Literature DB >> 16547689

Volumetric quantitative computed tomography of the proximal femur: relationships linking geometric and densitometric variables to bone strength. Role for compact bone.

V Bousson1, A Le Bras, F Roqueplan, Y Kang, D Mitton, S Kolta, C Bergot, W Skalli, E Vicaut, W Kalender, K Engelke, J-D Laredo.   

Abstract

INTRODUCTION: In assessing cervical fractures of the proximal femur, this in vitro quantitative computed tomography (QCT) study had three objectives: to compare QCT to dual-energy X-ray absorptiometry (DXA) for predicting the failure load of the proximal femur, to compare the contributions of density and geometry to bone failure load, and to compare the contributions of cortical and trabecular bone to bone failure load. A novel three-dimensional (3D) analysis tool [medical image analysis framework (MIAF-Femur)] was used to analyze QCT scans.
METHODS: The proximal ends of 28 excised femurs were studied (1) using QCT to separately measure bone mineral density (BMD) and geometric variables of trabecular and cortical bone, (2) using mechanical tests to failure in a stance configuration, and (3) using DXA to measure BMD. The variables were described with mean, standard deviation, and range. Correlation matrix and multivariate linear models were computed.
RESULTS: Among correlations, cortical thicknesses of the femoral neck were significantly correlated with femoral failure load, especially of the inferoanterior quadrant (r2=0.41; p<0.001), as was cortical volume at the "extended neck" (r2=0.41; p<0.001). Femoral failure load variance was best explained by a combination of QCT variables. Combining densitometric and geometric variables measured by QCT explained 76% of femoral failure load variance compared with 69% with the DXA model. Geometric variables (measured by QCT) explained 43% of femoral failure load variance compared with 72% for densitometric variables (measured by QCT). A model including only trabecular variables explained 52% of femoral failure load variance compared with 59% for a model including only cortical variables.
CONCLUSION: The QCT-MIAF reported here provides analysis of both geometric and densitometric variables characterizing cortical and trabecular bone. Confirmation of our results in an independent sample would suggest that QCT may better explain failure load variance for cervical fracture than the gold standard DXA-provided BMD.

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Year:  2006        PMID: 16547689     DOI: 10.1007/s00198-006-0074-5

Source DB:  PubMed          Journal:  Osteoporos Int        ISSN: 0937-941X            Impact factor:   4.507


  34 in total

1.  Fracture risk: a role for compact bone.

Authors:  R B Mazess
Journal:  Calcif Tissue Int       Date:  1990-10       Impact factor: 4.333

2.  Spinal bone mineral assessment in postmenopausal women: a comparison between dual X-ray absorptiometry and quantitative computed tomography.

Authors:  W Yu; C C Glüer; S Grampp; M Jergas; T Fuerst; C Y Wu; Y Lu; B Fan; H K Genant
Journal:  Osteoporos Int       Date:  1995       Impact factor: 4.507

3.  An anatomic coordinate system of the femoral neck for highly reproducible BMD measurements using 3D QCT.

Authors:  Yan Kang; Klaus Engelke; Christina Fuchs; Willi A Kalender
Journal:  Comput Med Imaging Graph       Date:  2005-09-06       Impact factor: 4.790

4.  A comparison of spinal quantitative computed tomography with dual energy X-ray absorptiometry in European women with vertebral and nonvertebral fractures.

Authors:  C Bergot; A M Laval-Jeantet; K Hutchinson; I Dautraix; F Caulin; H K Genant
Journal:  Calcif Tissue Int       Date:  2001-02       Impact factor: 4.333

5.  Evaluation of cortical bone by computed tomography.

Authors:  T N Hangartner; V Gilsanz
Journal:  J Bone Miner Res       Date:  1996-10       Impact factor: 6.741

6.  Mild versus definite osteoporosis: comparison of bone densitometry techniques using different statistical models.

Authors:  A F Heuck; J Block; C C Glueer; P Steiger; H K Genant
Journal:  J Bone Miner Res       Date:  1989-12       Impact factor: 6.741

7.  Predicting proximal femoral strength using structural engineering models.

Authors:  Joyce H Keyak; Tadashi S Kaneko; Jamshid Tehranzadeh; Harry B Skinner
Journal:  Clin Orthop Relat Res       Date:  2005-08       Impact factor: 4.176

8.  Relationships between femoral fracture loads for two load configurations.

Authors:  J H Keyak
Journal:  J Biomech       Date:  2000-04       Impact factor: 2.712

9.  Assessment of the strength of proximal femur in vitro: relationship to femoral bone mineral density and femoral geometry.

Authors:  X G Cheng; G Lowet; S Boonen; P H Nicholson; P Brys; J Nijs; J Dequeker
Journal:  Bone       Date:  1997-03       Impact factor: 4.398

10.  Cortical aging differences and fracture implications for the human femoral neck.

Authors:  T M Boyce; R D Bloebaum
Journal:  Bone       Date:  1993 Sep-Oct       Impact factor: 4.398

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  65 in total

1.  Assessment of technical and biological parameters of volumetric quantitative computed tomography of the foot: a phantom study.

Authors:  K E Smith; B R Whiting; G G Reiker; P K Commean; D R Sinacore; F W Prior
Journal:  Osteoporos Int       Date:  2011-12-07       Impact factor: 4.507

Review 2.  Functional interactions among morphologic and tissue quality traits define bone quality.

Authors:  Karl J Jepsen
Journal:  Clin Orthop Relat Res       Date:  2011-08       Impact factor: 4.176

3.  Finite element analysis applied to 3-T MR imaging of proximal femur microarchitecture: lower bone strength in patients with fragility fractures compared with control subjects.

Authors:  Gregory Chang; Stephen Honig; Ryan Brown; Cem M Deniz; Kenneth A Egol; James S Babb; Ravinder R Regatte; Chamith S Rajapakse
Journal:  Radiology       Date:  2014-04-02       Impact factor: 11.105

Review 4.  Bone Imaging and Fracture Risk after Spinal Cord Injury.

Authors:  W Brent Edwards; Thomas J Schnitzer
Journal:  Curr Osteoporos Rep       Date:  2015-10       Impact factor: 5.096

5.  Femoral neck cortical geometry measured with magnetic resonance imaging is associated with proximal femur strength.

Authors:  S L Manske; T Liu-Ambrose; P M de Bakker; D Liu; S Kontulainen; P Guy; T R Oxland; H A McKay
Journal:  Osteoporos Int       Date:  2006-07-18       Impact factor: 4.507

6.  Considerations for development of surrogate endpoints for antifracture efficacy of new treatments in osteoporosis: a perspective.

Authors:  Mary L Bouxsein; Pierre D Delmas
Journal:  J Bone Miner Res       Date:  2008-08       Impact factor: 6.741

7.  Cortical and trabecular bone in the femoral neck both contribute to proximal femur failure load prediction.

Authors:  S L Manske; T Liu-Ambrose; D M L Cooper; S Kontulainen; P Guy; B B Forster; H A McKay
Journal:  Osteoporos Int       Date:  2008-07-26       Impact factor: 4.507

8.  Parametric subject-specific model for in vivo 3D reconstruction using bi-planar X-rays: application to the upper femoral extremity.

Authors:  A Baudoin; W Skalli; J A de Guise; D Mitton
Journal:  Med Biol Eng Comput       Date:  2008-06-10       Impact factor: 2.602

Review 9.  Skeletal changes during and after spaceflight.

Authors:  Laurence Vico; Alan Hargens
Journal:  Nat Rev Rheumatol       Date:  2018-03-21       Impact factor: 20.543

Review 10.  Bone quality: the determinants of bone strength and fragility.

Authors:  Hélder Fonseca; Daniel Moreira-Gonçalves; Hans-Joachim Appell Coriolano; José Alberto Duarte
Journal:  Sports Med       Date:  2014-01       Impact factor: 11.136

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