One of the most prominent neurodegenerative diseases, multiple sclerosis (MS) is an autoimmune condition where the immune system attacks the myelin sheath of its own axons. This renders neuronal axons vulnerable and exposed, leaving behind glial lesions/“scars” in brain tissue which are the characteristic marker that lends the disease its name. “Multiple sclerosis” literally means “multiple regions of scarring”, which alludes to the various glial lesions/“scars” that are found in patients’ brain tissue. 

But as with any scarring injury, it can take a long time for the scars to form even if the patient is already displaying clinical symptoms like intense fatigue and dizziness. Often, a lot of damage is done before the lesions even show up on a conventional MRI. A regular MRI uses radio waves to create contrast images of water and fat distributions in the brain [Fig. 1]. While such imaging tells us a lot about changes in tissue density and how various conditions can affect soft tissues, in diseases like MS which feature prominent axonal degeneration, the localized white matter (WM) changes are not easy to study with a conventional MRI. Consequently, even normal-appearing white matter (NAWM) in progressive MS has been shown to be highly abnormal, displaying numerous degenerative changes and markers [1]. 

So how do we track disease progression in conditions like MS when a conventional MRI comes up empty-handed? The answer is diffusion tensor imaging (DTI) [2]. DTI is a type of MRI that focuses on mapping the diffusion of water molecules through axonal white matter tissue compared to the structural contrasts in tissues captured by a conventional MRI. DTI measures four variables: 

1. Fractional anisotropy (FA) - the overall degree of water molecule anisotropy in the axon
2. Mean diffusivity (MD) - the overall degree of diffusion in the axon
3. Radial diffusion (RD) - degree of diffusion across the axon
4. Axial diffusion (RD) - degree of diffusion along the axon

The areas where these variables are heavily altered from baseline often align with MS lesions that appear later during disease progressions, as well as areas of neuronal inflammation and degeneration [3].

Previously, diffusion MRI has been used to track WM deterioration in MS and characterize WM pathology for the disease [3]. A 2022 study using DTI to track changes in post-COVID-19 encephalitis, or the brain inflammation caused by the body’s own immune system,  showed promising results regarding the detection of early changes in NAWM associated with the disease when a conventional MRI appears normal [4].

In 2022, a team of researchers at a Chinese university hospital used DTI to assess the integrity of NAWM in MS [5]. In a previous study, they found metabolite abnormalities in NAWM of region-of-interest (ROI) tracts in MS [6]. They hypothesized that these occurred due to demyelination, accumulation of inflammatory cells, and axonal injury in NAWM, and wanted to see if these abnormalities were associated with microstructural changes in the white matter [6]. Their unique approach to this study involved creating a probabilistic lesion map of the likelihood of various brain regions being affected by lesions using patient and control group scans in combination with the open-access Johns Hopkins white matter atlas to examine specific ROIs [Fig. 4]. Such an approach helped the researchers reduce some bias regarding obvious/common regions of lesion formation [5].

The results showed large-scale differences in diffusion metrics captured by the DTI [5]. Compared to the control groups, MS patients had significantly lower FA values in the entire corpus callosum and other ROI tracts like the bilateral anterior corona radiata and the right posterior thalamic radiation, suggesting a decrease in white matter integrity in those brain regions in patients with MS. These patients also had higher MD values for all NAWM tracts, and there was a highly significant increase in MD values of the anterior and superior corona radiata tracts for both hemispheres, suggesting early microstructural damage or disruption in these regions even without obvious lesions in patients with MS. Furthermore, the AD and RD values derived from the DTI imaging were also elevated for all NAWM tracts. Particularly, AD displayed significant elevation in five NAWM tracts, whereas RD displayed significant elevation in six NAWM tracts, suggesting that MS produces potential damage to axons and myelin in multiple white matter tracts, even in areas without visible lesions [5].

Combined, these findings of widespread microstructural changes and damage in patients with MS provide evidence for the hypothesis that there is demyelination, axonal injury, and accumulation of inflammatory cells in the NAWM of the MS-affected brain [5]. While the researchers could not find a significant correlation between the affected regions in this study and their previous study of metabolite abnormalities in MS, their work highlights how important DTI metrics could be used as potentially non-invasive biomarkers of disease severity and progression in conditions like MS [5] [6]. These results thus have important medical implications, such as in cases where the typical biomarkers like lesions or oligoclonal bands are not found in patients with MS. To combat this diagnostic limitation, clinicians may choose to use diffusion imaging, such as DTI, to characterize and identify MS-specific WM pathology to help make the vital diagnosis and initiate treatment and management of MS as early as possible. Such an approach can help revolutionize disease prognosis and help patients live infinitely better lives.

References:

1. Gallego-Delgado, P., James, R., Browne, E., Meng, J., Umashankar, S., Tan, L., Picon, C., Mazarakis, N. D., Faisal, A. A., Howell, O. W., & Reynolds, R. (2020). Neuroinflammation in the normal-appearing white matter (NAWM) of the multiple sclerosis brain causes abnormalities at the nodes of ranvier. PLOS Biology, 18(12). doi:10.1371/journal.pbio.3001008 
2. Trivedi, R., Rathore, R. K. S., & Gupta, R. K. (2008). Review: Clinical application of diffusion tensor imaging. The Indian Journal of Radiology & Imaging, 18(1), 45–52. doi:10.4103/0971-3026.38505
3. Sbardella, E., Tona, F., Petsas, N., & Pantano, P. (2013). DTI Measurements in Multiple Sclerosis: Evaluation of Brain Damage and Clinical Implications. Multiple sclerosis international, 2013, 671730. doi:10.1155/2013/671730
4. Latini, F., Fahlström, M., Fällmar, D., Marklund, N., Cunningham, J. L., & Feresiadou, A. (2022). Can diffusion tensor imaging (DTI) outperform standard magnetic resonance imaging (MRI) investigations in post-COVID-19 autoimmune encephalitis?. Upsala journal of medical sciences, 127. doi:10.48101/ujms.v127.8562
5. Bao, J., Tu, H., Li, Y., Sun, J., Hu, Z., Zhang, F., & Li, J. (2022). Diffusion Tensor Imaging Revealed Microstructural Changes in Normal-Appearing White Matter Regions in Relapsing-Remitting Multiple Sclerosis. Frontiers in neuroscience, 16, 837452. doi:10.3389/fnins.2022.837452
6. Sun, J., Song, H., Yang, Y., Zhang, K., Gao, X., Li, X., Ni, L., Lin, P., & Niu, C. (2017). Metabolic changes in normal appearing white matter in multiple sclerosis patients using multivoxel magnetic resonance spectroscopy imaging. Medicine, 96(14), e6534. doi:10.1097/MD.0000000000006534