Evolution from a first clinical demyelinating event to multiple sclerosis in the REFLEX trial: Regional susceptibility in the conversion to multiple sclerosis at disease onset and its amenability to subcutaneous interferon beta-1a

BACKGROUND AND PURPOSE: In the REFLEX trial (ClinicalTrials.gov identifier: NCT00404352), patients with a first clinical demyelinating event (FCDE) displayed significantly delayed onset of multiple sclerosis (MS; McDonald criteria) when treated with subcutaneous interferon β-1a (scIFNβ-1a) versus placebo. This post hoc analysis evaluated the effect of scIFNβ-1a on spatio-temporal evolution of disease activity, assessed by changes in T2 lesion distribution, in specific brain regions of such patients and its relationship with conversion to MS. METHODS: Post hoc analysis of baseline and 24-month MRI data from FCDE patients who received scIFNβ-1a 44 μg once or three times weekly, or placebo in the REFLEX trial. Patients were grouped according to McDonald MS status (converter/non-converter) or treatment (scIFNβ-1a/placebo). For each patient group, a baseline lesion probability map (LPM) and longitudinal new/enlarging and shrinking/disappearing LPMs were created. Lesion location/frequency of lesion occurrence were assessed in the white matter (WM). RESULTS: At Month 24, lesion frequency was significantly higher in the anterior thalamic radiation (ATR) and corticospinal tract (CST) of converters versus non-converters (p<0.05). Additionally, the overall distribution of new/enlarging lesions across the brain at Month 24 was similar in placebo- and scIFNβ-1a-treated patients (ratio: 0.95). Patients treated with scIFNβ-1a versus placebo showed significantly lower new lesion frequency in specific brain regions (cluster corrected): ATR (p=0.025), superior longitudinal fasciculus (p=0.042), CST (p=0.048), and inferior longitudinal fasciculus (p=0.048). CONCLUSIONS: T2 lesion distribution in specific brain locations predict conversion to McDonald MS and show significantly reduced new lesion occurrence after treatment with scIFNβ-1a in an FCDE population

Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study

We investigated the ability of cortical and subcortical gray matter (GM) atrophy in combination with white matter (WM) integrity to distinguish behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) and from controls using voxel-based morphometry, subcortical structure segmentation, and tract-based spatial statistics. To determine which combination of MR markers differentiated the three groups with the highest accuracy, we conducted discriminant function analyses. Adjusted for age, sex and center, both types of dementia had more GM atrophy, lower fractional anisotropy (FA) and higher mean (MD), axial (L1) and radial diffusivity (L23) values than controls. BvFTD patients had more GM atrophy in orbitofrontal and inferior frontal areas than AD patients. In addition, caudate nucleus and nucleus accumbens were smaller in bvFTD than in AD. FA values were lower; MD, L1 and L23 values were higher, especially in frontal areas of the brain for bvFTD compared to AD patients. The combination of cortical GM, hippocampal volume and WM integrity measurements, classified 97-100% of controls, 81-100% of AD and 67-75% of bvFTD patients correctly. Our results suggest that WM integrity measures add complementary information to measures of GM atrophy, thereby improving the classification between AD and bvFTD

Postmortem Validation of MRI Cortical Volume Measurements in MS

Grey matter (GM) atrophy is a prominent aspect of multiple sclerosis pathology and an important outcome in studies. GM atrophy measurement requires accurate GM segmentation. Several methods are used in vivo for measuring GM volumes in MS, but assessing their validity in vivo remains challenging. In this postmortem study, we evaluated the correlation between postmortem MRI cortical volume or thickness and the cortical thickness measured on histological sections. Sixteen MS brains were scanned in situ using 3DT1‐weighted MRI and these images were used to measure regional cortical volume using FSL‐SIENAX, FreeSurfer, and SPM, and regional cortical thickness using FreeSurfer. Subsequently, cortical thickness was measured histologically in 5 systematically sampled cortical areas. Linear regression analyses were used to evaluate the relation between MRI regional cortical volume or thickness and histological cortical thickness to determine which postprocessing technique was most valid. After correction for multiple comparisons, we observed a significant correlation with the histological cortical thickness for FSL‐SIENAX cortical volume with manual editing (std. β = 0.345, adjusted R2 = 0.105, P = 0.005), and FreeSurfer cortical volume with manual editing (std. β = 0.379, adjusted R2 = 0.129, P = 0.003). In addition, there was a significant correlation between FreeSurfer cortical thickness with manual editing and histological cortical thickness (std. β = 0.381, adjusted R2 = 0.130, P = 0.003). The results support the use of FSL‐SIENAX and FreeSurfer in cases of severe MS pathology. Interestingly none of the methods were significant in automated mode, which supports the use of manual editing to improve the automated segmentation

Thinner temporal and parietal cortex is related to incident clinical progression to dementia in patients with subjective cognitive decline

INTRODUCTION: We aimed to investigate if thinner cortex of the Alzheimer's disease (AD)-signature region was related to clinical progression in patients with subjective cognitive decline (SCD). METHODS: We included 302 SCD patients with clinical follow-up (≥1 year) and three-dimensional T1 magnetic resonance imaging. We estimated AD-signature cortical thickness, consisting of nine frontal, parietal, and temporal gyri and hippocampal volume. We used Cox proportional hazard models (hazard ratios and 95% confidence intervals) to evaluate cortical thickness in relation to clinical progression to mild cognitive impairment (MCI) or dementia. RESULTS: After a follow-up of the mean (standard deviation) 3 (2) years, 49 patients (16%) showed clinical progression to MCI (n = 32), AD (n = 9), or non-AD dementia (n = 8). Hippocampal volumes, thinner cortex of the AD-signature (hazard ratio [95% confidence interval], 5 [2-17]) and various AD-signature subcomponents were associated with increased risk of clinical progression. Stratified analyses showed that thinner AD-signature cortex was specifically predictive for clinical progression to dementia but not to MCI. DISCUSSION: In SCD patients, thinner regional cortex is associated with clinical progression to dementia

Validation of a semi-automated method to quantify lesion volume changes in multiple sclerosis on 2D proton-density-weighted scans based on image subtraction

Background: The detection and quantification of changes in white matter lesions in the brain is important to monitor treatment effects in patients with multiple sclerosis (MS). Existing automatic tools predominantly require FLAIR images as input which are not always available, or only focus on new/enlarging activity. Therefore, we developed and validated a semi-automated method to quantify lesion volume changes based on 2D proton-density (PD)-weighted images and image subtraction. This semi-automated method provides insight in both “positive” activity (defined as new and enlarging lesions) and “negative” activity (disappearing and shrinking lesions). Methods: Yearly MRI scans of patients with early MS from the REFLEX/REFLEXION studies were used. The maximum follow-up period was 5 years. Two PD-weighted images were normalized, registered to a common halfway-space, intensity-matched, and subsequently subtracted. Within manual lesion masks, lesion changes were quantified using a subtraction intensity threshold and total lesion volume change (TLVC) was calculated. Reproducibility was measured by assessing transitivity, specifically, we calculated the intraclass correlation coefficient for the absolute agreement (ICCtrans) and the difference (Δtrans) between the direct one-step and indirect multi-step measurements of TLVC between two visits. Accuracy was assessed by calculating both the intraclass correlation coefficient for absolute agreement (ICCacc) and the difference (Δacc) between the one-step semi-automated TLVC and manually measured lesion volume change (numerical difference) between two visits. Spearman's correlations (rs) were used to assess the relation of global and central atrophy, manually measured T2 lesion volume, and lesion volume change with the method's performance as reflected by the difference measures |Δtrans| and Δacc. An alpha of 0.05 was used as the cut-off for significance. Results: Reproducibility was excellent, with ICCtrans values ranging from 0.90 to 0.96. Accuracy was good overall, with ICCacc values ranging from 0.67 to 0.86. The standard deviation of Δtrans ranged from 0.25 to 0.86 mL. The mean of Δacc ranged from 0.11 to 0.37 mL and was significantly different from zero. Both global and central atrophy significantly correlated with lower reproducibility (correlation of |Δtrans| with global atrophy, rs = −0.19 to −0.28, and correlation of |Δtrans| with central atrophy, rs = 0.22 to 0.34). There was generally no significant correlation between global/central atrophy and accuracy. Higher lesion volume was significantly correlated with lower reproducibility (rs = 0.62). Higher lesion volume change was significantly correlated with lower reproducibility (rs = 0.22) and lower accuracy (correlation of Δacc with lesion volume change, rs = −0.52). Discussion: The semi-automated method to quantify lesion volume changes has excellent reproducibility and overall good accuracy. The amount of atrophy and especially lesion volume (change) should be taken into account when applying this method, as an increase in these variables might affect the quality of the results. Conclusion: Overall, the semi-automated subtraction method allows a valid and reliable quantitative investigation of lesion volume changes over time in (early) MS for follow-up periods up to 5 years

Grey Matter Atrophy in Multiple Sclerosis: Clinical Interpretation Depends on Choice of Analysis Method

Aim To examine the consistency between FSL, FreeSurfer, SPM for GM atrophy measurement (for volumes, patient/control discrimination, and correlations with cognition). Materials and Methods 127 MS patients and 50 controls were included and cortical and deep grey matter (DGM) volumetrics were performed. Consistency of volumes was assessed with Intraclass Correlation Coefficient/ICC. Consistency of patients/controls discrimination was assessed with Cohen’s d, t-tests, MANOVA and a penalized double-loop logistic classifier. Consistency of association with cognition was assessed with Pearson correlation coefficient and ANOVA. Voxel-based morphometry (SPM-VBM and FSL-VBM) and vertex-wise FreeSurfer were used for group-level comparisons. Results The highest volumetry ICC were between SPM and FreeSurfer for cortical regions, and the lowest between SPM and FreeSurfer for DGM. The caudate nucleus and temporal lobes had high consistency between all software, while amygdala had lowest volumetric consistency. Consistency of patients/controls discrimination was largest in the DGM for all software, especially for thalamus and pallidum. The penalized double-loop logistic classifier most often selected the thalamus, pallidum and amygdala for all software. FSL yielded the largest number of significant correlations. DGM yielded stronger correlations with cognition than cortical volumes. Bilateral putamen and left insula volumes correlated with cognition using all methods. Conclusion GM volumes from FreeSurfer, FSL and SPM are different, especially for cortical regions. While group-level separation between MS and controls is comparable, correlations between regional GM volumes and clinical/cognitive variables in MS should be cautiously interpreted