Published July 2012 | Version v1
Journal article

Quantification of diffusion tensor imaging in normal white matter maturation of early childhood using an automated processing pipeline

  • 1. University of Malaya, Department of Biomedical Imaging, University Malaya Research Imaging Centre (UMRIC), Faculty of Medicine, Kuala Lumpur (Malaysia)
  • 2. University Malaya, Biomedical Imaging Department, Kuala Lumpur (Malaysia)
  • 3. University of Malaya, Department of Paediatrics, Faculty of Medicine, Kuala Lumpur (Malaysia)

Description

The degree and status of white matter myelination can be sensitively monitored using diffusion tensor imaging (DTI). This study looks at the measurement of fractional anistropy (FA) and mean diffusivity (MD) using an automated ROI with an existing DTI atlas. Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction. DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued. DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data. (orig.)

Availability note (English)

Available from: http://dx.doi.org/10.1007/s00330-012-2396-3

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology
Journal Volume
22
Journal Issue
7
Journal Page Range
p. 1413-1426
ISSN
0938-7994
CODEN
EURAE3