C Cooper; D Kendler; O Lamy; A Laslop; B M Camargos; J-Y Reginster; R Rizzoli; J A Kanis
Journal:  Bone       Date:  2015-05-16       Impact factor: 4.398

Review 10.  Trabecular bone score: a noninvasive analytical method based upon the DXA image.

Authors:  Barbara C Silva; William D Leslie; Heinrich Resch; Olivier Lamy; Olga Lesnyak; Neil Binkley; Eugene V McCloskey; John A Kanis; John P Bilezikian
Journal:  J Bone Miner Res       Date:  2014-03       Impact factor: 6.741

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