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Title

Retrospective Quantitative T1 Imaging to Examine Characteristics of Multiple Sclerosis Lesions

Creator

Young, Griffin James

Date

2024

Description

Quantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1...
Show moreQuantitative MRI plays an essential role in assessing tissue abnormality and diseaseprogression in multiple sclerosis (MS). Specifically, T1 relaxometry is gaining popularity as elevated T1 values have been shown to correlate with increased inflammation, demyelination, and gliosis. The predominant issue is that relaxometry requires parametric mapping through advanced imaging techniques not commonly included in standard clinical protocols. This leaves an information gap in large clinical datasets from which quantitative mapping could have been performed. We introduce T1-REQUIRE, a retrospective T1 mapping method that approximates T1 values from a single T1-weighted MR image. This method has already been shown to be accurate within 10% of a clinically available reference standard in healthy controls but will be further validated in MS cohorts. We also further aim to determine T1-REQUIRE’s statistical significance as a unique biomarker for the assessment of MS lesions as they relate to clinical disability and disease burden. A 14-subject comparison between T1-REQUIRE maps derived from 3D T1 weighted turbo field echoes (3D T1w TFE) and an inversion-recovery fast field echo (IRFFE) revealed a whole-brain voxel-wise Pearson’s correlation of r = 0.89 (p < 0.001) and mean bias of 3.99%. In MS white matter lesions, r = 0.81, R2 = 0.65 (p < 0.001, N = 159), bias = 10.07%, and in normal appearing white matter (NAWM), r = 0.82, R 2 = 0.67 (p < 0.001), bias = 9.48%. Mean lesional T1-REQUIRE and MTR correlated significantly (r = -0.68, p < 0.001, N = 587) similar to previously published literature. Median lesional MTR correlated significantly with EDSS (rho = -0.34, p = 0.037), and lesional T1-REQUIRE exhibited xiii significant correlations with global brain tissue atrophy as measured by brain parenchymal fraction (BPF) (r = -0.41, p = 0.010, N = 38). Multivariate linear regressions between T1- REQUIRE NAWM provided meaningful statistical relationships with EDSS (β = 0.03, p = 0.027, N = 38), as well as did mean MTR values in the Thalamus (β = -0.27, p = 0.037, N = 38). A new spoiled gradient echo variation of T1-REQUIRE was assessed as a proof of concept in a small 5-subject MS cohort compared with IR-FFE T1 maps, with a whole brain voxel-wise correlation of r = 0.88, R2 = 0.77 (p < 0.001), and Bias = 0.19%. Lesional T1 comparisons reached a correlation of r = 0.75, R2 = 0.56 (p < 0.001, N = 42), and Bias = 10.81%. The significance of these findings means that there is the potential to provide supplementary quantitative information in clinical datasets where quantitative protocols were not implemented. Large MS data repositories previously only containing structural T1 weighted images now may be used in big data relaxometric studies with the potential to lead to new findings in newly uncovered datasets. Furthermore, T1-REQUIRE has the potential for immediate use in clinics where standard T1 mapping sequences aren’t able to be readily implemented.
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