Literature DB >> 8309433

Application of fractal geometry techniques to the study of trabecular bone.

S Majumdar1, R S Weinstein, R R Prasad.   

Abstract

It is well recognized that both trabecular bone density and structure affect the overall bone quality and strength. In this study the aim is to quantify variations in the structural network of trabeculae using the concepts of fractal geometry. Fractal objects are objects that appear statistically similar over a range of scales. Typically fractals do not have smooth surfaces, but instead have rather complex structures with highly convoluted surfaces. Associated with every fractal is a characteristic dimension, called the fractal dimension. In this study, techniques of fractal analysis were used to characterize the trabecular bone matrix on digital images acquired by quantitative computed tomography (QCT) of dried excised human vertebral bodies (density ranging from 76-220 mg/cc) and photomicrography of transiliac crest biopsies. An automatic boundary tracking algorithm was used to identify the trabecular-bone and bone marrow interface, and a box-counting algorithm was used to estimate the fractal dimension of the trabecular boundary. Using this technique for fractal objects, if the boundary being analyzed is covered with boxes of differing sizes, epsilon, then the number of boxes N required to cover the surface increases indefinitely according to the relation N = epsilon-D, where D is the fractal dimension. Using this relationship in a preliminary study on five specimens we have found that the trabecular-bone boundary is fractal in nature. Using photomicrographs of iliac crest biopsies, it is found that the fractal dimension changes with the fractional trabecular bone content.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1993        PMID: 8309433     DOI: 10.1118/1.596948

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  14 in total

1.  Comparison of trabecular bone anisotropies based on fractal dimensions and mean intercept length determined by principal axes of inertia.

Authors:  Won-Jin Yi; Min-Suk Heo; Sam-Sun Lee; Soon-Chul Choi; Kyung-Hoe Huh
Journal:  Med Biol Eng Comput       Date:  2007-02-24       Impact factor: 2.602

2.  Fractal analysis of periapical bone from lossy compressed radiographs: a comparison of two lossy compression methods.

Authors:  B Güniz Baksi; Aleš Fidler
Journal:  J Digit Imaging       Date:  2011-12       Impact factor: 4.056

3.  Characterization of knee osteoarthritis-related changes in trabecular bone using texture parameters at various levels of spatial resolution-a simulation study.

Authors:  Torsten Lowitz; Oleg Museyko; Valerie Bousson; Willi A Kalender; Jean Denis Laredo; Klaus Engelke
Journal:  Bonekey Rep       Date:  2014-12-03

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

Authors:  Xuanliang Neil Dong; Rajeshwar Pinninti; Timothy Lowe; Patricia Cussen; Joyce E Ballard; David Di Paolo; Mukul Shirvaikar
Journal:  J Biomech       Date:  2015-02-02       Impact factor: 2.712

5.  Assessment of vertebral wedge strength using cancellous textural properties derived from digital tomosynthesis and density properties from dual energy X-ray absorptiometry and high resolution computed tomography.

Authors:  Yener N Yeni; Woong Kim; Daniel Oravec; Mary Nixon; George W Divine; Michael J Flynn
Journal:  J Biomech       Date:  2018-08-22       Impact factor: 2.712

6.  Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

Authors:  Virginia Byers Kraus; Sheng Feng; ShengChu Wang; Scott White; Maureen Ainslie; Alan Brett; Anthony Holmes; H Cecil Charles
Journal:  Arthritis Rheum       Date:  2009-12

7.  Assessment of bone fragility with clinical imaging modalities.

Authors:  Xn Dong; X Wang
Journal:  Hard Tissue       Date:  2013-02-15

8.  Radiographic trabecular 2D and 3D parameters of proximal femoral bone cores correlate with each other and with yield stress.

Authors:  D Steines; S-W Liew; C Arnaud; R Vargas-Voracek; A Nazarian; R Müller; B Snyder; P Hess; P Lang
Journal:  Osteoporos Int       Date:  2009-03-25       Impact factor: 4.507

9.  Fractures of the proximal femur: correlates of radiological evidence of osteoporosis.

Authors:  Salil H Patel; Kieran P Murphy
Journal:  Skeletal Radiol       Date:  2006-02-10       Impact factor: 2.199

10.  Biomechanical properties and microarchitecture parameters of trabecular bone are correlated with stochastic measures of 2D projection images.

Authors:  Xuanliang N Dong; Mukul Shirvaikar; Xiaodu Wang
Journal:  Bone       Date:  2013-06-10       Impact factor: 4.398

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