Long-term neuroprotective effects of natalizumab and fingolimod in multiple sclerosis: Evidence from real-world clinical data.

BACKGROUND: The long-term effect of high efficacy disease modifying therapy (DMT) on neurodegeneration in people with multiple sclerosis (pwMS) is largely unknown. The aim of this study was to evaluate the long-term effect of natalizumab (NTZ) or fingolimod (FTY) therapy on the evolution of brain atrophy compared to moderate efficacy DMT in a real-world clinical setting. METHODS: A total of 438 pwMS with 2,439 MRI exams during treatment were analyzed: 252 pwMS treated with moderate efficacy DMT, 130 with NTZ and 56 with FTY. Evolution of brain atrophy was analyzed over an average follow-up of 6.6 years after treatment initiation. Brain segmentation was performed on clinical 3D-FLAIRs using SynthSeg and regional brain volume changes over time were compared between the treatment groups. RESULTS: Total brain, white matter and deep gray matter atrophy rates did not differ between moderate efficacy DMTs, NTZ and FTY. Annualized ventricle growth rates were lower in pwMS treated with NTZ (1.1 %/year) compared with moderate efficacy DMT (2.4 %/year, p < 0.001) and similar to FTY (2.0 %/year, p = 0.051). Cortical atrophy rates were lower in NTZ (-0.08 %/year) compared with moderate efficacy DMT (-0.16 %/year, p = 0.048). CONCLUSION: In a real-world clinical setting, pwMS treated with NTZ had slower ventricular expansion and cortical atrophy compared to those treated with moderate efficacy DMT.

Multimodal MRI study on the relation between WM integrity and connected GM atrophy and its effect on disability in early multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is characterized by pathology in white matter (WM) and atrophy of grey matter (GM), but it remains unclear how these processes are related, or how they influence clinical progression. OBJECTIVE: To study the spatial and temporal relationship between GM atrophy and damage in connected WM in relapsing-remitting (RR) MS in relation to clinical progression. METHODS: Healthy control (HC) and early RRMS subjects visited our center twice with a 1-year interval for MRI and clinical examinations, including the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC) scores. RRMS subjects were categorized as MSFC decliners or non-decliners based on ΔMSFC over time. Ten deep (D)GM and 62 cortical (C) GM structures were segmented and probabilistic tractography was performed to identify the connected WM. WM integrity was determined per tract with, amongst others, fractional anisotropy (FA), mean diffusivity (MD), neurite density index (NDI), and myelin water fraction (MWF). Linear mixed models (LMMs) were used to investigate GM and WM differences between HC and RRMS, and between MSFC decliners and non-decliners. LMM was also used to test associations between baseline WM z-scores and changes in connected GM z-scores, and between baseline GM z-scores and changes in connected WM z-scores, in HC/RRMS subjects and in MSFC decliners/non-decliners. RESULTS: We included 13 HCs and 31 RRMS subjects with an average disease duration of 3.5 years and a median EDSS of 3.0. Fifteen RRMS subjects showed declining MSFC scores over time, and they showed higher atrophy rates and greater WM integrity loss compared to non-decliners. Lower baseline WM integrity was associated with increased CGM atrophy over time in RRMS, but not in HC subjects. This effect was only seen in MSFC decliners, especially when an extended WM z-score was used, which included FA, MD, NDI and MWF. Baseline GM measures were not significantly related to WM integrity changes over time in any of the groups. DISCUSSION: Lower baseline WM integrity was related to more cortical atrophy in RRMS subjects that showed clinical progression over a 1-year follow-up, while baseline GM did not affect WM integrity changes over time. WM damage, therefore, seems to drive atrophy more than conversely.

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR.

BACKGROUND AND OBJECTIVES: Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images. METHODS: 3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients. RESULTS: The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR. DISCUSSION: In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets.

Temporal evolution of new T1-weighted hypo-intense lesions and central brain atrophy in patients with a first clinical demyelinating event treated with subcutaneous interferon ß-1a.

OBJECTIVE: Evaluate the effect of subcutaneous interferon ß-1a (sc IFN ß-1a) versus placebo on the evolution of T1-weighted MRI lesions and central brain atrophy in in patients with a first clinical demyelinating event (FCDE). METHODS: Post hoc analysis of baseline-to-24 month MRI data from patients with an FCDE who received sc IFN ß-1a 44 µg once- (qw) or three-times-weekly (tiw), or placebo, in REFLEX. Patients were grouped according to treatment regimen or conversion to clinically definite MS (CDMS) status. The intensity of new lesions on unenhanced T1-weighted images was classified as T1 iso- or hypo-intense (black holes) and percentage ventricular volume change (PVVC) was assessed throughout the study. RESULTS: In patients not converting to CDMS, sc IFN ß-1a tiw or qw, versus placebo, reduced the overall number of new lesions (P < 0.001 and P = 0.005) and new T1 iso-intense lesions (P < 0.001 and P = 0.002) after 24 months; only sc IFN ß-1a tiw was associated with fewer T1 hypo-intense lesions versus placebo (P < 0.001). PVVC findings in patients treated with sc IFN ß-1a suggested pseudo-atrophy that was ~ fivefold greater versus placebo in the first year of treatment (placebo 1.11%; qw 4.28%; tiw 6.76%; P < 001); similar findings were apparent for non-converting patients. CONCLUSIONS: In patients with an FCDE, treatment with sc IFN ß-1a tiw for 24 months reduced the number of new lesions evolving into black holes.

Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods.

BACKGROUND: Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants' privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups. METHODS: FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer's Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired t tests. RESULTS: Automated analysis methods failed in 0-19% of cases in FFR-processed images versus 0-2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (p = 0.003) and WMLV (p ≤ 0.001). GBV was lower after QuickShear and Defacing (both p < 0.001). CONCLUSIONS: All three outcome measures were affected differently by FFR, including failure of analysis methods and both "random" variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants' privacy. KEY POINTS: • Protecting participants' privacy when sharing MRI data is important. • Impact of three facial features removal methods on subsequent analysis was assessed in three clinical groups. • Removing facial features degrades performance of image analysis methods.

Comparing lesion segmentation methods in multiple sclerosis: Input from one manually delineated subject is sufficient for accurate lesion segmentation.

PURPOSE: Accurate lesion segmentation is important for measurements of lesion load and atrophy in subjects with multiple sclerosis (MS). International MS lesion challenges show a preference of convolutional neural networks (CNN) strategies, such as nicMSlesions. However, since the software is trained on fairly homogenous training data, we aimed to test the performance of nicMSlesions in an independent dataset with manual and other automatic lesion segmentations to determine whether this method is suitable for larger, multi-center studies. METHODS: Manual lesion segmentation was performed in fourteen subjects with MS on sagittal 3D FLAIR images from a 3T GE whole-body scanner with 8-channel head coil. We compared five different categories of automated lesion segmentation methods for their volumetric and spatial agreement with manual segmentation: (i) unsupervised, untrained (LesionTOADS); (ii) supervised, untrained (LST-LPA and nicMSlesions with default settings); (iii) supervised, untrained with threshold adjustment (LST-LPA optimized for current data); (iv) supervised, trained with leave-one-out cross-validation on fourteen subjects with MS (nicMSlesions and BIANCA); and (v) supervised, trained on a single subject with MS (nicMSlesions). Volumetric accuracy was determined by the intra-class correlation coefficient (ICC) and spatial accuracy by Dice's similarity index (SI). Volumes and SI were compared between methods using repeated measures ANOVA or Friedman tests with post-hoc pairwise comparison. RESULTS: The best volumetric and spatial agreement with manual was obtained with the supervised and trained methods nicMSlesions and BIANCA (ICC absolute agreement > 0.968 and median SI > 0.643) and the worst with the unsupervised, untrained method LesionTOADS (ICC absolute agreement = 0.140 and median SI = 0.444). Agreement with manual in the single-subject network training of nicMSlesions was poor for input with low lesion volumes (i.e. two subjects with lesion volumes ≤ 3.0 ml). For the other twelve subjects, ICC varied from 0.593 to 0.973 and median SI varied from 0.535 to 0.606. In all cases, the single-subject trained nicMSlesions segmentations outperformed LesionTOADS, and in almost all cases it also outperformed LST-LPA. CONCLUSION: Input from only one subject to re-train the deep learning CNN nicMSlesions is sufficient for adequate lesion segmentation, with on average higher volumetric and spatial agreement with manual than obtained with the untrained methods LesionTOADS and LST-LPA.

Validation of mean upper cervical cord area (MUCCA) measurement techniques in multiple sclerosis (MS): High reproducibility and robustness to lesions, but large software and scanner effects.

INTRODUCTION: Atrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking. METHODS: Five methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations. RESULTS: In dataset A, MUCCA differed between MR machines (p < 0.001) and methods (p < 0.001) used, but not between scan sessions. With respect to MUCCA values, Xinapse JIM showed the highest within-scanner reproducibility (ICC absolute agreement = 0.995) while Xinapse JIM and SCT-PropSeg showed the highest between-scanner robustness (ICC consistency = 0.981 and 0.976, respectively). Reproducibility of segmentations between scan sessions was highest in Xinapse JIM and SCT-PropSeg segmentations (median SI ≥ 0.921), with a significant main effect of method (p < 0.001), but not of MR machine or subject group. In dataset B, SI with manual outlines did not differ between patients with or without cervical lesions for any of the segmentation methods (p > 0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p < 0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement = 0.940 and median SI = 0.962). CONCLUSION: Although MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance.

Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia.

OBJECTIVE: To compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD). BACKGROUND: Quantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans. MATERIALS AND METHODS: Manual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20  AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (NCTRL_MCI) and between controls and AD (NCTRL_AD). Finally, reproducibility of hippocampal atrophy rates was assessed using within-session rescans and expressed as an average distance measure DAve, which expresses the difference in atrophy rate, averaged over all subjects. The same DAve was used to determine the agreement between different methods. RESULTS: Except for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: NCTRL_MCI = 115, NCTRL_AD = 17 with DAve = 3.26%; MIRTK: NCTRL_MCI = 97, NCTRL_AD = 11 with DAve = 3.76%), while ANTs was most reproducible (NCTRL_MCI = 162, NCTRL_AD = 37 with DAve = 1.06%), followed by Elastix (NCTRL_MCI = 226, NCTRL_AD = 15 with DAve = 1.78%) and NiftyReg (NCTRL_MCI = 193, NCTRL_AD = 14 with DAve = 2.11%). Manually measured hippocampal atrophy rates required largest sample sizes to detect volume change and were poorly reproduced (NCTRL_MCI = 452, NCTRL_AD = 87 with DAve = 12.39%). Atrophy rates of non-linear registration methods also agreed best with each other. DISCUSSION AND CONCLUSION: Non-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.

Predicting clinical progression in multiple sclerosis after 6 and 12 years.

BACKGROUND AND PURPOSE: To predict disability and cognition in multiple sclerosis (MS) after 6 and 12 years, using early clinical and imaging measures. METHODS: A total of 115 patients with MS were selected and followed up after 2 and 6 years, with 79 patients also being followed up after 12 years. Disability was measured using the Expanded Disability Status Scale (EDSS); cognition was measured only at follow-up using neuropsychological testing. Predictors of interest included EDSS score, baseline brain and lesion volumes and their changes over 2 years, baseline age, clinical phenotype, sex and educational level. RESULTS: Higher 6-year EDSS score was predicted by early EDSS score and whole-brain volume changes and baseline diagnosis of primary progressive MS (adjusted R2  = 0.56). Predictors for 12-year EDSS score included larger EDSS score changes and higher T1-hypointense lesion volumes (adjusted R2  = 0.38). Year 6 cognition was predicted by primary progressive MS phenotype, lower educational level, male sex and early whole-brain atrophy (adjusted R2  = 0.26); year 12 predictors included male sex, lower educational level and higher baseline T1-hypointense lesion volumes (adjusted R2  = 0.14). CONCLUSIONS: Patients with early signs of neurodegeneration and a progressive disease onset were more prone to develop both disability progression and cognitive dysfunction. Male sex and lower educational level only affected cognitive dysfunction, which remains difficult to predict and probably needs more advanced imaging measures.

Inter-observer variation of hippocampus delineation in hippocampal avoidance prophylactic cranial irradiation.

BACKGROUND: Hippocampal avoidance prophylactic cranial irradiation (HA-PCI) techniques have been developed to reduce radiation damage to the hippocampus. An inter-observer hippocampus delineation analysis was performed and the influence of the delineation variability on dose to the hippocampus was studied. MATERIALS AND METHODS: For five patients, seven observers delineated both hippocampi on brain MRI. The intra-class correlation (ICC) with absolute agreement and the generalized conformity index (CIgen) were computed. Median surfaces over all observers' delineations were created for each patient and regional outlining differences were analysed. HA-PCI dose plans were made from the median surfaces and we investigated whether dose constraints in the hippocampus could be met for all delineations. RESULTS: The ICC for the left and right hippocampus was 0.56 and 0.69, respectively, while the CIgen ranged from 0.55 to 0.70. The posterior and anterior-medial hippocampal regions had most variation with SDs ranging from approximately 1 to 2.5 mm. The mean dose (Dmean) constraint was met for all delineations, but for the dose received by 1% of the hippocampal volume (D1%) violations were observed. CONCLUSION: The relatively low ICC and CIgen indicate that delineation variability among observers for both left and right hippocampus was large. The posterior and anterior-medial border have the largest delineation inaccuracy. The hippocampus Dmean constraint was not violated.

Reproducibility of Deep Gray Matter Atrophy Rate Measurement in a Large Multicenter Dataset.

BACKGROUND AND PURPOSE: Precise in vivo measurement of deep GM volume change is a highly demanded prerequisite for an adequate evaluation of disease progression and new treatments. However, quantitative data on the reproducibility of deep GM structure volumetry are not yet available. In this paper we aim to investigate this reproducibility using a large multicenter dataset. MATERIALS AND METHODS: We have assessed the reproducibility of 2 automated segmentation software packages (FreeSurfer and the FMRIB Integrated Registration and Segmentation Tool) by quantifying the volume changes of deep GM structures by using back-to-back MR imaging scans from the Alzheimer Disease Neuroimaging Initiative's multicenter dataset. Five hundred sixty-two subjects with scans at baseline and 1 year were included. Reproducibility was investigated in the bilateral caudate nucleus, putamen, amygdala, globus pallidus, and thalamus by carrying out descriptives as well as multilevel and variance component analysis. RESULTS: Median absolute back-to-back differences varied between GM structures, ranging from 59.6-156.4 µL for volume change, and 1.26%-8.63% for percentage volume change. FreeSurfer had a better performance for the outcome of longitudinal volume change for the bilateral amygdala, putamen, left caudate nucleus (P < .005), and right thalamus (P < .001). For longitudinal percentage volume change, Freesurfer performed better for the left amygdala, bilateral caudate nucleus, and left putamen (P < .001). Smaller limits of agreement were found for FreeSurfer for both outcomes for all GM structures except the globus pallidus. Our results showed that back-to-back differences in 1-year percentage volume change were approximately 1.5-3.5 times larger than the mean measured 1-year volume change of those structures. CONCLUSIONS: Longitudinal deep GM atrophy measures should be interpreted with caution. Furthermore, deep GM atrophy measurement techniques require substantially improved reproducibility, specifically when aiming for personalized medicine.

Brain endothelial cell expression of SPARCL-1 is specific to chronic multiple sclerosis lesions and is regulated by inflammatory mediators in vitro.

AIMS: Cell matrix modulating protein SPARCL-1 is highly expressed by astrocytes during CNS development and following acute CNS damage. Applying NanoLC-MS/MS to CSF of RRMS and SPMS patients, we identified SPARCL-1 as differentially expressed between these two stages of MS, suggesting a potential as CSF biomarker to differentiate RRMS from SPMS and a role in MS pathogenesis. METHODS: This study examines the potential of SPARCL-1 as CSF biomarker discriminating RRMS from SPMS in three independent cohorts (n = 249), analyses its expression pattern in MS lesions (n = 26), and studies its regulation in cultured human brain microvasculature endothelial cells (BEC) after exposure to MS-relevant inflammatory mediators. RESULTS: SPARCL-1 expression in CSF was significantly higher in SPMS compared to RRMS in a Dutch cohort of 76 patients. This finding was not replicated in 2 additional cohorts of MS patients from Sweden (n = 81) and Switzerland (n = 92). In chronic MS lesions, but not active lesions or NAWM, a vessel expression pattern of SPARCL-1 was observed in addition to the expression by astrocytes. EC were found to express SPARCL-1 in chronic MS lesions, and SPARCL-1 expression was regulated by MS-relevant inflammatory mediators in cultured human BEC. CONCLUSIONS: Conflicting results of SPARCL-1's differential expression in CSF of three independent cohorts of RRMS and SPMS patients precludes its use as biomarker for disease progression. The expression of SPARCL-1 by BEC in chronic MS lesions together with its regulation by inflammatory mediators in vitro suggest a role for SPARCL-1 in MS neuropathology, possibly at the brain vascular level.

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context.

BACKGROUND AND PURPOSE: The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. MATERIALS AND METHODS: The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. RESULTS: We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). CONCLUSIONS: The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS.

White Matter Hyperintensity Volume and Cerebral Perfusion in Older Individuals with Hypertension Using Arterial Spin-Labeling.

BACKGROUND AND PURPOSE: White matter hyperintensities of presumed vascular origin in elderly patients with hypertension may be part of a general cerebral perfusion deficit, involving not only the white matter hyperintensities but also the surrounding normal-appearing white matter and gray matter. We aimed to study the relation between white matter hyperintensity volume and CBF and assess whether white matter hyperintensities are related to a general perfusion deficit. MATERIALS AND METHODS: In 185 participants of the Prevention of Dementia by Intensive Vascular Care trial between 72 and 80 years of age with systolic hypertension, white matter hyperintensity volume and CBF were derived from 3D FLAIR and arterial spin-labeling MR imaging, respectively. We compared white matter hyperintensity CBF, normal-appearing white matter CBF, and GM CBF across quartiles of white matter hyperintensity volume and assessed the continuous relation between these CBF estimates and white matter hyperintensity volume by using linear regression. RESULTS: Mean white matter hyperintensity CBF was markedly lower in higher quartiles of white matter hyperintensity volume, and white matter hyperintensity volume and white matter hyperintensity CBF were negatively related (standardized ß = -0.248, P = .001) in linear regression. We found no difference in normal-appearing white matter or GM CBF across quartiles of white matter hyperintensity volume or any relation between white matter hyperintensity volume and normal-appearing white matter CBF (standardized ß = -0.065, P = .643) or GM CBF (standardized ß = -0.035, P = .382) in linear regression. CONCLUSIONS: Higher white matter hyperintensity volume in elderly individuals with hypertension was associated with lower perfusion within white matter hyperintensities, but not with lower perfusion in the surrounding normal-appearing white matter or GM. These findings suggest that white matter hyperintensities in elderly individuals with hypertension relate to local microvascular alterations rather than a general cerebral perfusion deficit.

Regional cortical thinning in multiple sclerosis and its relation with cognitive impairment: A multicenter study.

OBJECTIVES: The objectives of this paper are to compare in a multicenter setting patterns of regional cortical thickness in patients with relapsing-remitting multiple sclerosis (RRMS) and cognitive impairment (CI) and those cognitively preserved (CP), and explore the relationship between cortical thinning and cognitive performance. METHODS: T1-weighted isotropic brain scans were collected at 3T from seven European centers in 60 RRMS patients and 65 healthy controls (HCs). Patients underwent clinical and neuropsychological examinations. Cortical thickness (CTh) measures were calculated using FreeSurfer (failing in four) and both lobar and vertex-based general linear model (GLM) analyses were compared between study groups. RESULTS: Twenty (36%) MS patients were classified as CI. Mean global CTh was smaller in RRMS patients compared to HCs (left 2.43 vs. 2.53 mm, right 2.44 vs. 2.54 mm, p < 0.001). Multivariate GLM regional analysis showed significantly more temporal thinning in CI compared to CP patients. Verbal memory scores correlated to regional cortical thinning in the insula whereas visual memory scores correlated to parietal thinning. CONCLUSIONS: This multicenter study showed mild global cortical thinning in RRMS. The extent of thinning is less pronounced than previously reported. Only subtle regional differences between CI and CP patients were observed, some of which related to specific cognitive domains.

Multicenter Validation of Mean Upper Cervical Cord Area Measurements from Head 3D T1-Weighted MR Imaging in Patients with Multiple Sclerosis.

BACKGROUND AND PURPOSE: Spinal cord atrophy is a common and clinically relevant characteristic in multiple sclerosis. We aimed to perform a multicenter validation study of mean upper cervical cord area measurements in patients with multiple sclerosis and healthy controls from head MR images and to explore the effect of gadolinium administration on mean upper cervical cord area measurements. MATERIALS AND METHODS: We recruited 97 subjects from 3 centers, including 60 patients with multiple sclerosis of different disease types and 37 healthy controls. Both cervical cord and head 3D T1-weighted images were acquired. In 11 additional patients from 1 center, head images before and after gadolinium administration and cervical cord images after gadolinium administration were acquired. The mean upper cervical cord area was compared between cervical cord and head images by using intraclass correlation coefficients (ICC) for both consistency (ICCconsist) and absolute (ICCabs) agreement. RESULTS: There was excellent agreement of mean upper cervical cord area measurements from head and cervical cord images in the entire group (ICCabs = 0.987) and across centers and disease subtypes. The mean absolute difference between the mean upper cervical cord area measured from head and cervical cord images was 2 mm(2) (2.3%). Additionally, excellent agreement was found between the mean upper cervical cord area measured from head images with and without gadolinium administration (ICCabs = 0.991) and between the cervical cord and head images with gadolinium administration (ICCabs = 0.992). CONCLUSIONS: Excellent agreement between mean upper cervical cord area measurements on head and cervical cord images was observed in this multicenter study, implying that upper cervical cord atrophy can be reliably measured from head images. Postgadolinium head or cervical cord images may also be suitable for measuring mean upper cervical cord area.

What drives MRI-measured cortical atrophy in multiple sclerosis?

BACKGROUND: Cortical atrophy, assessed with magnetic resonance imaging (MRI), is an important outcome measure in multiple sclerosis (MS) studies. However, the underlying histopathology of cortical volume measures is unknown. OBJECTIVE: We investigated the histopathological substrate of MRI-measured cortical volume in MS using combined post-mortem imaging and histopathology. METHODS: MS brain donors underwent post-mortem whole-brain in-situ MRI imaging. After MRI, tissue blocks were systematically sampled from the superior and inferior frontal gyrus, anterior cingulate gyrus, inferior parietal lobule, and superior temporal gyrus. Histopathological markers included neuronal, axonal, synapse, astrocyte, dendrite, myelin, and oligodendrocyte densities. Matched cortical volumes from the aforementioned anatomical regions were measured on the MRI, and used as outcomes in a nested prediction model. RESULTS: Forty-five tissue blocks were sampled from 11 MS brain donors. Mean age at death was 68±12 years, post-mortem interval 4±1 hours, and disease duration 35±15 years. MRI-measured regional cortical volumes varied depending on anatomical region. Neuronal density, neuronal size, and axonal density were significant predictors of GM volume. CONCLUSIONS: In patients with long-standing disease, neuronal and axonal pathology are the predominant pathological substrates of MRI-measured cortical volume in chronic MS.

Bidirectional trans-synaptic axonal degeneration in the visual pathway in multiple sclerosis.

OBJECTIVE: To investigate the coexistence of anterograde and retrograde trans-synaptic axonal degeneration, and to explore the relationship between selective visual pathway damage and global brain involvement in longstanding multiple sclerosis (MS). METHODS: In this single-centre, cross-sectional study, patients with longstanding MS (N=222) and healthy controls (HC, N=62) were included. We analysed thickness of retinal layers (optical coherence tomography), damage within optic radiations (OR) (lesion volume and fractional anisotropy and mean diffusivity by diffusion tensor imaging) and atrophy of the visual cortex and that of grey and white matter of the whole-brain (structural MRI). Linear regression analyses were used to assess associations between the different components and for comparing patients with and without optic neuritis and HC. RESULTS: In patients with MS, an episode of optic neuritis (MSON) was significantly associated with decreased integrity of the ORs and thinning of the peripapillary retinal nerve fibre layer (pRNFL) and macular ganglion cell complex (GCC). Lesion volume in the OR was negatively associated with pRNFL and GCC thickness in patients without optic neuritis (MSNON). The pRNFL and GCC showed associations with integrity of the OR, thickness of the primary visual cortex (only in patients with MSON), and also with global white and grey matter atrophy. In HCs, no such relationships were demonstrated. INTERPRETATION: This study provides evidence for presence of bidirectional (both anterograde and retrograde) trans-synaptic axonal degeneration in the visual pathway of patients with MS. Additionally, thinning of the retinal pRNFL and GCC are related to global white and grey matter atrophy in addition to pathology of the visual pathway.

Accurate GM atrophy quantification in MS using lesion-filling with co-registered 2D lesion masks.

BACKGROUND: In multiple sclerosis (MS), brain atrophy quantification is affected by white matter lesions. LEAP and FSL-lesion_filling, replace lesion voxels with white matter intensities; however, they require precise lesion identification on 3DT1-images. AIM: To determine whether 2DT2 lesion masks co-registered to 3DT1 images, yield grey and white matter volumes comparable to precise lesion masks. METHODS: 2DT2 lesion masks were linearly co-registered to 20 3DT1-images of MS patients, with nearest-neighbor (NNI), and tri-linear interpolation. As gold-standard, lesion masks were manually outlined on 3DT1-images. LEAP and FSL-lesion_filling were applied with each lesion mask. Grey (GM) and white matter (WM) volumes were quantified with FSL-FAST, and deep gray matter (DGM) volumes using FSL-FIRST. Volumes were compared between lesion mask types using paired Wilcoxon tests. RESULTS: Lesion-filling with gold-standard lesion masks compared to native images reduced GM overestimation by 1.93 mL (p < .001) for LEAP, and 1.21 mL (p = .002) for FSL-lesion_filling. Similar effects were achieved with NNI lesion masks from 2DT2. Global WM underestimation was not significantly influenced. GM and WM volumes from NNI, did not differ significantly from gold-standard. GM segmentation differed between lesion masks in the lesion area, and also elsewhere. Using the gold-standard, FSL-FAST quantified as GM on average 0.4% of the lesion area with LEAP and 24.5% with FSL-lesion_filling. Lesion-filling did not influence DGM volumes from FSL-FIRST. DISCUSSION: These results demonstrate that for global GM volumetry, precise lesion masks on 3DT1 images can be replaced by co-registered 2DT2 lesion masks. This makes lesion-filling a feasible method for GM atrophy measurements in MS.

Oxysterols and cholesterol precursors correlate to magnetic resonance imaging measures of neurodegeneration in multiple sclerosis.

BACKGROUND: Cholesterol homeostasis is important for formation and maintenance of myelin and axonal membranes in the central nervous system (CNS). The concentrations of the brain specific cholesterol metabolite 24S-hydroxycholesterol (24OHC) and cholesterol precursors have been shown to be altered in multiple sclerosis (MS). However, how changes in sterol levels relate to the pathological processes in MS is not clear. METHODS: In this study, we compared serum and cerebrospinal fluid (CSF) sterol levels between 105 MS (51 relapsing-remitting (RR); 39 secondary progressive (SP) and 15 primary progressive (PP)) and 49 control patients. Sterol levels were correlated to magnetic resonance imaging (MRI) markers of disease activity. RESULTS: We found decreased serum 24OHC and 27-hydroxycholesterol (27OHC) and increased CSF lathosterol in MS patients compared to control patients (p=0.018, p=0.002 and p=0.002, respectively). Subgroup analysis showed that serum 24OHC levels were negatively correlated to normalized brain volume measurements in relapse-onset MS patients (r= -0.326, p=0.004). CONCLUSIONS: These results confirm that cholesterol homeostasis is disturbed in MS and suggest that changes in cholesterol synthesis are related to neurodegenerative pathological processes as seen on the MRI. The data seem to be in line with the recently reported observation that high dose statins may have a positive effect on clinical disability in secondary progressive MS.