Pharmacological blockade of 2-AG degradation ameliorates clinical, neuroinflammatory and synaptic alterations in experimental autoimmune encephalomyelitis.

The endocannabinoid system (ECS) is critically involved in the pathophysiology of Multiple Sclerosis (MS), a neuroinflammatory and neurodegenerative disease of the central nervous system (CNS). Over the past decade, researchers have extensively studied the neuroprotective and anti-inflammatory effects of the ECS. Inhibiting the degradation of the endocannabinoid 2-arachidonoylglycerol (2-AG) has emerged as a promising strategy to mitigate brain damage in MS. In this study, we investigated the effects of a novel reversible MAGL inhibitor (MAGLi 432) on C57/BL6 female mice with experimental autoimmune encephalomyelitis (EAE), a model of MS. We assessed its implications on motor disability, neuroinflammation, and synaptic dysfunction. Systemic in vivo treatment with MAGLi 432 resulted in a less severe EAE disease, accompanied by increased 2-AG levels and decreased levels of arachidonic acid (AA) and prostaglandins (PGs) in the brain. Additionally, MAGLi 432 reduced both astrogliosis and microgliosis, as evidenced by decreased microglia/macrophage density and a less reactive morphology. Flow cytometry analysis further revealed fewer infiltrating CD45+ and CD3+ cells in the brains of MAGLi 432-treated EAE mice. Finally, MAGLi treatment counteracted the striatal synaptic hyperexcitability promoted by EAE neuroinflammation. In conclusion, MAGL inhibition significantly ameliorated EAE clinical disability and striatal inflammatory synaptopathy through potent anti-inflammatory effects. These findings provide new mechanistic insights into the neuroprotective role of the ECS during neuroinflammation and highlight the therapeutic potential of MAGLi-based drugs in mitigating MS-related inflammatory and neurodegenerative brain damage.

Summary of Research: Collaboration Between Healthcare Professionals and People with Multiple Sclerosis to Develop Communication Tools to Improve the Standard of Multiple Sclerosis Care.

This is a summary of a previously published paper: Joint Healthcare Professional and Patient Development of Communication Tools to Improve the Standard of MS Care. It describes a collaboration between people with multiple sclerosis (PwMS) and healthcare professionals (HCPs) to identify challenges in multiple sclerosis (MS) care and design tools to improve communication during consultations.

Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stability.

OBJECTIVES: To develop an automatic method for accurate and robust thalamus segmentation in T1w-MRI for widespread clinical use without the need for strict harmonization of acquisition protocols and/or scanner-specific normal databases. METHODS: A three-dimensional convolutional neural network (3D-CNN) was trained on 1975 T1w volumes from 170 MRI scanners using thalamus masks generated with FSL-FIRST as ground truth. Accuracy was evaluated with 18 manually labeled expert masks. Intra- and inter-scanner test-retest stability were assessed with 477 T1w volumes of a single healthy subject scanned on 123 MRI scanners. The sensitivity of 3D-CNN-based volume estimates for the detection of thalamus atrophy was tested with 127 multiple sclerosis (MS) patients and a normal database comprising 4872 T1w volumes from 160 scanners. The 3D-CNN was compared with a publicly available 2D-CNN (FastSurfer) and FSL. RESULTS: The Dice similarity coefficient of the automatic thalamus segmentation with manual expert delineation was similar for all tested methods (3D-CNN and FastSurfer 0.86 ± 0.02, FSL 0.87 ± 0.02). The standard deviation of the single healthy subject's thalamus volume estimates was lowest with 3D-CNN for repeat scans on the same MRI scanner (0.08 mL, FastSurfer 0.09 mL, FSL 0.15 mL) and for repeat scans on different scanners (0.28 mL, FastSurfer 0.62 mL, FSL 0.63 mL). The proportion of MS patients with significantly reduced thalamus volume was highest for 3D-CNN (24%, FastSurfer 16%, FSL 11%). CONCLUSION: The novel 3D-CNN allows accurate thalamus segmentation, similar to state-of-the-art methods, with considerably improved robustness with respect to scanner-related variability of image characteristics. This might result in higher sensitivity for the detection of disease-related thalamus atrophy. KEY POINTS: • A three-dimensional convolutional neural network was trained for automatic segmentation of the thalamus with a heterogeneous sample of T1w-MRI from 1975 patients scanned on 170 different scanners. • The network provided high accuracy for thalamus segmentation with manual segmentation by experts as ground truth. • Inter-scanner variability of thalamus volume estimates across different MRI scanners was reduced by more than 50%, resulting in increased sensitivity for the detection of thalamus atrophy.

Automated detection of hyperreflective foci in the outer nuclear layer of the retina.

PURPOSE: Hyperreflective foci are poorly understood transient elements seen on optical coherence tomography (OCT) of the retina in both healthy and diseased eyes. Systematic studies may benefit from the development of automated tools that can map and track such foci. The outer nuclear layer (ONL) of the retina is an attractive layer in which to study hyperreflective foci as it has no fixed hyperreflective elements in healthy eyes. In this study, we intended to evaluate whether automated image analysis can identify, quantify and visualize hyperreflective foci in the ONL of the retina. METHODS: This longitudinal exploratory study investigated 14 eyes of seven patients including six patients with optic neuropathy and one with mild non-proliferative diabetic retinopathy. In total, 2596 OCT B-scan were obtained. An image analysis blob detector algorithm was used to detect candidate foci, and a convolutional neural network (CNN) trained on a manually labelled subset of data was then used to select those candidate foci in the ONL that fitted the characteristics of the reference foci best. RESULTS: In the manually labelled data set, the blob detector found 2548 candidate foci, correctly detecting 350 (89%) out of 391 manually labelled reference foci. The accuracy of CNN classifier was assessed by manually splitting the 2548 candidate foci into a training and validation set. On the validation set, the classifier obtained an accuracy of 96.3%, a sensitivity of 88.4% and a specificity of 97.5% (AUC 0.989). CONCLUSION: This study demonstrated that automated image analysis and machine learning methods can be used to successfully identify, quantify and visualize hyperreflective foci in the ONL of the retina on OCT scans.

Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment.

PURPOSE: Total intracranial volume (TIV) is often a nuisance covariate in MRI-based brain volumetry. This study compared two TIV adjustment methods with respect to their impact on z-scores in single subject analyses of regional brain volume estimates. METHODS: Brain parenchyma, hippocampus, thalamus, and TIV were segmented in a normal database comprising 5059 T1w images. Regional volume estimates were adjusted for TIV using the residual method or the proportion method. Age was taken into account by regression with both methods. TIV- and age-adjusted regional volumes were transformed to z-scores and then compared between the two adjustment methods. Their impact on the detection of thalamus atrophy was tested in 127 patients with multiple sclerosis. RESULTS: The residual method removed the association with TIV in all regions. The proportion method resulted in a switch of the direction without relevant change of the strength of the association. The reduction of physiological between-subject variability was larger with the residual method than with the proportion method. The difference between z-scores obtained with the residual method versus the proportion method was strongly correlated with TIV. It was larger than one z-score point in 5% of the subjects. The area under the ROC curve of the TIV- and age-adjusted thalamus volume for identification of multiple sclerosis patients was larger with the residual method than with the proportion method (0.84 versus 0.79). CONCLUSION: The residual method should be preferred for TIV and age adjustments of T1w-MRI-based brain volume estimates in single subject analyses.

Interleukin-6 Receptor Blockade in Treatment-Refractory MOG-IgG-Associated Disease and Neuromyelitis Optica Spectrum Disorders.

BACKGROUND AND OBJECTIVES: To evaluate the long-term safety and efficacy of tocilizumab (TCZ), a humanized anti-interleukin-6 receptor antibody in myelin oligodendrocyte glycoprotein-IgG-associated disease (MOGAD) and neuromyelitis optica spectrum disorders (NMOSD). METHODS: Annualized relapse rate (ARR), Expanded Disability Status Scale score, MRI, autoantibody titers, pain, and adverse events were retrospectively evaluated in 57 patients with MOGAD (n = 14), aquaporin-4 (AQP4)-IgG seropositive (n = 36), and seronegative NMOSD (n = 7; 12%), switched to TCZ from previous immunotherapies, particularly rituximab. RESULTS: Patients received TCZ for 23.8 months (median; interquartile range 13.0-51.1 months), with an IV dose of 8.0 mg/kg (median; range 6-12 mg/kg) every 31.6 days (mean; range 26-44 days). For MOGAD, the median ARR decreased from 1.75 (range 0.5-5) to 0 (range 0-0.9; p = 0.0011) under TCZ. A similar effect was seen for AQP4-IgG+ (ARR reduction from 1.5 [range 0-5] to 0 [range 0-4.2]; p < 0.001) and for seronegative NMOSD (from 3.0 [range 1.0-3.0] to 0.2 [range 0-2.0]; p = 0.031). During TCZ, 60% of all patients were relapse free (79% for MOGAD, 56% for AQP4-IgG+, and 43% for seronegative NMOSD). Disability follow-up indicated stabilization. MRI inflammatory activity decreased in MOGAD (p = 0.04; for the brain) and in AQP4-IgG+ NMOSD (p < 0.001; for the spinal cord). Chronic pain was unchanged. Regarding only patients treated with TCZ for at least 12 months (n = 44), ARR reductions were confirmed, including the subgroups of MOGAD (n = 11) and AQP4-IgG+ patients (n = 28). Similarly, in the group of patients treated with TCZ for at least 12 months, 59% of them were relapse free, with 73% for MOGAD, 57% for AQP4-IgG+, and 40% for patients with seronegative NMOSD. No severe or unexpected safety signals were observed. Add-on therapy showed no advantage compared with TCZ monotherapy. DISCUSSION: This study provides Class III evidence that long-term TCZ therapy is safe and reduces relapse probability in MOGAD and AQP4-IgG+ NMOSD.

A three-year longitudinal study of retinal function and structure in patients with multiple sclerosis.

BACKGROUND: Researchers have in recent years begun to investigate ophthalmological manifestations of multiple sclerosis (MS) other than optic neuritis (ON), and it is now clear that changes to retinal function (measured using the electroretinogram, ERG) and structure (measured using optical coherence tomography, OCT) are found in MS patients irrespective of prior ON episodes. ERG results are consistent with dysfunctional bipolar cells, as in other autoimmune diseases. To date, studies have presented only cross-sectional data regarding ERG and OCT. We, therefore, studied the longitudinal course of ERG and OCT in patients with MS, as well as the effect of disability changes and non-ON clinical relapses on these functional and structural measures. METHODS: MS patients (n = 23) participating in an ongoing longitudinal observational study were invited to take part in a 3-year ophthalmological substudy. ERG and OCT were performed, and measures of MS-related disability and relapse history were obtained. Study visits were repeated annually. ERG peak times, rod b-wave amplitude, mixed rod/cone and cone b-/a-wave amplitude ratios, thickness of the peripapillary retinal nerve fibre layer, and volumes of the segmented retinal layers/complexes were analysed. Using generalised estimating equation models adjusted for age, ON, and MS treatment status, we assessed changes to ERG and OCT over the study duration, the effect of changes in disability and recent non-ON MS relapses on ERG and OCT, and the effect of selected OCT parameters on corresponding ERG parameters. RESULTS: At the group level, small fluctuations of several ERG peak times were recorded, with OCT values remaining stable. Increased disability between visits was associated with significant prolongation of mixed rod-cone ERG b-wave peak times. No evidence of associations between OCT and ERG parameters was observed. CONCLUSIONS: Retinal bipolar cell function may be affected by changes in disability in patients with MS; however, recent non-ON MS clinical relapses appear not to affect ERG or OCT results. As ERG changes in MS patients over 3 years are likely to be small and of uncertain clinical relevance, longitudinal studies of retinal function in MS should be planned over an extended period.

Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networks.

OBJECTIVE: Automated quantification of infratentorial multiple sclerosis lesions on magnetic resonance imaging is clinically relevant but challenging. To overcome some of these problems, we propose a fully automated lesion segmentation algorithm using 3D convolutional neural networks (CNNs). METHODS: The CNN was trained on a FLAIR image alone or on FLAIR and T1-weighted images from 1809 patients acquired on 156 different scanners. An additional training using an extra class for infratentorial lesions was implemented. Three experienced raters manually annotated three datasets from 123 MS patients from different scanners. RESULTS: The inter-rater sensitivity (SEN) was 80% for supratentorial lesions but only 62% for infratentorial lesions. There was no statistically significant difference between the inter-rater SEN and the SEN of the CNN with respect to the raters. For supratentorial lesions, the CNN featured an intra-rater intra-scanner SEN of 0.97 (R1 = 0.90, R2 = 0.84) and for infratentorial lesion a SEN of 0.93 (R1 = 0.61, R2 = 0.73). CONCLUSION: The performance of the CNN improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input and matches the detection performance of experienced raters. Furthermore, for infratentorial lesions the CNN was more robust against repeated scans than experienced raters. KEY POINTS: • A 3D convolutional neural network was trained on MRI data from 1809 patients (156 different scanners) for the quantification of supratentorial and infratentorial multiple sclerosis lesions. • Inter-rater variability was higher for infratentorial lesions than for supratentorial lesions. The performance of the 3D convolutional neural network (CNN) improved significantly for infratentorial lesions when specifically trained on infratentorial lesions using a T1 image as an additional input. • The detection performance of the CNN matches the detection performance of experienced raters.

Optical coherence tomography in multiple sclerosis: A 3-year prospective multicenter study.

OBJECTIVE: To evaluate changes over 3 years in the thickness of inner retinal layers including the peripapillary retinal nerve fiber layer (pRNFL), and combined macular ganglion cell and inner plexiform layers (mGCIPL), in individuals with relapsing-remitting multiple sclerosis (RRMS) versus healthy controls; to determine whether optical coherence tomography (OCT) is sufficiently sensitive and reproducible to detect small degrees of neuroaxonal loss over time that correlate with changes in brain volume and disability progression as measured by the Expanded Disability Status Scale (EDSS). METHODS: Individuals with RRMS from 28 centers (n = 333) were matched with 64 healthy participants. OCT scans were performed on Heidelberg Spectralis machines (at baseline; 1 month; 6 months; 6-monthly thereafter). RESULTS: OCT measurements were highly reproducible between baseline and 1 month (intraclass correlation coefficient >0.98). Significant inner retinal layer thinning was observed in individuals with multiple sclerosis (MS) compared with controls regardless of previous MS-associated optic neuritis--group differences (95% CI) over 3 years: pRNFL: -1.86 (-2.54, -1.17) µm; mGCIPL: -2.03 (-2.78, -1.28) µm (both p < 0.0001; effect sizes 0.39 and 0.34). Greater inner retinal layer atrophy was observed in individuals diagnosed with RRMS <3 years versus >5 years (pRNFL: p < 0.05; mGCIPL: p < 0.01). Brain volume decreased by 1.3% in individuals with MS over 3 years compared to 0.5% in control subjects (effect size 0.76). mGCIPL atrophy correlated with brain atrophy (p < 0.0001). There was no correlation of OCT data with disability progression. INTERPRETATION: OCT has potential to estimate rates of neurodegeneration in the retina and brain. The effect size for OCT, smaller than for magnetic resonance imaging based on Heidelberg Spectralis data acquired in this study, was increased in early disease.

Understanding the impacts of COVID-19 pandemic in people with multiple sclerosis treated with ocrelizumab.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to major challenges in the therapeutic management of patients living with multiple sclerosis (PLwMS), particularly regarding the use of disease-modifying therapies. Despite an extraordinary scientific effort to study SARS-CoV-2 in PLwMS, the heterogeneity of COVID-19 manifestations, immunological mechanisms induced by the natural infection or the vaccines, and the extent of protection through the vaccines, major knowledge gaps remain. Here, we describe the scientific evidence generation plan developed by Roche/Genentech to better understand the impact of the COVID-19 pandemic in PLwMS treated with the B-cell depleting monoclonal antibody ocrelizumab.

APOSTEL 2.0 Recommendations for Reporting Quantitative Optical Coherence Tomography Studies.

OBJECTIVE: To update the consensus recommendations for reporting of quantitative optical coherence tomography (OCT) study results, thus revising the previously published Advised Protocol for OCT Study Terminology and Elements (APOSTEL) recommendations. METHODS: To identify studies reporting quantitative OCT results, we performed a PubMed search for the terms "quantitative" and "optical coherence tomography" from 2015 to 2017. Corresponding authors of the identified publications were invited to provide feedback on the initial APOSTEL recommendations via online surveys following the principle of a modified Delphi method. The results were evaluated and discussed by a panel of experts and changes to the initial recommendations were proposed. A final survey was recirculated among the corresponding authors to obtain a majority vote on the proposed changes. RESULTS: A total of 116 authors participated in the surveys, resulting in 15 suggestions, of which 12 were finally accepted and incorporated into an updated 9-point checklist. We harmonized the nomenclature of the outer retinal layers, added the exact area of measurement to the description of volume scans, and suggested reporting device-specific features. We advised to address potential bias in manual segmentation or manual correction of segmentation errors. References to specific reporting guidelines and room light conditions were removed. The participants' consensus with the recommendations increased from 80% for the previous APOSTEL version to greater than 90%. CONCLUSIONS: The modified Delphi method resulted in an expert-led guideline (evidence Class III; Grading of Recommendations, Assessment, Development and Evaluations [GRADE] criteria) concerning study protocol, acquisition device, acquisition settings, scanning protocol, funduscopic imaging, postacquisition data selection, postacquisition analysis, nomenclature and abbreviations, and statistical approach. It will be essential to update these recommendations to new research and practices regularly.

A randomized study of natalizumab dosing regimens for relapsing-remitting multiple sclerosis.

BACKGROUND: REFINE was an exploratory, dose- and frequency-blinded, prospective, randomized, dose-ranging study in relapsing-remitting multiple sclerosis (RRMS) patients. OBJECTIVE: To examine the efficacy, safety, and tolerability of natalizumab administered via various regimens in RRMS patients. METHODS: Clinically stable RRMS patients previously treated with 300 mg natalizumab intravenously for ⩾12 months were randomized to one of six natalizumab regimens over 60 weeks: 300 mg administered intravenously or subcutaneously every 4 weeks (Q4W), 300 mg intravenously or subcutaneously every 12 weeks (Q12W), or 150 mg intravenously or subcutaneously Q12W. The primary endpoint was the mean cumulative number of combined unique active magnetic resonance imaging (MRI) lesions at week 60. RESULTS: In total, 290 patients were enrolled. All Q12W dosing arms were associated with increased clinical and MRI disease activity and closed early; ⩾39.5% of patients in each Q12W arm met rescue criteria. In the 300 mg intravenous and subcutaneous Q4 W arms, the mean cumulative number of combined unique active MRI lesions was 0.23 and 0.02, respectively; annualized relapse rates were 0.07 and 0.08, respectively; and trough natalizumab serum levels and α4-integrin saturation were comparable. CONCLUSION: Natalizumab 300 mg subcutaneous Q4W was comparable to 300 mg intravenous Q4W dosing with respect to efficacy, pharmacokinetics/pharmacodynamics, and safety.

Structure-Function Relationship of Retinal Ganglion Cells in Multiple Sclerosis.

The retinal ganglion cells (RGC) may be considered an easily accessible pathophysiological site of degenerative processes in neurological diseases, such as the RGC damage detectable in multiple sclerosis (MS) patients with (HON) and without a history of optic neuritis (NON). We aimed to assess and interrelate RGC functional and structural damage in different retinal layers and retinal sites. We included 12 NON patients, 11 HON patients and 14 healthy controls for cross-sectional multifocal pattern electroretinography (mfPERG) and optical coherence tomography (OCT) measurements. Amplitude and peak times of the mfPERG were assessed. Macula and disc OCT scans were acquired to determine macular retinal layer and peripapillary retinal nerve fiber layer (pRNFL) thickness. In both HON and NON patients the foveal N2 amplitude of the mfPERG was reduced compared to controls. The parafoveal P1 peak time was significantly reduced in HON only. For OCT, parafoveal (pfGCL) and perifoveal (pGCL) ganglion cell layer thicknesses were decreased in HON vs. controls, while pRNFL in the papillomacular bundle sector (PMB) showed reductions in both NON and HON. As the mfPERG derived N2 originates from RGC axons, these findings suggest foveal axonal dysfunction not only in HON, but also in NON patients.

Predicting disability worsening in relapsing and progressive multiple sclerosis.

PURPOSE OF REVIEW: Multiple sclerosis (MS) is a clinically heterogeneous disease, which complicates expectant management as well as treatment decisions. This review provides an overview of both well established and emerging predictors of disability worsening, including clinical factors, imaging factors, biomarkers and treatment strategies. RECENT FINDINGS: In addition to well known clinical predictors (age, male sex, clinical presentation, relapse behaviour), smoking, obesity, vascular and psychiatric comorbidities are associated with subsequent disability worsening in persons with MS. A number of imaging features are predictive of disability worsening and are present to varying degrees in relapsing and progressive forms of MS. These include brain volumes, spinal cord atrophy, lesion volumes and optical coherence tomography features. Cerebrospinal and more recently blood biomarkers including neurofilament light show promise as more easily attainable biomarkers of future disability accumulation. Importantly, recent observational studies suggest that initiation of early-intensive therapy, as opposed to escalation based on breakthrough disease, is associated with decreased accumulation of disability overall, although randomized controlled trials investigating this question are underway. SUMMARY: Understanding risk factors associated with disability progression can help to both counsel patients and enhance the clinician's availability to provide evidence-based treatment recommendations.

Effect of Ozanimod on Symbol Digit Modalities Test Performance in Relapsing MS.

BACKGROUND: Cognitive dysfunction, including slowed cognitive processing speed (CPS), is one of the most disabling symptoms of multiple sclerosis (MS). The Symbol Digit Modalities Test (SDMT) is a preferred measure of CPS for MS trials and routine screening. Based on encouraging SDMT results in the phase 3 SUNBEAM trial, these post hoc, exploratory analyses were conducted to further compare effects of the sphingosine 1-phosphate receptor modulator ozanimod versus intramuscular interferon ß-1a on CPS in participants with relapsing multiple sclerosis (RMS). METHODS: In the phase 3, double-blind, double-dummy, SUNBEAM study, adults (aged 18‒55 years) with RMS (N=1,346) were randomized to once-daily oral ozanimod 0.92 or 0.46 mg, or weekly intramuscular interferon ß-1a 30 µg. The study continued until the last participant was treated for 12 months. CPS was measured as part of a secondary endpoint using the SDMT. Exploratory, post hoc analyses evaluated SDMT change and percentages of participants with clinically meaningful (≥4-point) SDMT improvement or worsening at months 6 and 12, and relationship between SDMT and brain volume on magnetic resonance imaging. RESULTS: Ozanimod improved SDMT scores compared with interferon ß-1a at months 6 and 12. At month 12, least squares mean difference in SDMT z-scores for ozanimod 0.92 mg versus interferon ß-1a was 0.102 (95% CI, 0.031‒0.174, nominal p = 0.0051; standardized mean difference = 0.1376). A greater percentage of ozanimod 0.92 mg‒treated participants had clinically meaningful improvements in SDMT scores versus interferon ß-1a at month 6 (30.0% versus 22.2%) and month 12 (35.6% versus 27.9%). Of those with SDMT improvement at month 6, 66.4% of those treated with ozanimod 0.92 mg and 55.9% of those treated with interferon ß-1a had sustained improvement at month 12. Brain volume loss was similar for those with SDMT improvement versus worsening at month 12. CONCLUSIONS: In these exploratory analyses, ozanimod had modestly beneficial effects on CPS in RMS participants. The effects of ozanimod on SDMT are being further evaluated in an ongoing 3-year clinical trial. SUNBEAM is registered on clinicaltrials.gov (NCT02294058) and the European Clinical Trials Database (EudraCT 2014-002320-27).

Age-dependent cut-offs for pathological deep gray matter and thalamic volume loss using Jacobian integration.

INTRODUCTION: Several recent studies indicate that deep gray matter or thalamic volume loss (VL) might be promising surrogate markers of disease activity in multiple sclerosis (MS) patients. To allow applying these markers to individual MS patients in clinical routine, age-dependent cut-offs distinguishing physiological from pathological VL and an estimation of the measurement error, which provides the confidence of the result, are to be defined. METHODS: Longitudinal MRI scans of the following cohorts were analyzed in this study: 189 healthy controls (HC) (mean age 54 years, 22% female), 98 MS patients from Zurich university hospital (mean age 34 years, 62% female), 33 MS patients from Dresden university hospital (mean age 38 years, 60% female), and publicly available reliability data sets consisting of 162 short-term MRI scan-rescan pairs with scan intervals of days or few weeks. Percentage annualized whole brain volume loss (BVL), gray matter (GM) volume loss (GMVL), deep gray matter volume loss (deep GMVL), and thalamic volume loss (ThalaVL) were computed deploying the Jacobian integration (JI) method. BVL was additionally computed using Siena, an established method used in many Phase III drug trials. A linear mixed effect model was used to estimate the measurement error as the standard deviation (SD) of model residuals of all 162 scan-rescan pairs For estimation of age-dependent cut-offs, a quadratic regression function between age and the corresponding annualized VL values of the HC was computed. The 5th percentile was defined as the threshold for pathological VL per year since 95% of HC subjects exhibit a less pronounced VL for a given age. For the MS patients BVL, GMVL, deep GMVL, and ThalaVL were mutually compared and a paired t-test was used to test whether there are systematic differences in VL between these brain regions. RESULTS: Siena and JI showed a high agreement for BVL measures, with a median absolute difference of 0.1% and a correlation coefficient of r = 0.78. Siena and GMVL showed a similar standard deviation (SD) of the scan-rescan error of 0.28% and 0.29%, respectively. For deep GMVL, ThalaVL the SD of the scan-rescan error was slightly higher (0.43% and 0.5%, respectively). Among the HC the thalamus showed the highest mean VL (-0.16%, -0.39%, and -0.59% at ages 35, 55, and 75, respectively). Corresponding cut-offs for a pathological VL/year were -0.68%, -0.91%, and -1.11%. The MS cohorts did not differ in BVL and GMVL. However, both MS cohorts showed a significantly (p = 0.05) stronger deep GMVL than BVL per year. CONCLUSION: It might be methodologically feasible to assess deep GMVL using JI in individual MS patients. However, age and the measurement error need to be taken into account. Furthermore, deep GMVL may be used as a complementary marker to BVL since MS patients exhibit a significantly stronger deep GMVL than BVL.

Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks.

The quantification of new or enlarged lesions from follow-up MRI scans is an important surrogate of clinical disease activity in patients with multiple sclerosis (MS). Not only is manual segmentation time consuming, but inter-rater variability is high. Currently, only a few fully automated methods are available. We address this gap in the field by employing a 3D convolutional neural network (CNN) with encoder-decoder architecture for fully automatic longitudinal lesion segmentation. Input data consist of two fluid attenuated inversion recovery (FLAIR) images (baseline and follow-up) per patient. Each image is entered into the encoder and the feature maps are concatenated and then fed into the decoder. The output is a 3D mask indicating new or enlarged lesions (compared to the baseline scan). The proposed method was trained on 1809 single point and 1444 longitudinal patient data sets and then validated on 185 independent longitudinal data sets from two different scanners. From the two validation data sets, manual segmentations were available from three experienced raters, respectively. The performance of the proposed method was compared to the open source Lesion Segmentation Toolbox (LST), which is a current state-of-art longitudinal lesion segmentation method. The mean lesion-wise inter-rater sensitivity was 62%, while the mean inter-rater number of false positive (FP) findings was 0.41 lesions per case. The two validated algorithms showed a mean sensitivity of 60% (CNN), 46% (LST) and a mean FP of 0.48 (CNN), 1.86 (LST) per case. Sensitivity and number of FP were not significantly different (p < 0.05) between the CNN and manual raters. New or enlarged lesions counted by the CNN algorithm appeared to be comparable with manual expert ratings. The proposed algorithm seems to outperform currently available approaches, particularly LST. The high inter-rater variability in case of manual segmentation indicates the complexity of identifying new or enlarged lesions. An automated CNN-based approach can quickly provide an independent and deterministic assessment of new or enlarged lesions from baseline to follow-up scans with acceptable reliability.

Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNs.

Multiple sclerosis is an inflammatory autoimmune demyelinating disease that is characterized by lesions in the central nervous system. Typically, magnetic resonance imaging (MRI) is used for tracking disease progression. Automatic image processing methods can be used to segment lesions and derive quantitative lesion parameters. So far, methods have focused on lesion segmentation for individual MRI scans. However, for monitoring disease progression, lesion activity in terms of new and enlarging lesions between two time points is a crucial biomarker. For this problem, several classic methods have been proposed, e.g., using difference volumes. Despite their success for single-volume lesion segmentation, deep learning approaches are still rare for lesion activity segmentation. In this work, convolutional neural networks (CNNs) are studied for lesion activity segmentation from two time points. For this task, CNNs are designed and evaluated that combine the information from two points in different ways. In particular, two-path architectures with attention-guided interactions are proposed that enable effective information exchange between the two time point's processing paths. It is demonstrated that deep learning-based methods outperform classic approaches and it is shown that attention-guided interactions significantly improve performance. Furthermore, the attention modules produce plausible attention maps that have a masking effect that suppresses old, irrelevant lesions. A lesion-wise false positive rate of 26.4% is achieved at a true positive rate of 74.2%, which is not significantly different from the interrater performance.

Efficacy and Safety of Alemtuzumab Through 9 Years of Follow-up in Patients with Highly Active Disease: Post Hoc Analysis of CARE-MS I and II Patients in the TOPAZ Extension Study.

BACKGROUND: Alemtuzumab efficacy versus subcutaneous interferon-ß-1a (SC IFNB-1a) was demonstrated over 2 years in patients with relapsing-remitting multiple sclerosis, with continued efficacy over 7 additional years. Alemtuzumab is included as a recommended treatment for patients with highly active disease (HAD) by the American Academy of Neurology Practice Guidelines, and the label indication in Europe was recently restricted to the treatment of HAD patients. There is currently no consensus definition for HAD, and alemtuzumab efficacy across various HAD definitions has not been explored previously. OBJECTIVES: In this post hoc analysis, we assess the efficacy and safety of alemtuzumab in Comparison of Alemtuzumab and Rebif® Efficacy in Multiple Sclerosis (CARE-MS) trial patients who met criteria for at least one of four separate definitions of HAD (one primary and three alternatives). Over 2 years, alemtuzumab-treated HAD patients were compared with SC IFNB-1a-treated HAD patients, with additional 7-year follow-up in patients from the alemtuzumab arm. METHODS: Patients in the CARE-MS studies received either alemtuzumab (baseline: 5 days; 12 months later: 3 days) or SC IFNB-1a (3 times weekly). Alemtuzumab-treated patients who enrolled in the extensions could receive additional courses ≥ 12 months apart. Four definitions of HAD were applied to assess alemtuzumab efficacy: the pre-specified primary definition (two or more relapses in the year prior to baseline and at least one gadolinium [Gd]-enhancing lesion at baseline) and three alternative definitions that focused on relapse, magnetic resonance imaging (MRI), or prior treatment response criteria. Efficacy outcomes were annualized relapse rate, change in Expanded Disability Status Scale score, 6-month confirmed disability worsening, 6-month confirmed disability improvement, MRI disease activity, and brain volume change. Adverse events were summarized for HAD patients meeting the primary definition. RESULTS: In the pooled CARE-MS population, 208 alemtuzumab-treated patients met the primary HAD definition. Annualized relapse rate was 0.27 in years 0-2 and 0.16 in years 3-9. Over 9 years, 62% of patients were free of 6-month confirmed disability worsening, 50% had 6-month confirmed disability improvement, and median cumulative change in brain volume was - 2.15%. During year 9, 62% had no evidence of disease activity, and 69% were free of MRI disease activity. Similar efficacy outcomes were observed using an alternative relapse-driven HAD definition. For patients meeting alternative HAD definitions focused on either higher MRI lesion counts or disease activity while on prior therapy, reduced efficacy for some endpoints was seen. Safety was consistent with the overall CARE-MS population through year 9. CONCLUSIONS: Over 9 years, alemtuzumab efficacy was maintained in CARE-MS HAD patients based on four HAD definitions. These results support intervention with alemtuzumab in patients with early indicators of HAD, including frequent relapse without high MRI activity. No safety signals were observed over 9 years that were unique to the HAD populations. CLINICALTRIALS. GOV IDENTIFIERS: NCT00530348; NCT00548405; NCT00930553; NCT02255656.