Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6023557 | NeuroImage | 2016 | 13 Pages |
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.
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Authors
Amanda F. Mejia, Elizabeth M. Sweeney, Blake Dewey, Govind Nair, Pascal Sati, Colin Shea, Daniel S. Reich, Russell T. Shinohara,