Literature DB >> 28732775

Statistical analysis of the inter-individual variations of the bone shape, volume fraction and fabric and their correlations in the proximal femur.

Elham Taghizadeh1, Vimal Chandran1, Mauricio Reyes1, Philippe Zysset1, Philippe Büchler2.   

Abstract

Including structural information of trabecular bone improves the prediction of bone strength and fracture risk. However, this information is available in clinical CT scans, only for peripheral bones. We hypothesized that a correlation exists between the shape of the bone, its volume fraction (BV/TV) and fabric, which could be characterized using statistical modeling. High-resolution peripheral computed tomography (HR-pQCT) images of 73 proximal femurs were used to build a combined statistical model of shape, BV/TV and fabric. The model was based on correspondence established by image registration and by morphing of a finite element mesh describing the spatial distribution of the bone properties. Results showed no correlation between the distribution of bone shape, BV/TV and fabric. Only the first mode of variation associated with density and orientation showed a strong relationship (R2>0.8). In addition, the model showed that the anisotropic information of the proximal femur does not vary significantly in a population of healthy, osteoporotic and osteopenic samples. In our dataset, the average anisotropy of the population was able to provide a close approximation of the patient-specific anisotropy. These results were confirmed by homogenized finite element (hFE) analyses, which showed that the biomechanical behavior of the proximal femur was not significantly different when the average anisotropic information of the population was used instead of patient-specific fabric extracted from HR-pQCT. Based on these findings, it can be assumed that the fabric information of the proximal femur follows a similar structure in an elderly population of healthy, osteopenic and osteoporotic proximal femurs.
Copyright © 2017 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Average fabric tensor; Bone properties; HR-pQCT; Proximal femur; Statistical model

Mesh:

Year:  2017        PMID: 28732775     DOI: 10.1016/j.bone.2017.07.012

Source DB:  PubMed          Journal:  Bone        ISSN: 1873-2763            Impact factor:   4.398


  4 in total

1.  A novel registration-based methodology for prediction of trabecular bone fabric from clinical QCT: A comprehensive analysis.

Authors:  Vimal Chandran; Mauricio Reyes; Philippe Zysset
Journal:  PLoS One       Date:  2017-11-27       Impact factor: 3.240

Review 2.  Statistical Shape and Appearance Models: Development Towards Improved Osteoporosis Care.

Authors:  Lorenzo Grassi; Sami P Väänänen; Hanna Isaksson
Journal:  Curr Osteoporos Rep       Date:  2021-11-13       Impact factor: 5.096

3.  Evaluation of Statistical Shape Modeling in Quantifying Femoral Morphologic Differences Between Symptomatic and Nonsymptomatic Hips in Patients with Unilateral Femoroacetabular Impingement Syndrome.

Authors:  Timothy C Keating; Natalie Leong; Edward C Beck; Benedict U Nwachukwu; Alejandro A Espinoza Orías; Xioaping Qian; Kang Li; Shane J Nho
Journal:  Arthrosc Sports Med Rehabil       Date:  2020-02-05

4.  A computational framework for canonical holistic morphometric analysis of trabecular bone.

Authors:  Dieter H Pahr; Alexander Synek; Sebastian Bachmann; Christopher J Dunmore; Matthew M Skinner
Journal:  Sci Rep       Date:  2022-03-25       Impact factor: 4.379

  4 in total

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