Background/objectives: Neurofilament light chain (NfL) levels in the cerebrospinal fluid (CSF) of multiple sclerosis (MS) patients correlate with the degree of neuronal injury. To date, little is known about NfL concentrations in the serum of relapsing remitting multiple sclerosis (RRMS) patients and their relationship with CSF levels and magnetic resonance imaging (MRI) measures of disease severity. We aimed to validate the quantification of NfL in serum samples of RRMS, as a biofluid source easily accessible for longitudinal studies. Methods: A total of 31 RRMS patients underwent CSF and serum sampling. After a median time of 3.6 years, 19 of these RRMS patients, 10 newly recruited RRMS patients and 18 healthy controls had a 3T MRI and serum sampling. NfL concentrations were determined by electrochemiluminescence immunoassay. Results: NfL levels in serum were highly correlated to levels in CSF ( r = 0.62, p = 0.0002). Concentrations in serum were higher in patients than in controls at baseline ( p = 0.004) and follow-up ( p = 0.0009) and did not change over time ( p = 0.56). Serum NfL levels correlated with white matter (WM) lesion volume ( r = 0.68, p < 0.0001), mean T1 ( r = 0.40, p = 0.034) and T2* relaxation time ( r = 0.49, p = 0.007) and with magnetization transfer ratio in normal appearing WM ( r = −0.41, p = 0.029). Conclusion: CSF and serum NfL levels were highly correlated, and serum concentrations were increased in RRMS. Serum NfL levels correlated with MRI markers of WM disease severity. Our findings further support longitudinal studies of serum NfL as a potential biomarker of on-going disease progression and as a potential surrogate to quantify effects of neuroprotective drugs in clinical trials.

Patients suffering from migraine with aura (MWA) and migraine without aura (MWoA) show abnormalities in visual motion perception during and between attacks. Whether this represents the consequences of structural changes in motion-processing networks in migraineurs is unknown. Moreover, the diagnosis of migraine relies on patient's history, and finding differences in the brain of migraineurs might help to contribute to basic research aimed at better understanding the pathophysiology of migraine. To investigate a common potential anatomical basis for these disturbances, we used high-resolution cortical thickness measurement and diffusion tensor imaging (DTI) to examine the motion-processing network in 24 migraine patients (12 with MWA and 12 MWoA) and 15 age-matched healthy controls (HCs). We found increased cortical thickness of motion-processing visual areas MT+ and V3A in migraineurs compared to HCs. Cortical thickness increases were accompanied by abnormalities of the subjacent white matter. In addition, DTI revealed that migraineurs have alterations in superior colliculus and the lateral geniculate nucleus, which are also involved in visual processing. A structural abnormality in the network of motion-processing areas could account for, or be the result of, the cortical hyperexcitability observed in migraineurs. The finding in patients with both MWA and MWoA of thickness abnormalities in area V3A, previously described as a source in spreading changes involved in visual aura, raises the question as to whether a “silent” cortical spreading depression develops as well in MWoA. In addition, these experimental data may provide clinicians and researchers with a noninvasively acquirable migraine biomarker.

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.

Objective: To examine morphologic changes in the somatosensory cortex (SSC) of patients with migraine. Methods: Cortical thickness of the SSC of patients with migraine was measured in vivo and compared with age- and sex-matched healthy subjects. The cohort was composed of 24 patients with migraine, subdivided into 12 patients who had migraine with aura, 12 patients who had migraine without aura, and 12 controls. Group and individual analyses were performed in the SSC and shown as average maps of significant changes in cortical thickness. Results: Migraineurs had on average thicker SSCs than the control group. The most significant thickness changes were noticed in the caudal SSC, where the trigeminal area, including head and face, is somatotopically represented. Conclusions: Our findings indicate the presence of interictal structural changes in the somatosensory cortex (SSC) of migraineurs. The SSC plays a crucial role in the noxious and nonnoxious somatosensory processing. Thickening in the SSC is in line with diffusional abnormalities observed in the subcortical trigeminal somatosensory pathway of the same migraine cohort in a previous study. Repetitive migraine attacks may lead to, or be the result of, neuroplastic changes in cortical and subcortical structures of the trigeminal somatosensory system.

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable fairly accurate automated classification of AD patients, mild cognitive impaired patients (MCI) and elderly controls. Little is known, however, about the classification power of volume-based morphometry, where features of interest consist of a few brain structure volumes (e.g. hippocampi, lobes, ventricles) as opposed to hundreds of thousands of voxel-wise gray matter concentrations. In this work, we experimentally evaluate two distinct volume-based morphometry algorithms (FreeSurfer and an in-house algorithm called MorphoBox) for automatic disease classification on a standardized data set from the Alzheimer's Disease Neuroimaging Initiative. Results indicate that both algorithms achieve classification accuracy comparable to the conventional whole-brain voxel-based morphometry pipeline using SPM for AD vs elderly controls and MCI vs controls, and higher accuracy for classification of AD vs MCI and early vs late AD converters, thereby demonstrating the potential of volume-based morphometry to assist diagnosis of mild cognitive impairment and Alzheimer's disease.