Relapsing-remitting multiple sclerosis (RRMS) is a chronic progressive disease that evolves through clinical relapses and subclinical inflammation and degeneration (1). To date, there is no cure for RRMS but a number of treatments substantially reduce the frequency of clinical relapses and the extent of local inflammation and brain volume loss (2). Conventional magnetic resonance imaging (cMRI), such as T1- and T2-weighted magnetic resonance imaging (MRI), provides essential metrics to measure local pathology (lesion number and volume), inflammatory activity, and severe tissue loss in the central nervous system (3). Yet, cMRI measures exhibit low sensitivity to diffuse brain alterations, do not provide metrics to differentiate inflammatory demyelination from brain remodeling and repair (4), and only partially correlate with patients function and disability (5). To overcome the limitations of cMRI, a number of non-conventional MRI techniques have been studied in MS patients, including Magnetization Transfer Imaging (MTI), Diffusion Tensor Imaging Susceptibility MRI, and MR relaxometry (5).

Among non-conventional MRI techniques, quantitative MRI (qMRI) probes the brain microstructure through standardized physical parameters that are directly linked to the biological and/or pathological properties of the tissue where they are measured (6). Besides, the combination of multiple qMRI metrics allow to amplify the true tissue-related information and limit their inherent measurement noise, thanks to the overlapping information that qMRI provide (7, 8). In fact, qMRI contrasts are influenced by the same tissue properties (i.e., micro/macromolecules, i.e., within axons, myelin, cells, intracellular/extracellular water, iron), though they exhibit different sensitivity to each of them (6, 9, 10). T1 relaxometry is highly sensitive to the tissue structural organization and free-water protons (11, 12): T1 rt increases when there is a loss of tissue structural organization/density (13, 14), and/or when free-water content increases. T1 rt also moderately decreases with an increase of iron content in the brain tissue (15). T2 rt is highly sensitive to free-water content, although it is also affected by the presence of macromolecules and iron. Both an accumulation of free water and a loss of macromolecules will increase T2 rt, while iron will decrease it (16). As well, the T2* transverse rt exhibit high sensitivity to free-water content and it is particularly sensitive to the presence of iron (17). An increase of T2* suggests a loss of macromolecules, while a decrease indicates an increase of iron or macromolecular compounds. Finally, the metrics obtained with MTI are very sensitive to variation of large molecular aggregates like lipids and proteins in myelin or cellular membranes (18, 19) so that they decrease when the amount of macromolecules decreases (i.e., in demyelination and/or cell loss) and/or the free water increases (i.e., edema) (20). Specific patterns of changes in T1, T2, T2* relaxation times, and magnetization transfer measures may be optimal to quantify brain abnormalities and their evolution in MS patients. For example, an increase in T1 and T2 relaxation times may suggest either a water accumulation (edema) or a loss of myelin/axon. A concomitant strong decrease in MTR will point at the latter phenomenon (myelin/axon loss), whereas a mild MTR decrease or no MTR changes are more typical of an increase in extracellular water (6). Combining multiple qMRI techniques in a clinically compatible protocol is challenging (e.g., due to motion, scan time, reproducibility, etc.) but there are currently ongoing efforts toward fast and reproducible protocols applying combined and accelerated acquisitions (21–23), synthetic computation of qMRI metrics (22) and qMRI fingerprinting (24).

To date, a number of cross-sectional studies [for review, see Ref. (5, 25)]—including some from our group (26–28)—leveraged the information obtained by multiple qMRI contrasts to describe brain inflammation and degeneration in MS patients. However, only few applied this approach to study longitudinal brain changes in patients with MS (29, 30) and reported the concomitant changes of multiple qMRI metrics [myelin water fraction, MTR, T1, and T2 relaxometry (29) and MTR and fractional anisotropy/diffusivities (30)] in black-holes and brain connectivity.

In this work, we have developed an automated MRI framework combining T1, T2, and T2* relaxometry with MTI (hereafter referred as qMRI) in order to (i) assess the potential of a combination of multiple qMRI parameters to quantify and interpret the evolution over 2 years of focal and diffuse pathology in a cohort of early RRMS patients and (ii) predict patients clinical outcome.

Our study shows that the combination of multiple qMRI metrics is sensitive to 2-year changes in brain pathology in a group of early-stage MS patients on therapy, suggesting a decrease in NAWM inflammation as well as repair processes in lesions. Besides, our work provides evidence that multiple qMRI metrics at baseline are strongly and differently related to patients’ motor and cognitive function at two year follow-up.

To date, there are very few studies that combined qMRI metrics to study the evolution of MS pathology over time and none applied T1, T2, T2* relaxometry, and MTR. A small number of longitudinal studies in MS patients applied either MTR (39–42) or T2* relaxometry maps (43). These works showed a progressive increase in MTR over time in subgroups of lesions [i.e., nearly 20% of acute lesions according to Chen et al. (40)] and a decrease in T2* rt in the basal ganglia (43) in MS patients, who were followed-up between 1 and 4 years. Changes in MTR and T2* rt were interpreted as remyelination in lesions and iron accumulation in basal ganglia; however, these interpretations may have been misleading because an increase in MTR and a decrease in T2* might be also due to a decrease in water content, i.e., edema reabsorption (20, 26).

Recent developments in MRI technology have made it possible to acquire multiple advanced MRI contrasts in scan times compatible with clinical research, thereby increasing sensitivity and specificity to brain pathology (21, 26, 27, 44). By combining multiple MR metrics and leveraging their biophysical properties, we have previously studied the pathology of MS lesions, NA tissue and brain connectivity (26, 28) and proposed a new classification of MS lesions (27). Here, we have developed an automated qMRI framework to monitor disease evolution in early MS patients.

Despite the absence of volumetric changes in the majority of lesions (75%), qMRI showed a concomitant significant decrease in T1 relaxation times and an increase of MTR suggesting repair mechanisms such as remyelination, increase in axonal density and/or gliosis (18, 45). Future studies combining qMRI with diffusion MRI may allow discriminating between gliotic or axonal/myelin restauration by exploiting the information on tissue anisotropy provided by the diffusion contrast.

The few lesions that disappeared at 2-year follow-up (resolved lesions) exhibited higher MTR and lower T1 and T2* rt at baseline than lesions that did not change in volume. While higher MTR may indicate at the time higher free-water content (i.e., more pronounced edema due to active inflammation) or higher higher myelin/axonal bound water (i.e., higher myelination/axonal density), the concomitant lower T1/T2* rt point at the latter pathophysiological explanation. In fact, the presence of edema would have increased—not decreased—both T1 and T2* rt (6).

Also, lesions that significantly decreased in volume at 2-year follow-up (shrunken lesions), evidenced a significant higher T2 rt at baseline compared to stable and other lesions, possibly related to higher inflammatory processes (i.e., high presence of extracellular water) or higher cellular infiltration (i.e., lower intracellular water). The absence of significant differences at baseline between lesions that enlarge at follow-up and other lesions suggests that the lesion microstructural properties as measured by qMRI is not predictive of lesion growth in this cohort of patients.

These findings provide new evidence that qMRI may be used as baseline biomarker of lesion evolution and extend current literature reporting that lesions with modest MTR decrease compared to healthy tissue are more likely to undergo partial or complete recovery (18, 46).

The study of NA tissue revealed a mild but significant longitudinal decrease in T2 rt in NAWM and a decrease of both T2 and T1 rt in the pallidum, whereas no longitudinal changes were observed in healthy subjects for all aMRI parameters. On one hand, these data provide evidence of the stability of qMRI in control subjects. On the other hand, our results suggest that—in our cohort of early MS patients with minimal clinical deficits—there is a longitudinal decrease in overall inflammation, i.e., due to lower microglia activation in patients on therapy (47) and/or iron accumulation (16). Overall these findings suggest that qMRI metrics may help defining the underpinnings of disease evolution in MS patients and provide new biomarkers of disease impact over time in the absence of significant brain volume changes.

Last, lesions and NAWM characteristics, as measured with qMRI, appeared to be strongly related to motor and cognitive changes at 2-year follow-up, whereas lesion volume did not. These results extend the evidence obtained in a previous cross-sectional study from our group, where a number of cognitive functions exhibited high correlations with lesion and NA tissue properties measured with qMRI (26). MS patients improved their motor and cognitive function over 2 years: while on one hand, cognitive improvement may be attributed to learning despite we adopted an adapted test for longitudinal assessment, the presence of both cognitive and motor improvement in a very homogeneous cohort of early-stage RRMS patients on therapy may well indicate compensatory plasticity.

The study suffers from some limitations. First, we studied a cohort of patients and healthy controls of moderate/small size. Future study should aim at confirming our findings in larger populations and extend them to more advanced disease stages. Second, since we studied a cohort of early-stage MS patients, we do not have histological data to corroborate our findings; therefore, we interpreted our results based upon the biophysical properties of the MR signals (6) and upon a number of previous publications using single contrasts parametric MRI and histopathology [for review see Ref. (48)]. However, though histological data might be valuable to assess changes in myelin and axons, postmortem experiments in patients will not provide any direct information about the presence of extracellular water accumulation (i.e., edema), as we do in the current study. To note, the only one study that—to our knowledge—attempted at correlating ex vivo T1/T2 relaxation times and MTR with histopathological metrics evinced the limits of ex vivo MRI to measure the complexity of phenomena influencing the MRI signal in vivo (49). Last, another potential limitation of our work is that the applied T2 relaxometry maps had a lower resolution than the other maps, which could have decreased the sensitivity to lesions and NA tissue pathology.

In summary, we have shown that combining different MR parameters allows increasing pathological specificity to ongoing damage even at early MS stages and provide metrics that predict patients motor and cognitive function at 2 years follow-up. In the future, we will assess the sensitivity of qMRI metrics to larger and more heterogeneous patients cohorts, we will establish the sensitivity of qMRI metrics to different therapy regimens as well as work on the development of “personalized” qMRI assessments.

The study was approved by the Ethic Committee of the Lausanne University Hospital (CHUV); all participants gave written informed consent prior to participation.

Study design (CG and GK); collection, analysis, and interpretation of data (GB, BM, MF, JM, MS, GK, CG, and PF); writing of the report and decision to submit the paper for publication (GB, BM, JM, SS, MS, RP, J-PT, GK, and CG).

GK and BM are Siemens Healthcare employees. The other authors have nothing to disclose. The reviewer EP and handling editor declared their shared affiliation, and the handling editor states that the process nevertheless met the standards of a fair and objective review.