This work describes the use of a novel whole brain 3D MRF sequence (18, 21) in differentiating F-NAWM and splenium in patients with MS based on relaxometry estimates. Given the highly reproducible and accurate information provided by MR relaxometry (21, 27) the results of this study, and the isotropic whole brain coverage afforded by this technique, MRF has the potential for use in the diagnosis of patients with MS. The previously described application of MRF in the normal brain (21, 22), brain tumors (23, 24), epilepsy (25) and Parkinson disease (26), suggests that MRF has the potential for even broader application beyond MS.
MRI currently is a fundamental clinical tool when guiding therapy for patients with MS (28). Given the complexity of the condition, several studies have been conducted with more advanced MRI techniques (such as myelin water fraction or functional MRI) to predict whether MS could be diagnosed by machine learning techniques (29–32). Although the mentioned investigations have been successful, those techniques differ from MRF in that they do not provide a multi parametric approach from a single acquisition leading to lengthier exam acquisitions. Furthermore, the reproducibility of said techniques is not as well established as MRF-based relaxation estimates for both in vivo and phantom experiments (27, 33).
F-NAWM demonstrated longer relaxation in patients with MS in our study. This has been described by other quantitative imaging investigations (34). Those changes are thought to be related with myelin histological changes in the white matter poorly defined by imaging (35) and importantly could predict clinical disability (12). In this study, F-NAWM differentiation using MRF relaxation properties between cases and controls was fairly weak (mean out of fold accuracy = 65%). Given the moderate sample size, it is possible larger samples could describe more robust differentiation. Also, it is important to note prior studies (34, 36, 37) have provided estimates of the entire NAWM through the brain, potentially including areas adjacent to MS plaques that can have subtle signal changes. In order to avoid this pitfall, values stated in this work were from segmented areas that only included white matter with no changes in the conventional T2 weighted imaging and double inversion recovery.
Splenium is partially responsible for interhemispheric connections within the brain (38). As such, studies describing splenium changes in patients with MS (39) have focused on diffusion tensor imaging. However, histological changes in MS may also be responsible for relaxation lengthening in the splenium (34). The accuracy described in this study for classifying disease and control at this anatomical site based solely on MRF-based relaxometry changes was fairly strong (= 90%), identifying a major advantage of MRF. Given its potential to depict changes that are currently not seen or described in clinical practice, MRF may useful, especially in those cases where the diagnosis of MS is not clearly established by more conventional well established imaging protocols.
It is known that timing since diagnosis in MS can influence normal tissue relaxation (7, 11, 37), and that those changes could predict clinical disability(40, 41). Papadoulos et at (7) described NAWM relaxation changes in a longitudinal study covering 5 years. However, Davies et al (11) found no significant differences in a three year longitudinal study after accessing T1 quantitative changes through NAWM and GM. In this study, T2 lengthening was observed in MS plaques on those patients with the longest time from diagnosis of MS to imaging. These findings could be related to a higher degree of Wallerian degeneration(42) although this finding has questionable clinical significance. Also, given this study was cross sectional, it would be valuable to investigate MRF through the same protocol in a longitudinal basis, so NAWM and splenium changes may be described and the faster acquisition as compared with the protocols mentioned (7, 40, 41) is a valuable tool for clinical application.
This study has several limitations. The relatively small sample size may not be sufficient to effectively establish F-NAWM and splenium changes in MS as compared to controls. Also, F-NAWM segmentations represented a minimal fraction of the overall WM in all the patients included. Both active and non-active lesions were included, as defined by gadolinium enhancement in conventional T1 weighted imaging, but given only 10 lesions were active, this study was not powered to detect changes within relaxometry for classifying lesion activity. Future studies with larger sample sizes and volumetric segmentation through normal appearing white matter may be considered.