Quantitative MR imaging of two-pool magnetization transfer model parameters in myelin mutant shaking pup

Alexey Samsonov, Andrew L. Alexander, Pouria Mossahebi, Yu Chien Wu, Ian D. Duncan, Aaron S. Field

Research output: Contribution to journalArticle

41 Scopus citations


Magnetization transfer (MT) imaging quantitatively assesses cerebral white matter disease through its sensitivity to macromolecule-bound protons including those associated with myelin proteins and lipid bilayers. However, traditional MT contrast measured by the MT ratio (MTR) lacks pathologic specificity as demyelination, axon loss, inflammation and edema all impact MTR, directly and/or indirectly through multiple covariances among imaging parameters (particularly MTR with T1) and tissue features (e.g. axon loss with demyelination). In this study, more complex modeling of MT phenomena ("quantitative" MT or qMT) was applied to a less complex disease model (the myelin mutant shaking [sh] pup, featuring hypomyelination but neither inflammation nor axon loss) in order to eliminate the covariances on both sides of the MR-pathology "equation" and characterize these important relationships free from the usual confounds. qMT measurements were acquired longitudinally in 6 sh pups and 4 age-matched controls ranging from 3 to 21months of age and compared with histology. The qMT parameter, bound pool fraction (f), was the most distinctive between diseased and control animals; both f and longitudinal relaxation rate R1 tracked myelination with normal aging, whereas MTR did not-presumably owing to counterbalancing MT and R1 effects. qMT imaging provides a more accurate and potentially more specific non-invasive tissue characterization.

Original languageEnglish (US)
Pages (from-to)1390-1398
Number of pages9
Issue number3
StatePublished - Sep 1 2012
Externally publishedYes


  • Animal models
  • Cross-relaxation imaging
  • Myelin
  • Quantitative magnetization transfer
  • Relaxometry
  • White matter

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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