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

Abstract Introduction Quantitative T 2 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 T 2 changes in normal-appearing brain regions of subjects with RRMS (N = 27) compared to age-matched controls (N = 38). Methods The EMC algorithm uses Bloch simulations to model T 2 decay curves in multi-spin-echo MRI sequences, independent of scanner, and scan-settings. T 2 values were extracted from normal-appearing white and gray matter brain regions using both expert manual regions-of-interest and user-independent FreeSurfer segmentation. Results Compared to conventional exponential T 2 modeling, EMC fitting provided more accurate estimations of T 2 with less variance across scans, MRI systems, and healthy individuals. Thalamic T 2 was increased 8.5% in RRMS subjects ( p 2 associated with RRMS diagnosis (all p 2 differences for different white and gray matter structures. Conclusions The EMC algorithm precisely characterizes T 2 values, and is able to detect subtle T 2 changes in normal-appearing brain regions of RRMS patients. These presumably capture both axon and myelin changes from inflammation and neurodegeneration. Further, T 2 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.