Atlas-based versus individual-based fiber tracking of the corpus callosum in patients with multiple sclerosis: Reliability and clinical correlations

Maria Marcella Laganà, Antonia Ceccarelli, Maria Giulia Preti, Chiara Venturelli, Maria Pia Sormani, Rosella Cavarretta, Giuseppe Baselli, Pietro Cecconi, Domenico Caputo, Marco Rovaris

Research output: Contribution to journalArticle

Abstract

Background And Purpose: In multiple sclerosis (MS), the presence of lesions and normal-appearing white matter damage may affect the reliability of diffusion tensor (DT) magnetic resonance imaging (MRI)-based tractography. We compared the performance of an individual-based method for corpus callosum (CC) fiber tracking in MS with those of two atlas-based methods. Methods: Brain DT MRI scans were acquired from 35 patients with MS and 18 age-matched healthy volunteers (HV). DT-derived metrics from the CC-the mean diffusivity (MD) and fractional anisotropy (FA)-were calculated using an individual-based and two atlas-based methods with different types of subject registration (linear and nonlinear) to a CC atlas. Customized termination criteria were applied to stop the tracking algorithm when using the individual-based method. Results: All the methods were able to distinguish between MS patients and HV. Using the individual-based method, stronger relationships were found between CC DT-derived metrics and the subjects' clinical condition. Conclusion: CC DT tractography using an individual-based method is more sensitive than the atlas-based ones to tract-specific alterations related to MS disability. An atlas-based method with nonlinear registration can be a valid alternative when an automated postprocessing is warranted, such as in the case of high volumes of data.

Original languageEnglish
Pages (from-to)355-364
Number of pages10
JournalJournal of Neuroimaging
Volume22
Issue number4
DOIs
Publication statusPublished - Oct 2012

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Keywords

  • Corpus callosum
  • Diffusion tensor MRI
  • Multiple sclerosis
  • Tractography

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology

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