Literature DB >> 22161807

Quantitative analysis of lumbar intervertebral disc abnormalities at 3.0 Tesla: value of T(2) texture features and geometric parameters.

Marius E Mayerhoefer1, David Stelzeneder, Werner Bachbauer, Goetz H Welsch, Tallal C Mamisch, Piotr Szczypinski, Michael Weber, Nicky H G M Peters, Julia Fruehwald-Pallamar, Stefan Puchner, Siegfried Trattnig.   

Abstract

T(2) relaxation time mapping provides information about the biochemical status of intervertebral discs. The present study aimed to determine whether texture features extracted from T(2) maps or geometric parameters are sensitive to the presence of abnormalities at the posterior aspect of lumbar intervertebral discs, i.e. bulging and herniation. Thirty-one patients (21 women and 10 men; age range 18-51 years) with low back pain were enrolled. MRI of the lumbar spine at 3.0 Tesla included morphological T(1) - and T(2) -weighted fast spin-echo sequences, and multi-echo spin-echo sequences that were used to construct T(2) maps. On morphological MRI, discs were visually graded into 'normal', 'bulging' or 'herniation'. On T(2) maps, texture analysis (based on the co-occurrence matrix and wavelet transform) and geometry analysis of the discs were performed. The three T(2) texture features and geometric parameters best-suited for distinguishing between normal discs and discs with bulging or herniation were determined using Fisher coefficients. Statistical analysis comprised ANCOVA and post hoc t-tests. Eighty-two discs were classified as 'normal', 49 as 'bulging' and 20 showed 'herniation.' The T(2) texture features Entropy and Difference Variance, and all three pre-selected geometric parameters differed significantly between normal and bulging, normal and herniated, and bulging and herniated discs (p < 0.05). These findings suggest that T(2) texture features and geometric parameters are sensitive to the presence of abnormalities at the posterior aspect of lumbar intervertebral discs, and may thus be useful as quantitative biomarkers that predict disease.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 22161807     DOI: 10.1002/nbm.1803

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  8 in total

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Authors:  Ruoliang Tang; Celal Gungor; Richard F Sesek; Kenneth Bo Foreman; Sean Gallagher; Gerard A Davis
Journal:  Eur Spine J       Date:  2016-02-12       Impact factor: 3.134

2.  Three-dimensional morphological and signal intensity features for detection of intervertebral disc degeneration from magnetic resonance images.

Authors:  A Neubert; J Fripp; C Engstrom; D Walker; M-A Weber; R Schwarz; S Crozier
Journal:  J Am Med Inform Assoc       Date:  2013-06-27       Impact factor: 4.497

3.  Radiomics: a new application from established techniques.

Authors:  Vishwa Parekh; Michael A Jacobs
Journal:  Expert Rev Precis Med Drug Dev       Date:  2016-03-31

4.  Quantitative Assessment of Variation in CT Parameters on Texture Features: Pilot Study Using a Nonanatomic Phantom.

Authors:  K Buch; B Li; M M Qureshi; H Kuno; S W Anderson; O Sakai
Journal:  AJNR Am J Neuroradiol       Date:  2017-03-24       Impact factor: 3.825

5.  Using Texture Analysis to Determine Human Papillomavirus Status of Oropharyngeal Squamous Cell Carcinomas on CT.

Authors:  K Buch; A Fujita; B Li; Y Kawashima; M M Qureshi; O Sakai
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6.  Quantifiable Imaging Biomarkers for Evaluation of the Posterior Cruciate Ligament Using 3-T Magnetic Resonance Imaging: A Feasibility Study.

Authors:  Katharine J Wilson; Rachel K Surowiec; Charles P Ho; Brian M Devitt; Jurgen Fripp; W Sean Smith; Ulrich J Spiegl; Grant J Dornan; Robert F LaPrade
Journal:  Orthop J Sports Med       Date:  2016-04-08

7.  The Radial Bulging and Axial Strains of Intervertebral Discs during Creep Obtained with the 3D-DIC System.

Authors:  Mengying Yang; Dingding Xiang; Song Wang; Weiqiang Liu
Journal:  Biomolecules       Date:  2022-08-10

8.  Quantitative variations in texture analysis features dependent on MRI scanning parameters: A phantom model.

Authors:  Karen Buch; Hirofumi Kuno; Muhammad M Qureshi; Baojun Li; Osamu Sakai
Journal:  J Appl Clin Med Phys       Date:  2018-10-27       Impact factor: 2.102

  8 in total

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