Neurological research in Italy from 2020 to 2023.

BACKGROUND: To assess the state of neurological scientific research in Italy in the time interval 2020-2023. METHODS: Elsevier's modular integrated platform "SciVal" was used to analyze bibliometric research products starting from scientific production data uploaded onto Scopus. We considered the research area "Neurology" in the 01/01/2020-14/06/2023 time interval, and the following variables were extracted: number of published studies, number of citations, Field-Weighted Citation Impact, and percentage of international collaborations. The contribution of Italian scientists to the neurological research was compared to that of the other nations. RESULTS: Research identified 90,633 scientific papers in the neurological area worldwide, with a total of 472,750 citations. The products assigned to Italian groups were 6670 (53,587 citations, Field-Weighted Citation Impact 1.68, 41% international collaborations). CONCLUSIONS: According to the present study, Italian neurological research 2020 to 2023 ranks fifth globally and third in Europe.

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.

Peak width of skeletonized mean diffusivity (PSMD) and cognitive functions in relapsing-remitting multiple sclerosis.

Peak width of skeletonized mean diffusivity (PSMD) is a new MRI marker, which has shown clinical relevance in some neurological conditions and, in preliminary data, in multiple sclerosis (MS). We aimed here to investigate, in a group of relapsing-remitting MS (RRMS) patients, the relationship between PSMD and cognitive performances, in comparison with other MRI measures. RRMS patients (n = 60) and normal controls (n = 15) underwent a 3 T MRI examination. MRI-based white matter (WM) lesion volume, microstructural integrity (assessed with Tract-Based Spatial Statistics of diffusion tensor imaging [DTI] images) and brain volumes (i.e., total brain, grey matter [GM] and WM) were computed. In addition, PSMD was calculated through "skeletonization" of WM tracts and diffusion histograms. Cognition was evaluated with Rao's Brief Repeatable Battery (BRB), which incorporated tests of verbal and visual memory, attention, concentration, information processing speed and verbal fluency. PSMD closely correlated with symbol digit modalities test (SDMT) (r = -0.70, p < 0.001) and, to a lesser extent, with verbal and visual memory tests. Multiple regression analysis showed that PSMD explained SDMT variance (R2 = 0.54, p < 0.001) more than other MRI measures. Results point out the relevance of microstructural damage, as assessed by PSMD, as a reliable marker of cognition in MS, especially in explaining dysfunction in information processing speed.

Subclinical motor impairment assessed with an engineered glove correlates with magnetic resonance imaging tissue damage in radiologically isolated syndrome.

BACKGROUND: An engineered glove measuring finger motor performance previously showed ability to discriminate early-stage multiple sclerosis (MS) patients from healthy controls (HCs). Radiologically isolated syndrome (RIS) classifies asymptomatic subjects with brain magnetic resonance imaging (MRI) abnormalities suggestive of multiple sclerosis. METHODS: Seventeen asymptomatic subjects with RIS and 17 HCs were assessed. They performed finger-to-thumb opposition sequences at their maximal velocity, metronome-paced bimanual movements and conventional and diffusion tensor MRI. RESULTS: Subjects with RIS showed lower (P = 0.005) maximal velocity and higher (P = 0.006) bimanual coordination impairment than HCs. In RIS, bimanual coordination correlated with T2-lesion volume, fractional anisotropy and radial diffusivity in the white matter. CONCLUSIONS: These findings point out the relevance of fine hand measures as a robust marker of subclinical disability.

Peak width of skeletonized mean diffusivity (PSMD) as marker of widespread white matter tissue damage in multiple sclerosis.

BACKGROUND: Peak width of skeletonized mean diffusivity (PSMD) is a novel and fully automated, MRI biomarker, which has shown clinical relevance in cerebral small vessel diseases (SVD). We aimed here to assess PSMD levels across the brain of patients with multiple sclerosis (MS), in comparison to normal controls (NC) and patients with CADASIL, a genetically defined form of severe SVD. METHODS: We assessed PSMD in relapsing-remitting (RR) MS patients (n = 47) in comparison to age-matched CADASIL patients (n = 25) and NC (n = 28). Diffusion Tensor Imaging data were acquired on 1.5T MR clinical scanner to automatically compute PSMD through "skeletonization" of WM tracts and diffusion histograms. RESULTS: RRMS had lower WM lesion volume (LV) than CADASIL (8.6 ±â€¯8.2 vs 24.4 ±â€¯17.4 cm3, p < 0.001). After correction for LV, PSMD values in MS were higher than in CADASIL patients (adjusted mean values: 4.5 vs 3.9 × 10-4 mm2/s, p = 0.03) and in both patient groups were higher than in NC (2.8 ±â€¯0.3 × 10-4 mm2/s, p < 0.001). PSMD values correlated with LV in both patient groups (r = 0.8, p < 0.001 in MS; r = 0.6, p = 0.002 in CADASIL). CONCLUSIONS: In both patient groups, PSMD was higher than in NC and closely correlated with LV, suggesting sensitivity in assessing brain tissue damage in these disorders. In MS patients, PSMD levels were higher than in CADASIL patients, despite the lower LV. This might be related to more severe normal-appearing WM abnormalities occurring in the MS brains. This novel, fully automated, MRI metric may represent a useful marker for a robust quantification of the diffuse WM tissue damage in MS.

The Italian Neuroimaging Network Initiative (INNI): enabling the use of advanced MRI techniques in patients with MS.

Magnetic resonance imaging (MRI) is an important paraclinical tool to diagnose and monitor multiple sclerosis (MS). Conventional MRI measures lack of pathological specificity and are weakly correlated with MS clinical manifestations. Advanced MRI techniques are improving the understanding of the mechanisms underlying tissue injury, repair, and functional adaptation in MS; however, they require careful standardization. The definition of standardized methods for the collection and analysis of advanced MRI techniques is central not only to improve the understanding of disease pathophysiology and evolution, but also to generate research hypotheses, monitor treatment, increase cost-effectiveness and power of clinical trials. We promoted the Italian Neuroimaging Network Initiative (INNI), involving centers and investigators with an International recognized expertise, with the major goal to determine and validate novel MRI biomarkers to be utilized as predictors and/or outcomes in future MS studies. The INNI initiative supported the creation of a centralized repository, where advanced structural and functional MRI scans available at the participating sites, with the related clinical and neuropsychological data, are collected. These data will be used to perform research studies to identify clinical, neuropsychological and imaging biomarkers characteristics of the entire spectrum of MS. INNI will be instrumental to help to define standardized MRI and clinical protocols towards an increasing uptake of personalized interventions for people with MS at a national and international level. Upon approval of the INNI Steering Committee, the data collected in the online database will be shared with any research center detailing specific research proposals on disease pathophysiology or treatment effects.

Hippocampal and Deep Gray Matter Nuclei Atrophy Is Relevant for Explaining Cognitive Impairment in MS: A Multicenter Study.

BACKGROUND AND PURPOSE: The structural MR imaging correlates of cognitive impairment in multiple sclerosis are still debated. This study assessed lesional and atrophy measures of white matter and gray matter involvement in patients with MS acquired in 7 European sites to identify the MR imaging variables most closely associated with cognitive dysfunction. MATERIALS AND METHODS: Brain dual-echo, 3D T1-weighted, and double inversion recovery scans were acquired at 3T from 62 patients with relapsing-remitting MS and 65 controls. Patients with at least 2 neuropsychological tests with abnormal findings were considered cognitively impaired. Focal WM and cortical lesions were identified, and volumetric measures from WM, cortical GM, the hippocampus, and deep GM nuclei were obtained. Age- and site-adjusted models were used to compare lesion and volumetric MR imaging variables between patients with MS who were cognitively impaired and cognitively preserved. A multivariate analysis identified MR imaging variables associated with cognitive scores and disability. RESULTS: Twenty-three patients (38%) were cognitively impaired. Compared with those with who were cognitively preserved, patients with MS with cognitive impairment had higher T2 and T1 lesion volumes and a trend toward a higher number of cortical lesions. Significant brain, cortical GM, hippocampal, deep GM nuclei, and WM atrophy was found in patients with MS with cognitive impairment versus those who were cognitively preserved. Hippocampal and deep GM nuclei atrophy were the best predictors of cognitive impairment, while WM atrophy was the best predictor of disability. CONCLUSIONS: Hippocampal and deep GM nuclei atrophy are key factors associated with cognitive impairment in MS. These MR imaging measures could be applied in a multicenter context, with cognition as clinical outcome.

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.

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.

Fingolimod effect on brain volume loss independently contributes to its effect on disability.

BACKGROUND: Brain volume loss occurs in patients with relapsing-remitting MS. Fingolimod reduced brain volume loss in three phase 3 studies. OBJECTIVE: To evaluate whether the effect of fingolimod on disability progression was mediated by its effects on MRI lesions, relapses or brain volume loss, and the extent of this effect. METHODS: Patients (992/1272; 78%) from the FTY720 Research Evaluating Effects of Daily Oral Therapy in Multiple Sclerosis (FREEDOMS) study were analyzed. Month-24 percentage brain volume change, month-12 MRI-active lesions and relapse were assessed. The Prentice criteria were used to test surrogate marker validity. The proportion of treatment effect on disability progression explained by each marker was calculated. RESULTS: Two-year disability progression was associated with active T2 lesions (OR = 1.24; p = 0.001) and more relapses during year 1 (OR = 2.90; p < 0.001) and lower percentage brain volume change over two years (OR = 0.78; p < 0.001). Treatment effect on active T2 lesions, relapses and percentage brain volume change explained 46%, 60% and 23% of the fingolimod effect on disability. Multivariate analysis showed the number of relapses during year 1 (OR = 2.62; p < 0.001) and yearly percentage brain volume change over two years (OR = 0.85; p = 0.009) were independent predictors of disability progression, together explaining 73% of fingolimod effect on disability. CONCLUSIONS: The treatment effect on relapses and, to a lesser extent, brain volume loss were both predictors of treatment effect on disability; combining these predictors better explained the effect on disability than either factor alone.

Predicting outcome in clinically isolated syndrome using machine learning.

We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clinically isolated syndrome (CIS), on the basis of single patient's lesion features and clinical/demographic characteristics. Seventy-four patients at onset of CIS were scanned and clinically reviewed after one and three years. CDMS was used as the gold standard against which SVM classification accuracy was tested. Radiological features related to lesional characteristics on conventional MRI were defined a priori and used in combination with clinical/demographic features in an SVM. Forward recursive feature elimination with 100 bootstraps and a leave-one-out cross-validation was used to find the most predictive feature combinations. 30 % and 44 % of patients developed CDMS within one and three years, respectively. The SVMs correctly predicted the presence (or the absence) of CDMS in 71.4 % of patients (sensitivity/specificity: 77 %/66 %) at 1 year, and in 68 % (60 %/76 %) at 3 years on average over all bootstraps. Combinations of features consistently gave a higher accuracy in predicting outcome than any single feature. Machine-learning-based classifications can be used to provide an "individualised" prediction of conversion to MS from subjects' baseline scans and clinical characteristics, with potential to be incorporated into routine clinical practice.

Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis.

Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy and sensitivity will reduce the numbers of patients required to detect a given treatment effect in a trial, and ultimately, will allow reliable characterization of individual patients for personalized treatment. Based on open issues in the field of MS research, and the current state of the art in magnetic resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image contrasts to allow more comprehensive analyses of lesion load and atrophy, across timepoints. Image artifacts need special attention given their effects on image analysis results. (2) Automated image segmentation methods integrating the assessment of lesion load and atrophy are desirable. (3) A standard dataset with benchmark results should be set up to facilitate development, calibration, and objective evaluation of image analysis methods for MS.

Time to first relapse as an endpoint in multiple sclerosis clinical trials.

BACKGROUND: The increasing number of effective therapies to treat multiple sclerosis (MS) raises ethical concerns for the use of placebo in clinical trials, suggesting that new clinical trial design strategies are needed. OBJECTIVES: To evaluate time to first relapse as an endpoint for MS clinical trials. METHODS: A recently-developed model fitting the distribution of time to first relapse in MS was used for simulations estimating the sample sizes of trials using this as an outcome, and for comparison with the size of trials using the annualized relapse rate (ARR) as the primary outcome. RESULTS: Trials based on time to first relapse were feasible, requiring sample sizes that were similar or even smaller than if the study was based on ARR instead. In the case of low ARR (0.4 relapses/year), as is expected in future trials, the 1-year trials designed to detect a treatment effect of 30%, with 90% power, require fewer patients when based on time to first relapse (470 patients/arm) than if based on ARR (540 patients/arm). CONCLUSIONS: Our simulations show that time to first relapse is not less powerful than ARR in MS trials; thus, this measure would be a potentially useful primary outcome offering the advantage of an ethically sound design, as the patients randomized to placebo can then switch to the active drug, once they relapse. A potential drawback is the loss of information for other endpoints collected at fixed time points.

Scoring treatment response in patients with relapsing multiple sclerosis.

BACKGROUND: We employed clinical and magnetic resonance imaging (MRI) measures in combination, to assess patient responses to interferon in multiple sclerosis. OBJECTIVE: To optimize and validate a scoring system able to discriminate responses to interferon treatment in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: Our analysis included two large, independent datasets of RRMS patients who were treated with interferons that included 4-year follow-up data. The first dataset ("training set") comprised of 373 RRMS patients from a randomized clinical trial of subcutaneous interferon beta-1a. The second ("validation set") included an observational cohort of 222 RRMS patients treated with different interferons. The new scoring system, a modified version of that previously proposed by Rio et al., was first tested on the training set, then validated using the validation set. The association between disability progression and risk group, as defined by the score, was evaluated by Kaplan Meier survival curves and Cox regression, and quantified by hazard ratios (HRs). RESULTS: The score (0-3) was based on the number of new T2 lesions (>5) and clinical relapses (0,1 or 2) during the first year of therapy. The risk of disability progression increased with higher scores. In the validation set, patients with score of 0 showed a 3-year progression probability of 24%, while those with a score of 1 increased to 33% (HR = 1.56; p = 0.13), and those with score greater than or equal to 2 increased to 65% (HR = 4.60; p < 0.001). CONCLUSIONS: We report development of a simple, quantitative and complementary tool for predicting responses in interferon-treated patients that could help clinicians make treatment decisions.

Natalizumab may reduce cognitive changes and brain atrophy rate in relapsing-remitting multiple sclerosis--a prospective, non-randomized pilot study.

BACKGROUND AND PURPOSE: The development of treatment strategies for cognitive impairment in multiple sclerosis (MS) is still in its infancy. The objective of this prospective, non-randomized, pilot study was to assess the possible efficacy of treatment with natalizumab in comparison with interferon beta (IFNB) in a group of relapsing-remitting patients with MS. METHODS: We included 12 patients treated with natalizumab and 14 with IFNB. At baseline and at follow-up, cognitive functioning was assessed through Rao's Brief Repeatable Battery. All the patients underwent brain MR study with the assessment of T2 lesion volumes, neocortical volume, normalized brain volume and percentage brain volume change (PBVC). Evolution of cognitive performance was assessed using available normative data for the Italian population. Treatment comparisons were assessed through the Mann-Whitney U-test, anova for repeated measures and linear multivariate regression analyses. RESULTS: After a mean follow-up of 1.5 years, the mean number of neuropsychological tests with a deteriorating performance was significantly lower in patients treated with natalizumab (0.7 ± 0.7 vs. 1.7 ± 1.4; P = 0.031). Likewise, PBVC was significantly lower in natalizumab-treated subjects than that observed in patients treated with IFNB (-0.51% ± 0.47% vs. -1.18% ± 0.98%; P = 0.050). CONCLUSION: Our results suggest a potential beneficial effect of natalizumab therapy on cognitive functioning in MS, possibly mediated by a reduction of brain atrophy.

Magnetic resonance imaging in Alzheimer's disease: from diagnosis to monitoring treatment effect.

Quantitative outcome variables in Alzheimer's disease (AD) are of interest because of their low longitudinal variability compared with that of repeated clinical and cognitive measurements. Conventional MR-based volumetry of structures within and beyond the medial temporal lobe has proven to be useful in the diagnostic work up of early AD patients, and measures of atrophy have the potential to monitor the efficacy of disease-modifying agents. The extensive application of new non-conventional MR-based techniques to the study of AD, such as proton magnetic resonance spectroscopy, diffusion tensor MRI, and functional MRI, has undoubtedly improved our understanding of the pathophysiology of the disease, and might lead to the identification of additional useful markers of disease progression. This review summarizes the main results obtained from the application of conventional and non-conventional MRI in AD patients, and supports their more extensive use in studies of disease evolution and clinical trials.

Optimizing parameter choice for FSL-Brain Extraction Tool (BET) on 3D T1 images in multiple sclerosis.

BACKGROUND: Brain atrophy studies often use FSL-BET (Brain Extraction Tool) as the first step of image processing. Default BET does not always give satisfactory results on 3DT1 MR images, which negatively impacts atrophy measurements. Finding the right alternative BET settings can be a difficult and time-consuming task, which can introduce unwanted variability. AIM: To systematically analyze the performance of BET in images of MS patients by varying its parameters and options combinations, and quantitatively comparing its results to a manual gold standard. METHODS: Images from 159 MS patients were selected from different MAGNIMS consortium centers, and 16 different 3DT1 acquisition protocols at 1.5 T or 3T. Before running BET, one of three pre-processing pipelines was applied: (1) no pre-processing, (2) removal of neck slices, or (3) additional N3 inhomogeneity correction. Then BET was applied, systematically varying the fractional intensity threshold (the "f" parameter) and with either one of the main BET options ("B" - bias field correction and neck cleanup, "R" - robust brain center estimation, or "S" - eye and optic nerve cleanup) or none. For comparison, intracranial cavity masks were manually created for all image volumes. FSL-FAST (FMRIB's Automated Segmentation Tool) tissue-type segmentation was run on all BET output images and on the image volumes masked with the manual intracranial cavity masks (thus creating the gold-standard tissue masks). The resulting brain tissue masks were quantitatively compared to the gold standard using Dice overlap coefficient (DOC). Normalized brain volumes (NBV) were calculated with SIENAX. NBV values obtained using for SIENAX other BET settings than default were compared to gold standard NBV with the paired t-test. RESULTS: The parameter/preprocessing/options combinations resulted in 20,988 BET runs. The median DOC for default BET (f=0.5, g=0) was 0.913 (range 0.321-0.977) across all 159 native scans. For all acquisition protocols, brain extraction was substantially improved for lower values of "f" than the default value. Using native images, optimum BET performance was observed for f=0.2 with option "B", giving median DOC=0.979 (range 0.867-0.994). Using neck removal before BET, optimum BET performance was observed for f=0.1 with option "B", giving median DOC 0.983 (range 0.844-0.996). Using the above BET-options for SIENAX instead of default, the NBV values obtained from images after neck removal with f=0.1 and option "B" did not differ statistically from NBV values obtained with gold-standard. CONCLUSION: Although default BET performs reasonably well on most 3DT1 images of MS patients, the performance can be improved substantially. The removal of the neck slices, either externally or within BET, has a marked positive effect on the brain extraction quality. BET option "B" with f=0.1 after removal of the neck slices seems to work best for all acquisition protocols.