Literature DB >> 31196859

Quantification of DTI in the Pediatric Spinal Cord: Application to Clinical Evaluation in a Healthy Patient Population.

B B Reynolds1, S By1, Q R Weinberg1, A A Witt1, A T Newton2,3,1, H R Feiler1, B Ramkorun1, D B Clayton4, P Couture2, J E Martus5, M Adams4, J C Wellons2,6, S A Smith2,7,1,6, A Bhatia8,1.   

Abstract

BACKGROUND AND
PURPOSE: The purpose of the study is to characterize diffusion tensor imaging indices in the developing spinal cord, evaluating differences based on age and cord region. Describing the progression of DTI indices in the pediatric cord increases our understanding of spinal cord development.
MATERIALS AND METHODS: A retrospective analysis was performed on DTI acquired in 121 pediatric patients (mean, 8.6 years; range, 0.3-18.0 years) at Monroe Carell Jr. Children's Hospital at Vanderbilt from 2017 to 2018. Diffusion-weighted images (15 directions; b = 750 s/mm2; slice thickness, 5 mm; in-plane resolution, 1.0 × 1.0 mm2) were acquired on a 3T scanner in the cervicothoracic and/or thoracolumbar cord. Manual whole-cord segmentation was performed. Images were masked and further segmented into cervical, upper thoracic, thoracolumbar, and conus regions. Analyses of covariance were performed for each DTI-derived index to investigate how age affects diffusion across cord regions, and 95% confidence intervals were calculated across age for each derived index and region. Post hoc testing was performed to analyze regional differences.
RESULTS: Analyses of covariance revealed significant correlations of age with axial diffusivity, mean diffusivity, and fractional anisotropy (all, P < .001). There were also significant differences among cord regions for axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy (all, P < .001).
CONCLUSIONS: This research demonstrates that diffusion evolves in the pediatric spinal cord during development, dependent on both cord region and the diffusion index of interest. Future research could investigate how diffusion may be affected by common pediatric spinal pathologies.
© 2019 by American Journal of Neuroradiology.

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Year:  2019        PMID: 31196859      PMCID: PMC7048550          DOI: 10.3174/ajnr.A6104

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


  30 in total

1.  Normal brain development and aging: quantitative analysis at in vivo MR imaging in healthy volunteers.

Authors:  E Courchesne; H J Chisum; J Townsend; A Cowles; J Covington; B Egaas; M Harwood; S Hinds; G A Press
Journal:  Radiology       Date:  2000-09       Impact factor: 11.105

2.  Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection.

Authors:  Andreia V Faria; Jiangyang Zhang; Kenichi Oishi; Xin Li; Hangyi Jiang; Kazi Akhter; Laurent Hermoye; Seung-Koo Lee; Alexander Hoon; Elaine Stashinko; Michael I Miller; Peter C M van Zijl; Susumu Mori
Journal:  Neuroimage       Date:  2010-04-24       Impact factor: 6.556

3.  Diffusion tensor imaging: the normal evolution of ADC, RA, FA, and eigenvalues studied in multiple anatomical regions of the brain.

Authors:  Ulrike Löbel; Jan Sedlacik; Daniel Güllmar; Werner A Kaiser; Jürgen R Reichenbach; Hans-Joachim Mentzel
Journal:  Neuroradiology       Date:  2009-01-09       Impact factor: 2.804

4.  Tract-specific and age-related variations of the spinal cord microstructure: a multi-parametric MRI study using diffusion tensor imaging (DTI) and inhomogeneous magnetization transfer (ihMT).

Authors:  Manuel Taso; Olivier M Girard; Guillaume Duhamel; Arnaud Le Troter; Thorsten Feiweier; Maxime Guye; Jean-Philippe Ranjeva; Virginie Callot
Journal:  NMR Biomed       Date:  2016-04-21       Impact factor: 4.044

Review 5.  Diffusion tensor imaging for understanding brain development in early life.

Authors:  Anqi Qiu; Susumu Mori; Michael I Miller
Journal:  Annu Rev Psychol       Date:  2015-01-03       Impact factor: 24.137

Review 6.  A review of diffusion tensor magnetic resonance imaging computational methods and software tools.

Authors:  Khader M Hasan; Indika S Walimuni; Humaira Abid; Klaus R Hahn
Journal:  Comput Biol Med       Date:  2010-11-18       Impact factor: 4.589

Review 7.  Maturation of white matter in the human brain: a review of magnetic resonance studies.

Authors:  T Paus; D L Collins; A C Evans; G Leonard; B Pike; A Zijdenbos
Journal:  Brain Res Bull       Date:  2001-02       Impact factor: 4.077

Review 8.  Diffusion tensor imaging of normal brain development.

Authors:  Shoko Yoshida; Kenichi Oishi; Andreia V Faria; Susumu Mori
Journal:  Pediatr Radiol       Date:  2013-01-04

9.  Spinal cord grey matter segmentation challenge.

Authors:  Ferran Prados; John Ashburner; Claudia Blaiotta; Tom Brosch; Julio Carballido-Gamio; Manuel Jorge Cardoso; Benjamin N Conrad; Esha Datta; Gergely Dávid; Benjamin De Leener; Sara M Dupont; Patrick Freund; Claudia A M Gandini Wheeler-Kingshott; Francesco Grussu; Roland Henry; Bennett A Landman; Emil Ljungberg; Bailey Lyttle; Sebastien Ourselin; Nico Papinutto; Salvatore Saporito; Regina Schlaeger; Seth A Smith; Paul Summers; Roger Tam; Marios C Yiannakas; Alyssa Zhu; Julien Cohen-Adad
Journal:  Neuroimage       Date:  2017-03-07       Impact factor: 6.556

10.  Voxel-based analysis of grey and white matter degeneration in cervical spondylotic myelopathy.

Authors:  Patrick Grabher; Siawoosh Mohammadi; Aaron Trachsler; Susanne Friedl; Gergely David; Reto Sutter; Nikolaus Weiskopf; Alan J Thompson; Armin Curt; Patrick Freund
Journal:  Sci Rep       Date:  2016-04-20       Impact factor: 4.379

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  2 in total

1.  Atlas-Based Quantification of DTI Measures in a Typically Developing Pediatric Spinal Cord.

Authors:  S Shahrampour; B De Leener; M Alizadeh; D Middleton; L Krisa; A E Flanders; S H Faro; J Cohen-Adad; F B Mohamed
Journal:  AJNR Am J Neuroradiol       Date:  2021-07-29       Impact factor: 4.966

Review 2.  Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review.

Authors:  Irina S Buyanova; Marie Arsalidou
Journal:  Front Hum Neurosci       Date:  2021-07-06       Impact factor: 3.169

  2 in total

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