Innate immune cells and myelin profile in multiple sclerosis: a multi-tracer PET/MR study.

PURPOSE: Neuropathological studies have demonstrated distinct profiles of microglia activation and myelin injury among different multiple sclerosis (MS) phenotypes and disability stages. PET imaging using specific tracers may uncover the in vivo molecular pathology and broaden the understanding of the disease heterogeneity. METHODS: We used the 18-kDa translocator protein (TSPO) tracer (R)-[11C]PK11195 and [11C]PIB PET images acquired in a hybrid PET/MR 3 T system to characterize, respectively, the profile of innate immune cells and myelin content in 47 patients with MS compared to 18 healthy controls (HC). For the volume of interest (VOI)-based analysis of the dynamic data, (R)-[11C]PK11195 distribution volume (VT) was determined for each subject using a metabolite-corrected arterial plasma input function while [11C]PIB distribution volume ratio (DVR) was estimated using a reference region extracted by a supervised clustering algorithm. A voxel-based analysis was also performed using Statistical Parametric Mapping. Functional disability was evaluated by the Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Symbol Digit Modality Test (SDMT). RESULTS: In the VOI-based analysis, [11C]PIB DVR differed between patients and HC in the corpus callosum (P = 0.019) while no differences in (R)-[11C]PK11195 VT were observed in patients relative to HC. Furthermore, no correlations or associations were observed between both tracers within the VOI analyzed. In the voxel-based analysis, high (R)-[11C]PK11195 uptake was observed diffusively in the white matter (WM) when comparing the progressive phenotype and HC, and lower [11C]PIB uptake was observed in certain WM regions when comparing the relapsing-remitting phenotype and HC. None of the tracers were able to differentiate phenotypes at voxel or VOI level in our cohort. Linear regression models adjusted for age, sex, and phenotype demonstrated that higher EDSS was associated with an increased (R)-[11C]PK11195 VT and lower [11C]PIB DVR in corpus callosum (P = 0.001; P = 0.023), caudate (P = 0.015; P = 0.008), and total T2 lesion (P = 0.007; P = 0.012), while better cognitive scores in SDMT were associated with higher [11C]PIB DVR in the corpus callosum (P = 0.001), and lower (R)-[11C]PK11195 VT (P = 0.013). CONCLUSIONS: Widespread innate immune cells profile and marked loss of myelin in T2 lesions and regions close to the ventricles may occur independently and are associated with disability, in both WM and GM structures.

Gray matter networks and cognitive impairment in multiple sclerosis.

BACKGROUND: Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS). OBJECTIVE: To investigate whether single-subject gray matter network properties are related to impaired cognition in MS. METHODS: We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level. RESULTS: Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values. CONCLUSION: Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.

The effect of lesion filling on brain network analysis in multiple sclerosis using structural magnetic resonance imaging.

BACKGROUND: Graph theoretical network analysis with structural magnetic resonance imaging (MRI) of multiple sclerosis (MS) patients can be used to assess subtle changes in brain networks. However, the presence of multiple focal brain lesions might impair the accuracy of automatic tissue segmentation methods, and hamper the performance of graph theoretical network analysis. Applying "lesion filling" by substituting the voxel intensities of a lesion with the voxel intensities of nearby voxels, thus creating an image devoid of lesions, might improve segmentation and graph theoretical network analysis. This study aims to determine if brain networks are different between MS subtypes and healthy controls (HC) and if the assessment of these differences is affected by lesion filling. METHODS: The study included 49 MS patients and 19 HC that underwent a T1w, and T2w-FLAIR MRI scan. Graph theoretical network analysis was performed from grey matter fractions extracted from the original T1w-images and T1w-images after lesion filling. RESULTS: Artefacts in lesion-filled T1w images correlated positively with total lesion volume (r = 0.84, p < 0.001) and had a major impact on grey matter segmentation accuracy. Differences in sensitivity for network alterations were observed between original T1w data and after application of lesion filling: graph theoretical network analysis obtained from lesion-filled T1w images produced more differences in network organization in MS patients. CONCLUSION: Lesion filling might reduce variability across subjects resulting in an increased detection rate of network alterations in MS, but also induces significant artefacts, and therefore should be applied cautiously especially in individuals with higher lesions loads.

Drug-related demyelinating syndromes: understanding risk factors, pathophysiological mechanisms and magnetic resonance imaging findings.

Some drugs and medications can precipitate immune system deregulations, which might be confused with recurrent demyelinating diseases, such as multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMO), exacerbations of an existing disease, neoplastic lesions or other conditions. In this narrative review we describe some of the most relevant drugs and medications associated with iatrogenic demyelination. The anthelminthic agent levamisole is a frequent cocaine adulterant and can precipitate an exacerbated immune response attacking the central nervous system (CNS). High-efficacy multiple sclerosis (MS) drugs might induce a selective CNS immunosuppression, making it susceptible for opportunistic infections that course with demyelination, such as progressive multifocal leukoencephalopathy. Sometimes, the interruption of a high-efficacy drug to treat MS can induce a rapid CNS reentry of lymphocytes, exacerbating demyelinating processes and triggering rebound syndromes. Furthermore, selective cytokines inhibition, such as anti-TNFα agents, might induce an imbalance between cell death and proliferation inducing a paradoxical increase of CNS tumor necrosis factor (TNF), affecting the activity of lymphocytes, microglia and macrophages, triggering aberrant inflammation and demyelination. Immune checkpoint inhibitors are a new class of antineoplastic drugs that enhance the immune response against tumor cells by an upregulation of T-cell activity. However, this hyperactivation of the immune system might be associated with induction of unwanted autoimmune responses. In this paper we review the risk factors, the possible pathological mechanisms and the magnetic resonance imaging (MRI) findings of these drug-related demyelinating syndromes.