Statistical estimation of T1 relaxation times using conventional magnetic resonance imaging Academic Article uri icon

Overview

MeSH Major

  • Algorithms
  • Brain
  • Diffusion Tensor Imaging
  • Image Interpretation, Computer-Assisted
  • Models, Statistical
  • Multiple Sclerosis
  • White Matter

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.

publication date

  • June 2016

Research

keywords

  • Academic Article

Identity

Language

  • eng

PubMed Central ID

  • PMC4889526

Digital Object Identifier (DOI)

  • 10.1016/j.neuroimage.2015.12.037

PubMed ID

  • 26732403

Additional Document Info

start page

  • 176

end page

  • 188

volume

  • 133