New rapid, accurate T2 quantification detects pathology in normal-appearing brain regions of relapsing-remitting MS patients

Quantitative T2 mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T2 changes in normal-appearing brain regions of subjects with RRMS (N=27) compared to...

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Published inNeuroImage clinical Vol. 14; no. C; pp. 363 - 370
Main Authors Shepherd, Timothy M., Kirov, Ivan I., Charlson, Erik, Bruno, Mary, Babb, James, Sodickson, Daniel K., Ben-Eliezer, Noam
Format Journal Article
LanguageEnglish
Published Elsevier Inc 2017
Elsevier
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ISSN2213-1582
2213-1582
DOI10.1016/j.nicl.2017.01.029

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Summary:Quantitative T2 mapping may provide an objective biomarker for occult nervous tissue pathology in relapsing-remitting multiple sclerosis (RRMS). We applied a novel echo modulation curve (EMC) algorithm to identify T2 changes in normal-appearing brain regions of subjects with RRMS (N=27) compared to age-matched controls (N=38). The EMC algorithm uses Bloch simulations to model T2 decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T2 values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation. Compared to conventional exponential T2 modeling, EMC fitting provided more accurate estimations of T2 with less variance across scans, MRI systems, and healthy individuals. Thalamic T2 was increased 8.5% in RRMS subjects (p<0.001) and could be used to discriminate RRMS from healthy controls well (AUC=0.913). Manual segmentation detected both statistically significant increases (corpus callosum & temporal stem) and decreases (posterior limb internal capsule) in T2 associated with RRMS diagnosis (all p<0.05). In healthy controls, we also observed statistically significant T2 differences for different white and gray matter structures. The EMC algorithm precisely characterizes T2 values, and is able to detect subtle T2 changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T2 variations between different brain regions of healthy controls may correlate with distinct nervous tissue environments that differ from one another at a mesoscopic length-scale. •EMC technique provides accurate and scanner-invariant T2 mapping in MS subjects.•Thalamus T2 differences distinguish relapsing-remitting MS subjects from controls.•Normal-appearing brain regions demonstrate T2 changes in MS patients compared to controls.•T2 values reflect anatomic and function-specific differences in healthy controls.
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ISSN:2213-1582
2213-1582
DOI:10.1016/j.nicl.2017.01.029