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

SUITer: An Automated Method for Improving Segmentation of Infratentorial Structures at Ultra-High-Field MRI

none6siBACKGROUND AND PURPOSE: The advent of high and ultra-high-field MRI has significantly improved the investigation of infratentorial structures by providing high-resolution images. However, none of the publicly available methods for cerebellar image analysis has been optimized for high-resolution images yet. METHODS: We present the implementation of an automated algorithm—SUITer (spatially unbiased infratentorial for enhanced resolution) method for cerebellar lobules parcellation on high-resolution MR images acquired at both 3 and 7T MRI. SUITer was validated on five manually segmented data and compared with SUIT, FreeSurfer, and convolutional neural networks (CNN). SUITer was then applied to 3 and 7T MR images from 10 multiple sclerosis (MS) patients and 10 healthy controls (HCs). RESULTS: The difference in volumes estimation for the cerebellar grey matter (GM), between the manual segmentation (ground truth), SUIT, CNN, and SUITer was reduced when computed by SUITer compared to SUIT (5.56 vs. 29.23 mL) and CNN (5.56 vs. 9.43 mL). FreeSurfer showed low volumes difference (3.56 mL). SUITer segmentations showed a high correlation (R2 =.91) and a high overlap with manual segmentations for cerebellar GM (83.46%). SUITer also showed low volumes difference (7.29 mL), high correlation (R2 =.99), and a high overlap (87.44%) for cerebellar GM segmentations across magnetic fields. SUITer showed similar cerebellar GM volume differences between MS patients and HC at both 3T and 7T (7.69 and 7.76 mL, respectively). CONCLUSIONS: SUITer provides accurate segmentations of infratentorial structures across different resolutions and MR fields.mixedEl Mendili M.M.; Petracca M.; Podranski K.; Fleysher L.; Cocozza S.; Inglese M.El Mendili, M. M.; Petracca, M.; Podranski, K.; Fleysher, L.; Cocozza, S.; Inglese, M

SUITer: an automated method for improving segmentation of infratentorial structures at ultra-high field MRI

Background and purpose: The advent of high and ultra-high-field MRI has significantly improved the investigation of infratentorial structures by providing high-resolution images. However, none of the publicly available methods for cerebellar image analysis has been optimized for high-resolution images yet. Methods: We present the implementation of an automated algorithm-SUITer (spatially unbiased infratentorial for enhanced resolution) method for cerebellar lobules parcellation on high-resolution MR images acquired at both 3 and 7T MRI. SUITer was validated on five manually segmented data and compared with SUIT, FreeSurfer, and convolutional neural networks (CNN). SUITer was then applied to 3 and 7T MR images from 10 multiple sclerosis (MS) patients and 10 healthy controls (HCs). Results: The difference in volumes estimation for the cerebellar grey matter (GM), between the manual segmentation (ground truth), SUIT, CNN, and SUITer was reduced when computed by SUITer compared to SUIT (5.56 vs. 29.23 mL) and CNN (5.56 vs. 9.43 mL). FreeSurfer showed low volumes difference (3.56 mL). SUITer segmentations showed a high correlation (R2 = .91) and a high overlap with manual segmentations for cerebellar GM (83.46%). SUITer also showed low volumes difference (7.29 mL), high correlation (R2 = .99), and a high overlap (87.44%) for cerebellar GM segmentations across magnetic fields. SUITer showed similar cerebellar GM volume differences between MS patients and HC at both 3T and 7T (7.69 and 7.76 mL, respectively). Conclusions: SUITer provides accurate segmentations of infratentorial structures across different resolutions and MR fields

Streamline density and lesion volume reveal a postero-anterior gradient of corpus callosum damage in multiple sclerosis

Background and purpose: Although interhemispheric disconnection significantly contributes to disability in multiple sclerosis (MS), the topography, timeline and relationship of callosal damage accrual with hemispheric damage are still unclear. Methods: Streamline density and the presence of focal lesions in five callosal subregions were computed in 55 people with MS [13 relapsing-remitting (RRMS), 20 secondary progressive (SPMS), 22 primary progressive (PPMS)] and 24 healthy controls. Results: Streamline density decrease was identified in SPMS in all corpus callosum (CC) subregions, in PPMS in the posterior CC and mid-posterior CC and in RRMS in the posterior CC. CC density was independently predicted by CC lesion volume and hemispheric lesion volume and independently predicted visuospatial memory, Expanded Disability Status Scale, manual dexterity and ambulation. Conclusions: The reduction in CC density across phenotypes suggests an earlier involvement of the posterior regions, followed only at a later stage by involvement of the anterior portions of the CC. Such interhemispheric disconnection seems to develop as a consequence of white matter macroscopic damage and exerts a relevant impact on motor and, to a lesser extent, cognitive disability

Depression is associated with disconnection of neurotransmitter-related nuclei in multiple sclerosis

Background: Depression is frequently associated with multiple sclerosis (MS). However, the biological background underlying such association is poorly understood. Objective: Investigating the functional connections of neurotransmitter-related brainstem nuclei, along with their relationship with white matter (WM) microstructure, in MS patients with depressive symptomatology (MS-D) and without depressive symptomatology (MS-nD). Methods: Combined resting-state functional magnetic resonance imaging (fMRI) and diffusion-weighted MRI (dMRI) study on 50 MS patients, including 19 MS-D and 31 MS-nD patients, along with 37 healthy controls (HC). Main analyses performed are (1) comparison between groups of raphe nuclei (RN)-related functional connectivity (FC); (2) correlation between RN-related FC and whole brain dMRI-derived fractional anisotropy (FA) map; and (3) comparison between groups of FA in the RN-related WM area. Results: (1) RN-related FC was reduced in MS-D when compared to MS-nD and HC; (2) RN-related FC positively correlated with FA in a WM cluster mainly encompassing thalamic/basal ganglia regions, including the fornix; and (3) FA in such WM area was reduced in MS-D. Conclusion: Depressive symptomatology in MS is specifically associated to a functional disconnection of neurotransmitter-related nuclei, which in turn may be traced to a distinct spatial pattern of WM alterations mainly involving the limbic network

Depression is associated with disconnection of neurotransmitter-related nuclei in multiple sclerosis

Background: Depression is frequently associated with multiple sclerosis (MS). However, the biological background underlying such association is poorly understood. Objective: Investigating the functional connections of neurotransmitter-related brainstem nuclei, along with their relationship with white matter (WM) microstructure, in MS patients with depressive symptomatology (MS-D) and without depressive symptomatology (MS-nD). Methods: Combined resting-state functional magnetic resonance imaging (fMRI) and diffusion-weighted MRI (dMRI) study on 50 MS patients, including 19 MS-D and 31 MS-nD patients, along with 37 healthy controls (HC). Main analyses performed are (1) comparison between groups of raphe nuclei (RN)-related functional connectivity (FC); (2) correlation between RN-related FC and whole brain dMRI-derived fractional anisotropy (FA) map; and (3) comparison between groups of FA in the RN-related WM area. Results: (1) RN-related FC was reduced in MS-D when compared to MS-nD and HC; (2) RN-related FC positively correlated with FA in a WM cluster mainly encompassing thalamic/basal ganglia regions, including the fornix; and (3) FA in such WM area was reduced in MS-D. Conclusion: Depressive symptomatology in MS is specifically associated to a functional disconnection of neurotransmitter-related nuclei, which in turn may be traced to a distinct spatial pattern of WM alterations mainly involving the limbic network

Non-invasive quantification of inflammation, axonal and myelin injury in multiple sclerosis

The aim of this study was to determine the feasibility of diffusion basis spectrum imaging in multiple sclerosis at 7 T and to investigate the pathological substrates of tissue damage in lesions and normal-appearing white matter. To this end, 43 patients with multiple sclerosis (24 relapsing-remitting, 19 progressive), and 21 healthy control subjects were enrolled. White matter lesions were classified in T1-isointense, T1-hypointense and black holes. Mean values of diffusion basis spectrum imaging metrics (fibres, restricted and non-restricted fractions, axial and radial diffusivities and fractional anisotropy) were measured from whole brain white matter lesions and from both lesions and normal appearing white matter of the corpus callosum. Significant differences were found between T1-isointense and black holes (P ranging from 0.005 to <0.001) and between lesions' centre and rim (P < 0.001) for all the metrics. When comparing the three subject groups in terms of metrics derived from corpus callosum normal appearing white matter and T2-hyperintense lesions, a significant difference was found between healthy controls and relapsing-remitting patients for all metrics except restricted fraction and fractional anisotropy; between healthy controls and progressive patients for all metrics except restricted fraction and between relapsing-remitting and progressive multiple sclerosis patients for all metrics except fibres and restricted fractions (P ranging from 0.05 to <0.001 for all). Significant associations were found between corpus callosum normal-appearing white matter fibres fraction/non-restricted fraction and the Symbol Digit Modality Test (respectively, r = 0.35, P = 0.043; r = -0.35, P = 0.046), and between black holes radial diffusivity and Expanded Disability Status Score (r = 0.59, P = 0.002). We showed the feasibility of diffusion basis spectrum imaging metrics at 7 T, confirmed the role of the derived metrics in the characterization of lesions and normal appearing white matter tissue in different stages of the disease and demonstrated their clinical relevance. Thus, suggesting that diffusion basis spectrum imaging is a promising tool to investigate multiple sclerosis pathophysiology, monitor disease progression and treatment response