Multiple sclerosis is a chronic disease of inflammation and neurodegeneration. Conventional T₂-weighted MRI can detect most areas of active inflammation and white matter (WM) regions with substantial myelin pathology, but visible lesion burden does not always correlate well with patient disability, disease progression, or many symptoms such as cognitive impairment^1,2. Gray matter (GM) regions are known to be involved in MS from an early stage, yet also seldom show signal abnormalities on conventional MRI. There remains a strong need for new, more sensitive biomarkers of occult MS brain pathology for different stages or variations of the disease. We recently described a novel, highly accurate method – the echo-modulation curve (EMC) technique – allowing to quantify T₂ relaxation values from multiple spin echo (MSE) acquisitions in a manner that is independent of the specific MRI sequence, parameter-set, and scanner being used^3,4. In this study, we demonstrate the potential for EMC-based T₂ mapping to detect occult pathology in a large cohort of patients with relapsing-remitting multiple sclerosis (RR-MS).

Data acquisition: 39 healthy volunteers (23 males) and 27 patients (9 males) with clinically diagnosed RR-MS were imaged on a whole-body 3T scanner (Siemens Skyra) using a T₂ mapping MSE protocol and a T₁ weighted reference. Scan parameters were {TR=2500 ms, Echo-spacing=12 ms, N_echoes=10, res=1.7x1.7mm², slice=3 mm, bandwidth=200 [Hz/Px], Tacq=2:44min using 2x GRAPPA acceleration}.

EMC algorithm: Bloch simulations of the prospective MSE protocol were performed using the exact RF pulse shapes and other experimental parameters. Simulations were repeated for a range of T₂ and B₁⁺ values (T₂=1…1000ms, B₁⁺ = 50…130 % deviation from nominal value), producing a database of EMCs, each associated with a unique [B₁⁺,T₂] value pair. T₂ maps were then generated by pixel-by-pixel matching of the MSE DICOMs time-series, to the database of simulated EMC via l₂-norm minimization of the difference between experimental and simulated EMCs³.

Segmentation: Freesurfer⁵ was used to delineate 7 regions-of-interest (ROIs) in the T₂ maps based on a co-registered volumetric T₁ dataset. Separately, manual ROIs were drawn for 14 GM and WM structures by a board certified neuroradiologist on T₂-weighted images, synthetically generated based on the EMC fitted T₂ map (Figure 1).

Statistical analysis: Mean and standard deviation (SD) were calculated for each ROI. Analysis of covariance (ANCOVA) was used to test the statistical difference between MS and control groups in terms of T₂ mean and SD for each ROI, adjusted for age and gender. Logistic regression and area under the ROC curve (AUC) was used to assess the utility of mean T₂ for discriminating MS patients from controls. Region-specific T₂ values were also correlated with disease duration and patient-reported disability⁶ (ordinal scale of 0-8 with 8 being bedridden).

Tables 1 & 2 summarize the average T₂ values for the Freesurfer and manually drawn brain ROIs respectively. Statistically significant T₂ differences were detected in the MS versus healthy controls groups in 4 out of 7 Freesurfer ROIs, and 9 out of 14 for manually drawn ROIs. AUC analysis showed that thalamic T₂ changes could discriminate RR-MS from control subjects (AUC = 0.913). Last, whole-brain WM T₂ positively correlated with the patient reported disability scale (p-value 0.038). Full benchmark tests of the EMC technique were also run across different scanners and parameter sets (results not shown) yielding high reproducibility (mean SD=1.8% across 24 scans) and low inter-subject and inter-scanner variability (mean SD=2.4 % across 30 volunteers).A novel, highly accurate EMC technique can detect subtle T₂ differences for a variety of normal-appearing brain structures in a large cohort of RR-MS patients compared to healthy controls. Significant T₂ changes were observed for the thalamus and other GM regions (see Table 2). GM injury can occur in earliest stages of MS and is associated with a wide range of clinical symptoms including cognitive decline, motor deficits, fatigue, and pain syndromes⁷. As expected, WM lesions visible on conventional MRI had T₂ values 37-45% higher than homologous WM regions in healthy controls (all comparisons, p-value < 0.001). Also noted, were significant T₂ increases for the manually drawn ROIs in the normal-appearing WM regions such as the periventricular WM, genu, and body of the corpus callosum. The biophysical basis for these underlying T₂ changes will be complex and may reflect different pathological aspects of MS including GM demyelination, microglial activation, iron deposition and/or decreased neuronal density. Overall the current results suggest EMC-derived T₂ mapping could become a useful imaging biomarker of occult MS pathology in normal appearing brain structures. Future efforts will compare regional T₂ changes across time and between MS disease classifications.