Literature DB >> 17520165

Analysis of trabecular bone structure with multidetector spiral computed tomography in a simulated soft-tissue environment.

Jan S Bauer1, Thomas M Link, Andrew Burghardt, Tobias D Henning, Dirk Mueller, Sharmila Majumdar, Sven Prevrhal.   

Abstract

We investigated the influence of soft tissue (ST) on image quality by high-resolution multidetector computed tomography (MDCT) scans and assessed the effect of surrounding ST on the quantification of trabecular bone structure. Eight bone cores obtained from human proximal femoral heads discarded during hip replacement surgery were scanned with micro-computed tomography (microCT) as well as with MDCT both without (w/o) and with (w) simulated surrounding ST, where a phantom imitated a human torso. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured in all scans. Apparent trabecular bone structure parameters were calculated and compared to similar parameters obtained in coregistered sections of the microCT scans. Residual errors were calculated as root-mean-square (RMS) errors relative to the microCT measurements. Compared to microCT results, trabecular structure parameters were overestimated by MDCT both w and w/o ST. SNR and CNR were significantly higher in the scans w/o ST. Significant correlations between microCT and MDCT results were found for bone fraction (r = 0.90 w/o ST, r = 0.84 w ST), trabecular number, and separation. RMS ranged from 10% to 15% for MDCT w/o ST and from 10% to 17% for MDCT w ST. Only bone fraction showed significantly different RMS and correlations for scans w/o vs. w ST (P < 0.05). This study showed that MDCT is able to visualize trabecular bone structure in an in vivo-like setting at skeletal sites within the torso such as the proximal femur. Even though ST scatter compromises image quality substantially, the major characteristics of the trabecular network can still be appreciated and quantified.

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Year:  2007        PMID: 17520165     DOI: 10.1007/s00223-007-9021-5

Source DB:  PubMed          Journal:  Calcif Tissue Int        ISSN: 0171-967X            Impact factor:   4.333


  17 in total

1.  Trabecular bone structure analysis in the osteoporotic spine using a clinical in vivo setup for 64-slice MDCT imaging: comparison to microCT imaging and microFE modeling.

Authors:  Ahi S Issever; Thomas M Link; Marie Kentenich; Patrik Rogalla; Karsten Schwieger; Markus B Huber; Andrew J Burghardt; Sharmila Majumdar; Gerd Diederichs
Journal:  J Bone Miner Res       Date:  2009-09       Impact factor: 6.741

2.  Trabecular bone structure parameters from 3D image processing of clinical multi-slice and cone-beam computed tomography data.

Authors:  Eva Klintström; Orjan Smedby; Rodrigo Moreno; Torkel B Brismar
Journal:  Skeletal Radiol       Date:  2013-11-24       Impact factor: 2.199

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.  Improving bone strength prediction in human proximal femur specimens through geometrical characterization of trabecular bone microarchitecture and support vector regression.

Authors:  Chien-Chun Yang; Mahesh B Nagarajan; Markus B Huber; Julio Carballido-Gamio; Jan S Bauer; Thomas Baum; Felix Eckstein; Eva Lochmüller; Sharmila Majumdar; Thomas M Link; Axel Wismüller
Journal:  J Electron Imaging       Date:  2014-01-09       Impact factor: 0.945

Review 5.  High-resolution imaging techniques for the assessment of osteoporosis.

Authors:  Roland Krug; Andrew J Burghardt; Sharmila Majumdar; Thomas M Link
Journal:  Radiol Clin North Am       Date:  2010-05       Impact factor: 2.303

6.  Assessment of trabecular bone structure using MDCT: comparison of 64- and 320-slice CT using HR-pQCT as the reference standard.

Authors:  Ahi S Issever; Thomas M Link; Marie Kentenich; Patrik Rogalla; Andrew J Burghardt; Galateia J Kazakia; Sharmila Majumdar; Gerd Diederichs
Journal:  Eur Radiol       Date:  2009-08-27       Impact factor: 5.315

7.  Trabecular bone structure analysis of the spine using clinical MDCT: can it predict vertebral bone strength?

Authors:  Thomas Baum; Martin Gräbeldinger; Christoph Räth; Eduardo Grande Garcia; Rainer Burgkart; Janina M Patsch; Ernst J Rummeny; Thomas M Link; Jan S Bauer
Journal:  J Bone Miner Metab       Date:  2013-04-20       Impact factor: 2.626

Review 8.  High-resolution computed tomography for clinical imaging of bone microarchitecture.

Authors:  Andrew J Burghardt; Thomas M Link; Sharmila Majumdar
Journal:  Clin Orthop Relat Res       Date:  2011-08       Impact factor: 4.176

9.  Vertebral bone marrow T2* mapping using chemical shift encoding-based water-fat separation in the quantitative analysis of lumbar osteoporosis and osteoporotic fractures.

Authors:  Yannik Leonhardt; Florian T Gassert; Georg Feuerriegel; Felix G Gassert; Sophia Kronthaler; Christof Boehm; Alexander Kufner; Stefan Ruschke; Thomas Baum; Benedikt J Schwaiger; Marcus R Makowski; Dimitrios C Karampinos; Alexandra S Gersing
Journal:  Quant Imaging Med Surg       Date:  2021-08

10.  Predicting Trabecular Bone Stiffness from Clinical Cone-Beam CT and HR-pQCT Data; an In Vitro Study Using Finite Element Analysis.

Authors:  Eva Klintström; Benjamin Klintström; Rodrigo Moreno; Torkel B Brismar; Dieter H Pahr; Örjan Smedby
Journal:  PLoS One       Date:  2016-08-11       Impact factor: 3.240

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