Combining sodium MRI, proton MR spectroscopic imaging, and intracerebral EEG in epilepsy.

Whole brain ionic and metabolic imaging has potential as a powerful tool for the characterization of brain diseases. We combined sodium MRI (23 Na MRI) and 1 H-MR Spectroscopic Imaging (1 H-MRSI), assessing changes within epileptogenic networks in comparison with electrophysiologically normal networks as defined by stereotactic EEG (SEEG) recordings analysis. We applied a multi-echo density adapted 3D projection reconstruction pulse sequence at 7 T (23 Na-MRI) and a 3D echo-planar spectroscopic imaging sequence at 3 T (1 H-MRSI) in 19 patients suffering from drug-resistant focal epilepsy who underwent presurgical SEEG. We investigated 23 Na MRI parameters including total sodium concentration (TSC) and the sodium signal fraction associated with the short component of T2 * decay (f), alongside the level of metabolites N-acetyl aspartate (NAA), choline compounds (Cho), and total creatine (tCr). All measures were extracted from spherical regions of interest (ROIs) centered between two adjacent SEEG electrode contacts and z-scored against the same ROI in controls. Group comparison showed a significant increase in f only in the epileptogenic zone (EZ) compared to controls and compared to patients' propagation zone (PZ) and non-involved zone (NIZ). TSC was significantly increased in all patients' regions compared to controls. Conversely, NAA levels were significantly lower in patients compared to controls, and lower in the EZ compared to PZ and NIZ. Multiple regression analyzing the relationship between sodium and metabolites levels revealed significant relations in PZ and in NIZ but not in EZ. Our results are in agreement with the energetic failure hypothesis in epileptic regions associated with widespread tissue reorganization.

Laminar analysis of the cortical T1/T2-weighted ratio at 7T.

OBJECTIVE: In this observational study, we explored cortical structure as function of cortical depth through a laminar analysis of the T1/T2-weighted (T1w/T2w) ratio, which has been related to dendrite density in ex vivo brain tissue specimens of patients with MS. METHODS: In 39 patients (22 relapsing-remitting, 13 female, age 41.1 ± 10.6 years; 17 progressive, 11 female, age 54.1 ± 9.9 years) and 21 healthy controls (8 female, , age 41.6 ± 10.6 years), we performed a voxel-wise analysis of T1w/T2w ratio maps from high-resolution 7T images from the subpial surface to the gray matter/white matter boundary. Six layers were sampled to ensure accuracy based on mean cortical thickness and image resolution. RESULTS: At the voxel-wise comparison (p < 0.05, family wise error rate corrected), the whole MS group showed lower T1w/T2w ratio values than controls, both when considering the entire cortex and each individual layer, with peaks occurring in the fusiform, temporo-occipital, and superior and middle frontal cortex. In relapsing-remitting patients, differences in the T1w/T2w ratio were only identified in the subpial layer, with the peak occurring in the fusiform cortex, whereas results obtained in progressive patients mirrored the widespread damage found in the whole group. CONCLUSIONS: Laminar analysis of T1w/T2w ratio mapping confirms the presence of cortical damage in MS and shows a variable expression of intracortical damage according to the disease phenotype. Although in the relapsing-remitting stage, only the subpial layer appears susceptible to damage, in progressive patients, widespread cortical abnormalities can be observed, not only, as described before, with regard to myelin/iron concentration but, possibly, to other microstructural features.

Sensory-motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy.

Graph theory and network modelling have been previously applied to characterize motor network structural topology in multiple sclerosis (MS). However, between-group differences disclosed by graph analysis might be primarily driven by discrepancy in density, which is likely to be reduced in pathologic conditions as a consequence of macroscopic damage and fibre loss that may result in less streamlines properly traced. In this work, we employed the convex optimization modelling for microstructure informed tractography (COMMIT) framework, which, given a tractogram, estimates the actual contribution (or weight) of each streamline in order to optimally explain the diffusion magnetic resonance imaging signal, filtering out those that are implausible or not necessary. Then, we analysed the topology of this 'COMMIT-weighted sensory-motor network' in MS accounting for network density. By comparing with standard connectivity analysis, we also tested if abnormalities in network topology are still identifiable when focusing on more 'quantitative' network properties. We found that topology differences identified with standard tractography in MS seem to be mainly driven by density, which, in turn, is strongly influenced by the presence of lesions. We were able to identify a significant difference in density but also in network global and local properties when accounting for density discrepancy. Therefore, we believe that COMMIT may help characterize the structural organization in pathological conditions, allowing a fair comparison of connectomes which considers discrepancies in network density. Moreover, discrepancy-corrected network properties are clinically meaningful and may help guide prognosis assessment and treatment choice.