Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging

Amanda F. Mejia, Elizabeth M. Sweeney, Blake Dewey, Govind Nair, Pascal Sati, Colin Shea, Daniel S. Reich, Russell T. Shinohara

Research output: Contribution to journalArticlepeer-review

Abstract

Quantitative T1 maps estimate T1 relaxation times and can be used to assess diffuse tissue abnormalities within normal-appearing tissue. T1 maps are popular for studying the progression and treatment of multiple sclerosis (MS). However, their inclusion in standard imaging protocols remains limited due to the additional scanning time and expert calibration required and susceptibility to bias and noise. Here, we propose a new method of estimating T1 maps using four conventional MR images, which are intensity-normalized using cerebellar gray matter as a reference tissue and related to T1 using a smooth regression model. Using cross-validation, we generate statistical T1 maps for 61 subjects with MS. The statistical maps are less noisy than the acquired maps and show similar reproducibility. Tests of group differences in normal-appearing white matter across MS subtypes give similar results using both methods.

Original languageEnglish (US)
Pages (from-to)176-188
Number of pages13
JournalNeuroImage
Volume133
DOIs
StatePublished - Jun 1 2016

Keywords

  • Image synthesis
  • Magnetic resonance imaging
  • Multiple sclerosis
  • T1 relaxation time

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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