Literature DB >> 15956535

MR diffusion tensor imaging and fiber tracking in spinal cord compression.

David Facon1, Augustin Ozanne, Pierre Fillard, Jean-François Lepeintre, Caroline Tournoux-Facon, Denis Ducreux.   

Abstract

BACKGROUND AND
PURPOSE: Spinal cord damage can result in major functional disability. Alteration of the spinal cord structural integrity can be assessed by using diffusion tensor imaging methods. Our objective is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), fractional anisotropy (FA), and fiber tracking in both acute and slowly progressive spinal cord compressions.
METHODS: Fifteen patients with clinical symptoms of acute (n = 2) or slowly progressive (n = 13) spinal cord compression and 11 healthy volunteers were prospectively selected. We performed T2-weighted fast spin echo (FSE) and diffusion tensor imaging by using a 1.5-T MR scanner. ADC and FA maps were computed. Regions of interest were placed at the cervical, upper and lower thoracic cord levels for the healthy subjects and on the area with abnormal T2-weighted signal intensity in the patients with cord compression. In three patients, we used fiber tracking to locate the areas of cord compression precisely. Data were analyzed by using a mixed model. The sensitivity (SE) and specificity (sp) of imaging (T2, ADC, and FA maps) in the detection of spinal cord abnormality were statistically evaluated.
RESULTS: For the healthy subjects, averaged ADC values ranged from 0.96 10(-3) mm(2)/s to 1.05 10(-3) mm(2)/s and averaged FA values ranged from 0.745 to 0.751. Ten patients had decreased FA (0.67 +/- 0.087), and one had increased FA values (0.831); only two patients had increased ADC values (1.03 +/- 0.177). There was a statistically significant difference in the FA values between volunteers and patients (P = .012). FA had a much higher sensitivity (SE = 73.3%) and specificity (sp = 100%) in spinal cord abnormalities detection compared with T2-weighted FSE imaging (se = 46.7%, sp = 100%) and ADC (SE = 13.4%, sp = 80%).
CONCLUSIONS: FA has the highest sensitivity and specificity in the detection of acute spinal cord abnormalities. Spinal cord fiber tracking is a useful tool to focus measurements on the compressed spinal cord.

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Year:  2005        PMID: 15956535      PMCID: PMC8149058     

Source DB:  PubMed          Journal:  AJNR Am J Neuroradiol        ISSN: 0195-6108            Impact factor:   3.825


  32 in total

1.  A geometric analysis of diffusion tensor measurements of the human brain.

Authors:  A L Alexander; K Hasan; G Kindlmann; D L Parker; J S Tsuruda
Journal:  Magn Reson Med       Date:  2000-08       Impact factor: 4.668

Review 2.  Processing and visualization for diffusion tensor MRI.

Authors:  C-F Westin; S E Maier; H Mamata; A Nabavi; F A Jolesz; R Kikinis
Journal:  Med Image Anal       Date:  2002-06       Impact factor: 8.545

3.  A framework for callosal fiber distribution analysis.

Authors:  Dongrong Xu; Susumu Mori; Meiyappan Solaiyappan; Peter C M van Zijl; Christos Davatzikos
Journal:  Neuroimage       Date:  2002-11       Impact factor: 6.556

4.  Sensitivity-encoded diffusion tensor MR imaging of the cervical cord.

Authors:  Mara Cercignani; Mark A Horsfield; Federica Agosta; Massimo Filippi
Journal:  AJNR Am J Neuroradiol       Date:  2003 Jun-Jul       Impact factor: 3.825

5.  Rapid automated algorithm for aligning and reslicing PET images.

Authors:  R P Woods; S R Cherry; J C Mazziotta
Journal:  J Comput Assist Tomogr       Date:  1992 Jul-Aug       Impact factor: 1.826

6.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI.

Authors:  P J Basser; C Pierpaoli
Journal:  J Magn Reson B       Date:  1996-06

7.  Automated image registration: I. General methods and intrasubject, intramodality validation.

Authors:  R P Woods; S T Grafton; C J Holmes; S R Cherry; J C Mazziotta
Journal:  J Comput Assist Tomogr       Date:  1998 Jan-Feb       Impact factor: 1.826

8.  Automated image registration: II. Intersubject validation of linear and nonlinear models.

Authors:  R P Woods; S T Grafton; J D Watson; N L Sicotte; J C Mazziotta
Journal:  J Comput Assist Tomogr       Date:  1998 Jan-Feb       Impact factor: 1.826

9.  Toward a quantitative assessment of diffusion anisotropy.

Authors:  C Pierpaoli; P J Basser
Journal:  Magn Reson Med       Date:  1996-12       Impact factor: 4.668

10.  Diffusion-weighted MR imaging with apparent diffusion coefficient and apparent diffusion tensor maps in cervical spondylotic myelopathy.

Authors:  Ayhan Demir; Mario Ries; Crit T W Moonen; Jean-Marc Vital; Joël Dehais; Pierre Arne; Jean-Marie Caillé; Vincent Dousset
Journal:  Radiology       Date:  2003-10       Impact factor: 11.105

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  88 in total

1.  Diffusion tensor imaging and fibre tracking in cervical spondylotic myelopathy.

Authors:  Jean-François Budzik; Vincent Balbi; Vianney Le Thuc; Alain Duhamel; Richard Assaker; Anne Cotten
Journal:  Eur Radiol       Date:  2010-08-20       Impact factor: 5.315

2.  Application of diffusion tensor imaging for the diagnosis of segmental level of dysfunction in cervical spondylotic myelopathy.

Authors:  Y Suetomi; T Kanchiku; S Nishijima; Y Imajo; H Suzuki; Y Yoshida; N Nishida; T Taguchi
Journal:  Spinal Cord       Date:  2015-10-27       Impact factor: 2.772

3.  Magnetic resonance diffusion tensor imaging and fiber-tracking diffusion tensor tractography in the management of spinal astrocytomas.

Authors:  Alessandro Landi; Valeria Palmarini; Alessandro D'Elia; Nicola Marotta; Maurizio Salvati; Antonio Santoro; Roberto Delfini
Journal:  World J Clin Cases       Date:  2016-01-16       Impact factor: 1.337

4.  Diffusion tensor imaging and fiber tractography in cervical compressive myelopathy: preliminary results.

Authors:  Joon Woo Lee; Jae Hyoung Kim; Jong Bin Park; Kun Woo Park; Jin S Yeom; Guen Young Lee; Heung Sik Kang
Journal:  Skeletal Radiol       Date:  2011-04-15       Impact factor: 2.199

5.  In vivo tracing of neural tracts in the intact and injured spinal cord of marmosets by diffusion tensor tractography.

Authors:  Kanehiro Fujiyoshi; Masayuki Yamada; Masaya Nakamura; Junichi Yamane; Hiroyuki Katoh; Kazuya Kitamura; Kenji Kawai; Seiji Okada; Suketaka Momoshima; Yoshiaki Toyama; Hideyuki Okano
Journal:  J Neurosci       Date:  2007-10-31       Impact factor: 6.167

6.  Comparison between diffusion tensor imaging and conventional MR imaging sequences in the detection of spinal cord abnormalities.

Authors:  Alexis Lacout; Stephen Binsse; Mostafa El-Hajjam
Journal:  AJNR Am J Neuroradiol       Date:  2007-05       Impact factor: 3.825

Review 7.  Advanced MRI strategies for assessing spinal cord injury.

Authors:  Seth A Smith; James J Pekar; Peter C M van Zijl
Journal:  Handb Clin Neurol       Date:  2012

8.  Diffusion tensor imaging at 3 hours after traumatic spinal cord injury predicts long-term locomotor recovery.

Authors:  Joong H Kim; David N Loy; Qing Wang; Matthew D Budde; Robert E Schmidt; Kathryn Trinkaus; Sheng-Kwei Song
Journal:  J Neurotrauma       Date:  2010-03       Impact factor: 5.269

9.  Quantification of diffusivities of the human cervical spinal cord using a 2D single-shot interleaved multisection inner volume diffusion-weighted echo-planar imaging technique.

Authors:  T H Kim; L Zollinger; X F Shi; S E Kim; J Rose; A A Patel; E K Jeong
Journal:  AJNR Am J Neuroradiol       Date:  2009-12-17       Impact factor: 3.825

Review 10.  Imaging techniques in spinal cord injury.

Authors:  Benjamin M Ellingson; Noriko Salamon; Langston T Holly
Journal:  World Neurosurg       Date:  2012-12-12       Impact factor: 2.104

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