Literature DB >> 21803681

Reconstructing the 3D shape and bone mineral density distribution of the proximal femur from dual-energy X-ray absorptiometry.

Tristan Whitmarsh1, Ludovic Humbert, Mathieu De Craene, Luis M Del Rio Barquero, Alejandro F Frangi.   

Abstract

The accurate diagnosis of osteoporosis has gained increasing importance due to the aging of our society. Areal bone mineral density (BMD) measured by dual-energy X-ray absorptiometry (DXA) is an established criterion in the diagnosis of osteoporosis. This measure, however, is limited by its two-dimensionality. This work presents a method to reconstruct both the 3D bone shape and 3D BMD distribution of the proximal femur from a single DXA image used in clinical routine. A statistical model of the combined shape and BMD distribution is presented, together with a method for its construction from a set of quantitative computed tomography (QCT) scans. A reconstruction is acquired in an intensity based 3D-2D registration process whereby an instance of the model is found that maximizes the similarity between its projection and the DXA image. Reconstruction experiments were performed on the DXA images of 30 subjects, with a model constructed from a database of QCT scans of 85 subjects. The accuracy was evaluated by comparing the reconstructions with the same subject QCT scans. The method presented here can potentially improve the diagnosis of osteoporosis and fracture risk assessment from the low radiation dose and low cost DXA devices currently used in clinical routine.

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Year:  2011        PMID: 21803681     DOI: 10.1109/TMI.2011.2163074

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  7 in total

1.  Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy.

Authors:  Nora Baka; Bart L Kaptein; J Erik Giphart; Marius Staring; Marleen de Bruijne; Boudewijn P F Lelieveldt; Edward Valstar
Journal:  J Biomech       Date:  2013-10-09       Impact factor: 2.712

2.  Adding liver R2* quantification to proton density fat fraction MRI of vertebral bone marrow improves the prediction of osteoporosis.

Authors:  Feng Lu; Yan-Jun Zhao; Jian-Ming Ni; Yu Jiang; Fang-Ming Chen; Zhong-Juan Wang; Zhui-Yang Zhang
Journal:  Eur Radiol       Date:  2022-05-25       Impact factor: 7.034

3.  Perspectives on the non-invasive evaluation of femoral strength in the assessment of hip fracture risk.

Authors:  M L Bouxsein; P Zysset; C C Glüer; M McClung; E Biver; D D Pierroz; S L Ferrari
Journal:  Osteoporos Int       Date:  2020-01-03       Impact factor: 4.507

4.  Focal osteoporosis defects play a key role in hip fracture.

Authors:  Kenneth E S Poole; Linda Skingle; Andrew H Gee; Thomas D Turmezei; Fjola Johannesdottir; Karen Blesic; Collette Rose; Madhavi Vindlacheruvu; Simon Donell; Jan Vaculik; Pavel Dungl; Martin Horak; Jan J Stepan; Jonathan Reeve; Graham M Treece
Journal:  Bone       Date:  2016-10-21       Impact factor: 4.398

5.  Prediction of femoral strength using 3D finite element models reconstructed from DXA images: validation against experiments.

Authors:  Lorenzo Grassi; Sami P Väänänen; Matti Ristinmaa; Jukka S Jurvelin; Hanna Isaksson
Journal:  Biomech Model Mechanobiol       Date:  2016-12-21

Review 6.  Statistical shape and appearance models in osteoporosis.

Authors:  Isaac Castro-Mateos; Jose M Pozo; Timothy F Cootes; J Mark Wilkinson; Richard Eastell; Alejandro F Frangi
Journal:  Curr Osteoporos Rep       Date:  2014-06       Impact factor: 5.096

7.  Prediction of incident hip fracture with the estimated femoral strength by finite element analysis of DXA Scans in the study of osteoporotic fractures.

Authors:  Lang Yang; Lisa Palermo; Dennis M Black; Richard Eastell
Journal:  J Bone Miner Res       Date:  2014-12       Impact factor: 6.741

  7 in total

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