Choroid plexus volume differentiates MS from its mimics.

This study aimed to determine whether choroid plexus volume (CPV) could differentiate multiple sclerosis (MS) from its mimics. A secondary analysis of two previously enrolled studies, 50 participants with MS and 64 with alternative diagnoses were included. CPV was automatically segmented from 3T magnetic resonance imaging (MRI), followed by manual review to remove misclassified tissue. Mean normalized choroid plexus volume (nCPV) to intracranial volume demonstrated relatively high specificity for MS participants in each cohort (0.80 and 0.76) with an area under the receiver-operator characteristic curve of 0.71 (95% confidence interval (CI) = 0.55-0.87) and 0.65 (95% CI = 0.52-0.77). In this preliminary study, nCPV differentiated MS from its mimics.

A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis.

BACKGROUND: The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE: The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS: Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS: Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION: A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.

A Characterization of Neurology Consults for Inpatients with SARS-CoV-2 Infection Compared to Other Respiratory Viruses.

Introduction: Neurological consultation for patients infected with SARS-CoV-2 is common; it is currently unknown whether the neurologist's approach to inpatient consultation of patients with SARS-CoV-2 should differ from the paradigm used to evaluate hospitalized patients with similar respiratory viruses. The goal of the present study is to determine if the preponderance of new neurologic diagnoses differs between inpatients with SARS-CoV-2 and similar non-SARS-CoV-2 respiratory viruses for whom neurology is consulted. Methods: We performed a retrospective chart analysis of inpatient neurologic consultations at three major Philadelphia-based hospitals. We compared the final neurologic diagnosis of 152 patients infected with SARS-CoV-2 to 54 patients with a similar ubiquitous non-SARS-CoV-2 respiratory virus (influenza A, influenza B, respiratory syncytial virus, rhinovirus, or adenovirus, the most commonly tested respiratory viruses at our institution). Secondary metrics included age, sex, level of care, prior neurologic diagnoses, and mortality. A multinomial logistic regression model was utilized to evaluate the relative difference between diagnostic category groups on all metrics. Results: The proportion of patients with seizure who were infected with SARS-CoV-2 admitted to an intensive care unit (ICU) was significantly higher than those who were admitted to a medical-surgical floor. SARS-CoV-2 was also associated with increased risk for ICU admission compared to other common respiratory viruses. SARS-CoV-2 inpatients requiring neurologic consultation were also more likely to be older and female as compared to the non-SARS-CoV-2 cohort. In other domains, the proportion of neurologic diagnoses between SAR-CoV-2 and non-SARS-CoV-2 respiratory viruses showed no significant difference. Conclusion: Patients requiring inpatient neurologic consultation with a diagnosis of SARS-CoV-2 infection or another respiratory virus were found to be remarkably similar in terms of their ultimate neurologic diagnosis, with the exception of a larger preponderance of seizure in critical-care-level patients with SARS-CoV-2 infection. Our study suggests that the neurological approach to patients hospitalized with SARS-CoV-2 should be similar to that for patients with similar common respiratory infections, noting that seizure was seen more frequently in critically ill patients infected with SARS-CoV-2.

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis.

BACKGROUND: Multiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS. METHODS: Using electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain. RESULTS: MS lesions preferentially affected fascicles within versus outside the depression network (ß = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (ß = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (ß = 0.02, 95% CI = 0.003 to 0.040, p = .020). CONCLUSIONS: We demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis.

BACKGROUND AND PURPOSE: Multicenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites. METHODS: Images were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole-brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization-prepared rapid acquisition gradient echo and T2 fluid-attenuated inversion recovery lesions. Random-effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. RESULTS: Random-effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. CONCLUSION: Differences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.

Severe Neuroinvasive West Nile Virus in Association With Anti-CD20 Monotherapy for Multiple Sclerosis.

OBJECTIVES: The objective of this study was to report on the development of neuroinvasive West Nile virus (WNV) infection in the context of anti-CD20 monotherapy for multiple sclerosis (MS). METHODS: This is a case series study. RESULTS: In 2021-2022, we observed 4 cases of neuroinvasive WNV infection in our patient population of 2009 patients with MS on ocrelizumab, compared with a total of 46 cases of neuroinvasive WNV infection reported in Pennsylvania and 40 in New Jersey. Odds were 258 times that of the general population (95% confidence interval 97-691), χ2 p < 0.0001). All were women aged 41-61 years with variable disease duration, level of disability, and duration of anti-CD20 therapy. All presented in summer/early fall with fever, headache, and encephalopathy consistent with meningoencephalitis. Three patients had acute cerebellitis. Two had anterior nerve root involvement progressing to quadriparesis, and 1 developed refractory nonconvulsive status epilepticus. All required intubation and experienced significant morbidity. All had CSF pleocytosis. Two patients were WNV IgM positive in both the serum and CSF, 1 patient had positive serum IgM and CSF metagenomic next-generation sequencing (mNGS), while 1 had positive CSF mNGS with negative serum and CSF antibodies. DISCUSSION: Neuroinvasive WNV infection can develop with anti-CD20 monotherapy in the absence of additional immunosuppression. WNV serologies may be negative in the setting of anti-CD20 treatment; in the appropriate clinical context, one should consider direct detection methods such as PCR or mNGS-based testing.

Mapping the relationship of white matter lesions to depression in multiple sclerosis.

Importance: Multiple sclerosis (MS) is an immune-mediated neurological disorder that affects nearly one million people in the United States. Up to 50% of patients with MS experience depression. Objective: To investigate how white matter network disruption is related to depression in MS. Design: Retrospective case-control study of participants who received research-quality 3-tesla neuroimaging as part of MS clinical care from 2010-2018. Analyses were performed from May 1 to September 30, 2022. Setting: Single-center academic medical specialty MS clinic. Participants: Participants with MS were identified via the electronic health record (EHR). All participants were diagnosed by an MS specialist and completed research-quality MRI at 3T. After excluding participants with poor image quality, 783 were included. Inclusion in the depression group (MS+Depression) required either: 1) ICD-10 depression diagnosis (F32-F34.*); 2) prescription of antidepressant medication; or 3) screening positive via Patient Health Questionnaire-2 (PHQ-2) or -9 (PHQ-9). Age- and sex-matched nondepressed comparators (MS-Depression) included persons with no depression diagnosis, no psychiatric medications, and were asymptomatic on PHQ-2/9. Exposure: Depression diagnosis. Main Outcomes and Measures: We first evaluated if lesions were preferentially located within the depression network compared to other brain regions. Next, we examined if MS+Depression patients had greater lesion burden, and if this was driven by lesions specifically in the depression network. Outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain. Secondary measures included between-diagnosis lesion burden, stratified by brain network. Linear mixed-effects models were employed. Results: Three hundred-eighty participants met inclusion criteria, (232 MS+Depression: age[SD]=49[12], %females=86; 148 MS-Depression: age[SD]=47[13], %females=79). MS lesions preferentially affected fascicles within versus outside the depression network (ß=0.09, 95% CI=0.08-0.10, P<0.001). MS+Depression had more white matter lesion burden (ß=0.06, 95% CI=0.01-0.10, P=0.015); this was driven by lesions within the depression network (ß=0.02, 95% CI 0.003-0.040, P=0.020). Conclusions and Relevance: We provide new evidence supporting a relationship between white matter lesions and depression in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression had more disease than MS-Depression, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Early Magnetic Resonance Imaging Features of New Paramagnetic Rim Lesions in Multiple Sclerosis.

OBJECTIVE: To determine early magnetic resonance imaging (MRI) features of new multiple sclerosis (MS) lesions that will develop into paramagnetic rim lesions (PRLs), which have been associated with progressive tissue injury in MS. METHODS: New contrast-enhancing lesions observed on routine clinical MRI were imaged at 7 T within 4 weeks of observation, and 3 and 6 months later. The 6-month MRI was used to classify PRL status (PRL or non-PRL). The relationship between early lesion characteristics and subsequent PRL status was assessed using generalized linear mixed effects models. Random forest classification was performed to classify early predictors of subsequent PRL status. RESULTS: From 93 contrast-enhancing lesions in 23 MS patients, 37 lesions developed into a PRL. In lesions that developed into PRLs compared with those that did not, the average lesion T1 on the initial 7 T MRI was 1994 ms compared with 1,670 ms (p-value <0.001), and the average volume was 168.7 mL compared with 44 mL (p-value <0.001) in lesions that did not. These volume differences were also found on 3 T scans (p-value <0.001), and for intensity-normalized T1 -w (p-value = 0.011) and fluid-attenuated inversion recovery (p-value = 0.005). The area under the receiver operating characteristic curve for the random forest classification with leave-one-out cross-validation was found to be 0.86 using initial 7 T features. INTERPRETATION: New MS lesions that evolve into PRLs can be identified early in lesion evolution. These findings suggest that biological mechanisms underlying PRL development begin early, which has important implications for clinical trials targeting PRLs development and subsequent therapeutics. ANN NEUROL 2023;94:736-744.

Mechanisms, Effects, and Management of Neurological Complications of Post-Acute Sequelae of COVID-19 (NC-PASC).

With a growing number of patients entering the recovery phase following infection with SARS-CoV-2, understanding the long-term neurological consequences of the disease is important to their care. The neurological complications of post-acute sequelae of SARS-CoV-2 infection (NC-PASC) represent a myriad of symptoms including headaches, brain fog, numbness/tingling, and other neurological symptoms that many people report long after their acute infection has resolved. Emerging reports are being published concerning COVID-19 and its chronic effects, yet limited knowledge of disease mechanisms has challenged therapeutic efforts. To address these issues, we review broadly the literature spanning 2020-2022 concerning the proposed mechanisms underlying NC-PASC, outline the long-term neurological sequelae associated with COVID-19, and discuss potential clinical interventions.

T1 /T2 ratio from 3T MRI improves multiple sclerosis cortical lesion contrast.

BACKGROUND AND PURPOSE: Cortical demyelinated lesions are prevalent in multiple sclerosis (MS), associated with disability, and have recently been incorporated into MS diagnostic criteria. Presently, advanced and ultrahigh-field MRIs-not routinely available in clinical practice-are the most sensitive methods for detection of cortical lesions. Approaches utilizing MRI sequences obtainable in routine clinical practice remain an unmet need. We plan to assess the sensitivity of the ratio of T1 -weighted and T2 -weighted (T1 /T2 ) signal intensity for focal cortical lesions in comparison to other high-field imaging methods. METHODS: 3-Tesla and 7-Tesla MRI collected from 10 adults with MS were included in the study. T1 /T2 images were calculated by dividing 3T T1 -weighted (T1 w) images by 3T T2 -weighted (T2 w) fluid-attenuated inversion recovery images for each participant. A total of 614 cortical lesions were identified using 7T T2 *w and T1 w images and corresponding voxels were assessed on registered 3T images. Signal intensities were compared across 3T imaging sequences, including T1 /T2 , T1 w, T2 w, and inversion recovery susceptibility-weighted imaging with enhanced T2 weighting (IR-SWIET) images. RESULTS: T1 /T2 images demonstrated a larger contrast between median lesional and nonlesional cortical signal intensity (median ratio = 1.29, range: 1.19-1.38) when compared to T1 w (1.01, 0.97-1.10, p < .002), T2 w (1.17, 1.07-1.26, p < .002), and IR-SWIET (1.21, 1.01-1.29, p < .03). CONCLUSION: T1 /T2 images are sensitive to cortical lesions. Approaches incorporating T1 /T2 could improve the accessibility of cortical lesion detection in research settings and clinical practice.

Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis.

BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.

Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data.

Introduction: Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T. Methods: A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions. Results: Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume. Conclusions: LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.

Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions.

Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34-0.5 × 0.34-0.5 × 3-5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = -19.0-15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.

Clinically Deployed Computational Assessment of Multiple Sclerosis Lesions.

Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system that affects nearly 1 million adults in the United States. Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis and treatment monitoring in MS patients. In particular, follow-up MRI with T2-FLAIR images of the brain, depicting white matter lesions, is the mainstay for monitoring disease activity and making treatment decisions. In this article, we present a computational approach that has been deployed and integrated into a real-world routine clinical workflow, focusing on two tasks: (a) detecting new disease activity in MS patients, and (b) determining the necessity for injecting Gadolinium Based Contract Agents (GBCAs). This computer-aided detection (CAD) software has been utilized for the former task on more than 19, 000 patients over the course of 10 years, while its added function of identifying patients who need GBCA injection, has been operative for the past 3 years, with > 85% sensitivity. The benefits of this approach are summarized in: (1) offering a reproducible and accurate clinical assessment of MS lesion patients, (2) reducing the adverse effects of GBCAs (and the deposition of GBCAs to the patient's brain) by identifying the patients who may benefit from injection, and (3) reducing healthcare costs, patients' discomfort, and caregivers' workload.

Matrix decomposition for modeling lesion development processes in multiple sclerosis.

Our main goal is to study and quantify the evolution of multiple sclerosis lesions observed longitudinally over many years in multi-sequence structural magnetic resonance imaging (sMRI). To achieve that, we propose a class of functional models for capturing the temporal dynamics and spatial distribution of the voxel-specific intensity trajectories in all sMRI sequences. To accommodate the hierarchical data structure (observations nested within voxels, which are nested within lesions, which, in turn, are nested within study participants), we use structured functional principal component analysis. We propose and evaluate the finite sample properties of hypothesis tests of therapeutic intervention effects on lesion evolution while accounting for the multilevel structure of the data. Using this novel testing strategy, we found statistically significant differences in lesion evolution between treatment groups.

Fully automated detection of paramagnetic rims in multiple sclerosis lesions on 3T susceptibility-based MR imaging.

BACKGROUND AND PURPOSE: The presence of a paramagnetic rim around a white matter lesion has recently been shown to be a hallmark of a particular pathological type of multiple sclerosis lesion. Increased prevalence of these paramagnetic rim lesions is associated with a more severe disease course in MS, but manual identification is time-consuming. We present APRL, a method to automatically detect paramagnetic rim lesions on 3T T2*-phase images. METHODS: T1-weighted, T2-FLAIR, and T2*-phase MRI of the brain were collected at 3T for 20 subjects with MS. The images were then processed with automated lesion segmentation, lesion center detection, lesion labelling, and lesion-level radiomic feature extraction. A total of 951 lesions were identified, 113 (12%) of which contained a paramagnetic rim. We divided our data into a training set (16 patients, 753 lesions) and a testing set (4 patients, 198 lesions), fit a random forest classification model on the training set, and assessed our ability to classify paramagnetic rim lesions on the test set. RESULTS: The number of paramagnetic rim lesions per subject identified via our automated lesion labelling method was highly correlated with the gold standard count per subject, r = 0.86 (95% CI [0.68, 0.94]). The classification algorithm using radiomic features classified lesions with an area under the curve of 0.82 (95% CI [0.74, 0.92]). CONCLUSION: This study develops a fully automated technique, APRL, for the detection of paramagnetic rim lesions using standard T1 and FLAIR sequences and a T2*phase sequence obtained on 3T MR images.

BK virus-specific T cells for immunotherapy of progressive multifocal leukoencephalopathy: an open-label, single-cohort pilot study.

BACKGROUND: Progressive multifocal leukoencephalopathy, a rare disease of the CNS caused by JC virus and occurring in immunosuppressed people, is typically fatal unless adaptive immunity is restored. JC virus is a member of the human polyomavirus family and is closely related to the BK virus. We hypothesised that use of partly HLA-matched donor-derived BK virus-specific T cells for immunotherapy in progressive multifocal leukoencephalopathy would be feasible and safe. METHODS: We did an open-label, single-cohort pilot study in patients (aged 18 years or older) with clinically definite progressive multifocal leukoencephalopathy and disease progression in the previous month at the National Institutes of Health (NIH) Clinical Center (Bethesda, MD, USA). Overlapping peptide libraries derived from large T antigen and major capsid protein VP1 of BK virus with high sequence homology to JC virus counterparts were used to generate polyomavirus-specific T cells cross-recognising JC virus antigens. Polyomavirus-specific T cells were manufactured from peripheral blood mononuclear cells of first-degree relative donors aged 18 years or older. These cells were administered to patients by intravenous infusion at 1 × 106 polyomavirus-specific T cells per kg, followed by up to two additional infusions at 2 × 106 polyomavirus-specific T cells per kg. The primary endpoints were feasibility (no manufacturing failure based on meeting release criteria, achieving adequate numbers of cell product for clinical use, and showing measurable antiviral activity) and safety in all patients. The safety monitoring period was 28 days after each infusion. Patients were followed up with serial MRI for up to 12 months after the final infusion. This trial is registered at ClinicalTrials.gov, NCT02694783. FINDINGS: Between April 7, 2016, and Oct 19, 2018, 26 patients were screened, of whom 12 were confirmed eligible and received treatment derived from 14 matched donors. All administered polyomavirus-specific T cells met the release criteria and recognised cognate antigens in vitro. 12 patients received at least one infusion, ten received at least two, and seven received a total of three infusions. The median on-study follow-up was 109·5 days (range 23-699). All infusions were tolerated well, and no serious treatment-related adverse events were observed. Seven patients survived progressive multifocal leukoencephalopathy for longer than 1 year after the first infusion, whereas five died of progressive multifocal leukoencephalopathy within 3 months. INTERPRETATION: We showed that generation of polyomavirus-specific T cells from healthy related donors is feasible, and these cells can be safely used as an infusion for adoptive immunotherapy of progressive multifocal leukoencephalopathy. Although not powered to assess efficacy, our data provide additional support for this strategy as a potential life-saving therapy for some patients. FUNDING: Intramural Research Program of the National Institute of Neurological Disorders and Stroke of the NIH.

Haploinsufficiency of immune checkpoint receptor CTLA4 induces a distinct neuroinflammatory disorder.

BACKGROUNDCytotoxic T lymphocyte antigen 4 (CTLA4) is essential for immune homeostasis. Genetic mutations causing haploinsufficiency (CTLA4h) lead to a phenotypically heterogenous, immune-mediated disease that can include neuroinflammation. The neurological manifestations of CTLA4h are poorly characterized.METHODSWe performed an observational natural history study of 50 patients with CTLA4h who were followed at the NIH. We analyzed clinical, radiological, immunological, and histopathological data.RESULTSEvidence for neuroinflammation was observed in 32% (n = 16 of 50) of patients in this cohort by magnetic resonance imaging (MRI) and/or by cerebrospinal fluid analysis. Clinical symptoms were commonly absent or mild in severity, with headaches as the leading complaint (n = 13 of 16). The most striking findings were relapsing, large, contrast-enhancing focal lesions in the brain and spinal cord observed on MRI. We detected inflammation in the cerebrospinal fluid and leptomeninges before the parenchyma. Brain biopsies of inflammatory lesions from 10 patients showed perivascular and intraparenchymal mixed cellular infiltrates with little accompanying demyelination or neuronal injury.CONCLUSIONSNeuroinflammation due to CTLA4h is mediated primarily by an infiltrative process with a distinct and striking dissociation between clinical symptoms and radiological findings in the majority of patients.FUNDINGNIAID, NIH, Division of Intramural Research, NINDS, NIH, Division of Intramural Research, and the National Multiple Sclerosis Society-American Brain Foundation.TRIAL REGISTRATIONClinicalTrials.gov NCT00001355.

TAPAS: A Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis.

Total brain white matter lesion (WML) volume is the most widely established magnetic resonance imaging (MRI) outcome measure in studies of multiple sclerosis (MS). To estimate WML volume, there are a number of automatic segmentation methods available, yet manual delineation remains the gold standard approach. Automatic approaches often yield a probability map to which a threshold is applied to create lesion segmentation masks. Unfortunately, few approaches systematically determine the threshold employed; many methods use a manually selected threshold, thus introducing human error and bias into the automated procedure. In this study, we propose and validate an automatic thresholding algorithm, Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis (TAPAS), to obtain subject-specific threshold estimates for probability map automatic segmentation of T2-weighted (T2) hyperintense WMLs. Using multimodal MRI, the proposed method applies an automatic segmentation algorithm to obtain probability maps. We obtain the true subject-specific threshold that maximizes the Sørensen-Dice similarity coefficient (DSC). Then the subject-specific thresholds are modeled on a naive estimate of volume using a generalized additive model. Applying this model, we predict a subject-specific threshold in data not used for training. We ran a Monte Carlo-resampled split-sample cross-validation (100 validation sets) using two data sets: the first obtained from the Johns Hopkins Hospital (JHH) on a Philips 3 Tesla (3T) scanner (n = 94) and a second collected at the Brigham and Women's Hospital (BWH) using a Siemens 3T scanner (n = 40). By means of the proposed automated technique, in the JHH data we found an average reduction in subject-level absolute error of 0.1 mL per one mL increase in manual volume. Using Bland-Altman analysis, we found that volumetric bias associated with group-level thresholding was mitigated when applying TAPAS. The BWH data showed similar absolute error estimates using group-level thresholding or TAPAS likely since Bland-Altman analyses indicated no systematic biases associated with group or TAPAS volume estimates. The current study presents the first validated fully automated method for subject-specific threshold prediction to segment brain lesions.

Experimental design and sample size considerations in longitudinal magnetic resonance imaging-based biomarker detection for multiple sclerosis.

Several modeling approaches have been developed to quantify differences in multiple sclerosis lesion evolution on magnetic resonance imaging to identify the effect of treatment on disease progression. These studies have limited clinical applicability due to onerous scan frequency and lengthy study duration. Efficient methods are needed to reduce the required sample size, study duration, and sampling frequency in longitudinal magnetic resonance imaging studies. We develop a data-driven approach to identify parameters of study design for evaluation of longitudinal magnetic resonance imaging biomarkers of multiple sclerosis lesion evolution. Our design strategies are considerably shorter than those described in previous studies, thus having the potential to lower costs of clinical trials. From a dataset of 36 multiple sclerosis patients with at least six monthly magnetic resonance imagings, we extracted new lesions and performed principal component analysis to estimate a biomarker that recapitulated lesion recovery. We tested the effect of multiple sclerosis disease modifying therapy on the lesion evolution index in three experimental designs and calculated sample sizes needed to appropriately power studies. Our proposed methods can be used to calculate required sample size and scan frequency in observational studies of multiple sclerosis disease progression as well as in designing clinical trials to find effects of treatment on multiple sclerosis lesion evolution.