Abstract Multiple sclerosis (MS) white matter lesion (WML) automated segmentation on ultra-high-field 7T MRI remains challenging due to the domain shift from lower-field acquisitions, limited annotated data, and specific imaging artifacts. Fine-tuning is an effective and practical strategy for adapting deep learning WML segmentation algorithms to 7T MRI, even with limited annotated data. This study evaluates fine-tuning as a domain adaptation strategy to leverage a pre-trained deep learning model for automated WML segmentation on 7T MRI. We fine-tuned a U-Net-based model, originally trained on approximately 35,000 heterogeneous lower-field (1T, 1.5T, 3T) multi-contrast MRI scans of people with MS for T2-hyperintense WML (T2-WML) segmentation, using a 7T dataset. Multiple approaches were evaluated, including standard fine-tuning on 3D FLAIR images, low-rank adaptation (LoRA) and training from scratch (nnU-Net). Models were evaluated on an external multi-center 7T test dataset. Additionally, a separate model was fine-tuned for T1-hypointense WML (T1-WML) segmentation on 7T MP2RAGE images. The original model showed substantial performance degradation on 7T data compared to 3T (Dice score decreased from 0.69 to 0.31), confirming the need for domain adaptation. Fine-tuning markedly improved T2-WML segmentation, with the fine-tuned model achieving a median Dice score of 0.57. Lesion-wise sensitivity and F1-score were 0.78 and 0.75, respectively, and the lesion volume agreement with manual segmentation was 0.93. For T1-hypointense WML, fine-tuning showed lower lesion detection performance compared to the T2-hyperintense WML segmentation (sensitivity and F1 of 0.58 and 0.50, respectively); however, incorporating multi-center data into the training set substantially reduced false positives by 23% and improved lesion detection by 14%. Multi-center fine-tuning further improved performance, particularly for the more challenging task of T1-WML segmentation. The models presented here may be included in MS research workflows to facilitate multi-center collaborations with 7T MRI.

Ultra-high field 7-tesla (7T) MRI improves visualization of multiple sclerosis (MS) white matter lesions (WML) but differs sufficiently in contrast and artifacts from 1.5-3T imaging - suggesting that widely used automated segmentation tools may not translate directly. We analyzed 7T FLAIR scans and generated reference WML masks from Lesion Segmentation Tool (LST) outputs followed by expert manual revision. As external comparators, we applied LST-LPA and the more recent LST-AI ensemble, both originally developed on lower-field data. We then trained 3D UNETR and SegFormer transformer-based models on 7T FLAIR at multiple resolutions (0.5x0.5x0.5^3, 1.0x1.0x1.0^3, and 1.5x1.5x2.0^3) and evaluated all methods using voxel-wise and lesion-wise metrics from the BraTS 2023 framework. On the held-out test set at native 0.5x0.5x0.5^3 resolution, 7T-trained transformers achieved competitive overlap with LST-AI while recovering additional small lesions that were missed by classical methods, at the cost of some boundary variability and occasional artifact-related false positives. On a held-out 7 T test set, our best transformer model (SegFormer) achieved a voxel-wise Dice of 0.61 and lesion-wise Dice of 0.20, improving on the classical LST-LPA tool (Dice 0.39, lesion-wise Dice 0.02). Performance decreased for models trained on downsampled images, underscoring the value of native 7T resolution for small-lesion detection. By releasing our 7T-trained models, we aim to provide a reproducible, ready-to-use resource for automated lesion quantification in ultra-high field MS research (https://github.com/maynord/7T-MS-lesion-segmentation).

Multiple sclerosis (MS) is a chronic inflammatory disease affecting the central nervous system that involves immune-mediated demyelination and axonal degeneration. Clinical imaging techniques play a critical role in diagnosing and assessing the prognosis of MS. Magnetic resonance imaging has been most frequently used to visualize demyelination and detect acute and chronic active lesions, which are key indicators of clinical course of illness. Previous research has also highlighted the effectiveness of translocator protein 18-kDa (TSPO) positron emission tomography (PET) imaging for identifying chronic active lesions and progressive pathology. Building on this work, the present study used PET imaging to explore the role of cyclooxygenase-1 and -2 (COX-1 and COX-2)—key enzymes involved in neuroinflammation—in individuals with MS. Five participants with MS were recruited, and lesions were identified using 7 Tesla MRI. No significant differences in COX radioligand binding were observed in the co-registered PET images between lesioned areas and normal-appearing brain tissues, nor between individuals with MS and healthy volunteers. The negative findings underscore the complexity of MS pathology and raise several important considerations for planning future studies using COX PET for imaging in MS.

Background and Objectives:A growing number of nurse practitioners (NPs) are entering neurologic practice. Postgraduate educational needs of NPs are partly dictated by previous neurologic educational experience, which is not well defined. We aim to describe neurologic education in NP programs to better inform efforts to develop tailored educational initiatives. Methods:A website review was performed to identify accredited NP programs and program leaders. A previously developed survey designed to facilitate a description of neurologic education in physician assistant (PA) programs was adapted for NP program leaders by an iterative approach. The survey was distributed in spring and fall 2023. Results:Three hundred and thirty-three Family NP, 140 Adult-Gerontologic Primary Care NP, and 136 Adult-Gerontologic Acute Care NP registered programs were identified. Leaders of 206 programs completed the survey (response rate = 34.9%). Two hundred four respondents (99.0%) reported neuroscience didactics included within their curriculum, typically contained within core, discipline-based courses. Neurologic disease and examination (n = 201, 98%) were covered most while lesion localization (n = 37, 18.0%) and neuroradiology (n = 50, 24.3%) were taught least often. Of 201 respondents who indicated that neurologic examination is included, 175 (87.1%) reported a hands-on approach. Didactic neuroscience instructors were specialized in clinical neurology in 109 programs (53.4%). One hundred sixty-nine programs (82.0%) offer a neurology clinical rotation, typically as an elective. Of respondents who provided an estimate, most reported that 10% or fewer of their students complete a neurology clinical rotation per year (n = 62, 77.5%). The most frequently reported barrier to offering clinical placement in neurology was lack of neurology preceptors (n = 85, 56.6%). Programs reporting graduates pursuing careers in neurology were associated with larger size, acute care track, and neurology NP as a didactic neuroscience instructor. Discussion:Lesion localization and neuroradiology are important targets for postgraduate training of NPs entering neurologic practice. Recruiting neurology NPs to teach neuroscience didactics may increase programs with students pursuing careers in neurology. Availability of clinical neurology rotations is not universal in NP programs. Encouraging neurology clinicians, including PAs and physicians, to precept NP students could help increase access to clinical neurology rotations. These results highlight important opportunities for augmenting neurologic education during and after NP programs.

Background and Objectives: Changes to the perivascular space (PVS) may be associated with multiple sclerosis (MS) pathology. In this study, we aimed to quantify PVS burden and assess PVS contrast enhancement on 7T MRI in MS. Methods: Participants with MS (N = 100), other inflammatory neurological disorders (OIND, N = 12), and healthy controls (HC, N = 18) underwent 7T MRI. PVS segmentation was performed using an automated algorithm. Post-contrast FLAIR images were reviewed for gadolinium contrast-enhancing PVS (CE-PVS). The count, volume, and fraction of PVS and CE-PVS patterns were quantified. Results: Overall, 67% of participants were female, with the same proportion across HC, MS, and OIND groups. Median age was 41 years in HC, 46 years in MS, and 35 years in OIND. The segmentation algorithm achieved a median Dice Similarity Coefficient (DSC) of 0.994 compared to manually revised masks. PVS count, volume, and the proportion of PVS volume divided by total white matter (WM) volume did not differ significantly between individuals with and without MS. This finding was no different when restricting the analysis to only PVS in the large size category (> 2.65 mm3). CE- PVS were seen in 29% of MS, 11% of HC, and 8% of OIND, p = 0.431. Participants with progressive MS (PMS, N = 21) had greater PVS count (1341 (841, 1481)) than those with relapsing-remitting MS (RRMS, N = 79) (849 (571, 1283)), adjusted p = 0.037. Conclusions: 7T MRI and an automated algorithm enabled accurate PVS quantification. Although trends towards increased baseline PVS burden and CE-PVS in MS were seen, these differences were not significant. An observed difference in PVS between PMS and RRMS across all time points suggests a potential biological distinction, though, which warrants further investigation.

The use of ultra-high-field 7-Tesla (7T) MRI in multiple sclerosis (MS) research has grown significantly over the past two decades. With recent regulatory approvals of 7T scanners for clinical use in 2017 and 2020, the use of this technology for routine care is poised to continue to increase in the coming years. In this context, the North American Imaging in MS Cooperative (NAIMS) convened a workshop in February 2023 to review the previous and current use of 7T technology for MS research and potential future research and clinical applications. In this workshop, experts were tasked with reviewing the current literature and proposing a series of consensus statements, which were reviewed and approved by the NAIMS. In this review and consensus paper, we provide background on the use of 7T MRI in MS research, highlighting this technology's promise for identification and quantification of aspects of MS pathology that are more difficult to visualize with lower-field MRI, such as grey matter lesions, paramagnetic rim lesions, leptomeningeal enhancement and the central vein sign. We also review the promise of 7T MRI to study metabolic and functional changes to the brain in MS. The NAIMS provides a series of consensus statements regarding what is currently known about the use of 7T MRI in MS, and additional statements intended to provide guidance as to what work is necessary going forward to accelerate 7T MRI research in MS and translate this technology for use in clinical practice and clinical trials. This includes guidance on technical development, proposals for a universal acquisition protocol and suggestions for research geared towards assessing the utility of 7T MRI to improve MS diagnostics, prognostics and therapeutic efficacy monitoring. The NAIMS expects that this article will provide a roadmap for future use of 7T MRI in MS.

Background Paramagnetic rim lesions (PRLs) are associated with chronic inflammation in multiple sclerosis (MS). 7‐Tesla (7T) magnetic resonance imaging (MRI) can evaluate the integrity of the blood‐brain barrier (BBB) in addition to the tissue myelination status and cell loss. Purpose To use MRI metrics to investigate underlying physiology and clinical importance of PRLs. Study Type Prospective. Subjects Thirty‐six participants (mean‐age 47, 23 females, 13 males) of mixed MS subtypes. Field Strength/Sequence 7T, MP2RAGE, MULTI‐ECHO 3D‐GRE, FLAIR. Assessment Lesion heterogeneity; longitudinal changes in lesion counts; comparison of T1, R2*, and χ ; association between baseline lesion types and disease progression (2–3 annual MRI visits with additional years of annual clinical follow‐up). Statistical Tests Two‐sample t ‐test, Wilcoxon Rank‐Sum test, Pearson's chi‐square test, two‐group comparison with linear‐mixed‐effect model, mixed‐effect ANOVA, logistic regression. P ‐values <0.05 were considered significant. Results A total of 58.3% of participants had at least one PRL at baseline. Higher male proportion in PRL+ group was found. Average change in PRL count was 0.20 (SD = 2.82) for PRLs and 0.00 (SD = 0.82) for mottled lesions. Mean and median pre‐/post‐contrast T1 were longer in PRL+ than in PRL−. No differences in mean χ were seen for lesions grouped by PRL ( P = 0.310, pre‐contrast; 0.086, post‐contrast) or PRL/M presence ( P = 0.234, pre‐contrast; 0.163, post‐contrast). Median χ were less negative in PRL+ and PRL/M+ than in PRL− and PRL/M−. Mean and median pre−/post‐contrast R2* were slower in PRL+ compared to PRL−. Mean and median pre−/post‐contrast R2* were slower in PRL/M+ than in PRL/M−. PRL presence at baseline was associated with confirmed EDSS Plus progression (OR 3.75 [1.22–7.59]) and PRL/M+ at baseline with confirmed EDSS Plus progression (OR 3.63 [1.14–7.43]). Data Conclusion Evidence of BBB breakdown in PRLs was not seen. Quantitative metrics confirmed prior results suggesting greater demyelination, cell loss, and possibly disruption of tissue anisotropy in PRLs. Evidence Level 2 Technical Efficacy Stage 2

Although 7 T MRI research has contributed much to our understanding of multiple sclerosis (MS) pathology, most prior data has come from small, single-center studies with varying methods. In order to truly know if such findings have widespread applicability, multicenter methods and studies are needed. To address this, members of the North American Imaging in MS (NAIMS) Cooperative worked together to create a multicenter collaborative study of 7 T MRI in MS. In this manuscript, we describe the methods we have developed for the purpose of pooling together a large, retrospective dataset of 7 T MRIs acquired in multiple MS studies at five institutions. To date, this group has contributed five-hundred and twenty-eight 7 T MRI scans from 350 individuals with MS to a common data repository, with plans to continue to increase this sample size in the coming years. We have developed unified methods for image processing for data harmonization and lesion identification/segmentation. We report here our initial observations on intersite differences in acquisition, which includes site/device differences in brain coverage and image quality. We also report on the development of our methods and training of image evaluators, which resulted in median Dice Similarity Coefficients for trained raters' annotation of cortical and deep gray matter lesions, paramagnetic rim lesions, and meningeal enhancement between 0.73 and 0.82 compared to final consensus masks. We expect this publication to act as a resource for other investigators aiming to combine multicenter 7 T MRI datasets for the study of MS, in addition to providing a methodological reference for all future analysis projects to stem from the development of this dataset.

The PatientA 65-year-old previously healthy man presented to the emergency department, after waking up, with new right frontal headache, blurry vision, and perception of flashing lights.Preceding these symptoms, he had 3 weeks of watery diarrhea, sore throat, ankle swelling, and generalized fatigue.After arriving in the emergency department, he was noted to have a decreasing level of arousal, with intermittent periods of agitation, and was intubated.

Background/Purpose Leptomeningeal enhancement (LME) on post-contrast FLAIR is described as a potential biomarker of meningeal inflammation in multiple sclerosis (MS). Here we report an assessment of the impact of MRI field strength and acquisition timing on meningeal contrast enhancement (MCE). Methods This was a cross-sectional, observational study of 95 participants with MS and 17 healthy controls (HC) subjects. Each participant underwent an MRI of the brain on both a 7 Tesla (7T) and 3 Tesla (3T) MRI scanner. 7T protocols included a FLAIR image before, soon after (Gd+ Early 7T FLAIR), and 23 minutes after gadolinium (Gd+ Delayed 7T FLAIR). 3T protocol included FLAIR before and 21 minutes after gadolinium (Gd+ Delayed 3T FLAIR). Results LME was seen in 23.3% of participants with MS on Gd+ Delayed 3T FLAIR, 47.4% on Gd+ Early 7T FLAIR (p = 0.002) and 57.9% on Gd+ Delayed 7T FLAIR (p < 0.001 and p = 0.008, respectively). The count and volume of LME, leptomeningeal and paravascular enhancement (LMPE), and paravascular and dural enhancement (PDE) were all highest for Gd+ Delayed 7T FLAIR and lowest for Gd+ Delayed 3T FLAIR. Non-significant trends were seen for higher proportion, counts, and volumes for LME and PDE in MS compared to HCs. The rate of LMPE was different between MS and HCs on Gd+ Delayed 7T FLAIR (98.9% vs 82.4%, p = 0.003). MS participants with LME on Gd+ Delayed 7T FLAIR were older (47.6 (10.6) years) than those without (42.0 (9.7), p = 0.008). Conclusion 7T MRI and a delay after contrast injection increased sensitivity for all forms of MCE. However, the lack of difference between groups for LME and its association with age calls into question its relevance as a biomarker of meningeal inflammation in MS.

Chronic active lesions (CAL) are an important manifestation of chronic inflammation in multiple sclerosis and have implications for non-relapsing biological progression. In recent years, the discovery of innovative MRI and PET-derived biomarkers has made it possible to detect CAL, and to some extent quantify them, in the brain of persons with multiple sclerosis, in vivo. Paramagnetic rim lesions on susceptibility-sensitive MRI sequences, MRI-defined slowly expanding lesions on T1-weighted and T2-weighted scans, and 18-kDa translocator protein-positive lesions on PET are promising candidate biomarkers of CAL. While partially overlapping, these biomarkers do not have equivalent sensitivity and specificity to histopathological CAL. Standardization in the use of available imaging measures for CAL identification, quantification and monitoring is lacking. To fast-forward clinical translation of CAL, the North American Imaging in Multiple Sclerosis Cooperative developed a consensus statement, which provides guidance for the radiological definition and measurement of CAL. The proposed manuscript presents this consensus statement, summarizes the multistep process leading to it, and identifies the remaining major gaps in knowledge.

We aim to describe neurologic education in nurse practitioner (NP) programs to better inform efforts to develop tailored educational initiatives.

OBJECTIVES:To define consensus entrustable professional activities (EPAs) for neurocritical care (NCC) advanced practice providers (APPs), establish validity evidence for the EPAs, and evaluate factors that inform entrustment expectations of NCC APP supervisors.DESIGN:A three-round modified Delphi consensus process followed by application of the EQual rubric and assessment of generalizability by clinicians not affiliated with academic medical centers.SETTING:Electronic surveys.SUBJECTS:NCC APPs ( n = 18) and physicians ( n = 12) in the United States with experience in education scholarship or APP program leadership.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:The steering committee generated an initial list of 61 possible EPAs. The panel proposed 30 additional EPAs. A total of 47 unique nested EPAs were retained by consensus opinion. The steering committee defined six core EPAs addressing medical knowledge, procedural competencies, and communication proficiency which encompassed the nested EPAs. All core EPAs were retained and subsequently met the previously described cut score for quality and structure using the EQual rubric. Most clinicians who were not affiliated with academic medical centers rated each of the six core EPAs as very important or mandatory. Entrustment expectations did not vary by prespecified groups.CONCLUSIONS:Expert consensus was used to create EPAs for NCC APPs that reached a predefined quality standard and were important to most clinicians in different practice settings. We did not identify variables that significantly predicted entrustment expectations. These EPAs may aid in curricular design for an EPA-based assessment of new NCC APPs and may inform the development of EPAs for APPs in other critical care subspecialties.

This Viewpoint discusses hypothermic temperature control for neuroprotection among survivors of out-of-hospital cardiac arrest and offers a rational approach to treating such patients as investigations continue.

Background: Autopsy data suggests that meningeal inflammation in multiple sclerosis (MS) is driven by CD20+ Bcells. Ocrelizumab is an anti-CD20 monoclonal antibody, and thus could potentially ameliorate meningeal inflammation in MS. Leptomeningeal enhancement (LME) on MRI is suggested as a surrogate biomarker of meningeal inflammation in MS, and thus may be a way of monitoring for this treatment effect. Objectives: To determine if ocrelizumab impacts meningeal enhancement (ME) on 7T MRI in MS. Methods: Twenty-two patients with MS started on ocrelizumab by their treating physician were enrolled into this single-center, open-label, prospective trial. Participants underwent 7T MRI of the brain prior to first infusion, with screening for the presence of LME. Fourteen patients (48 +/- 11 years; 11 women) had LME on the baseline scan and were invited to return for an additional 7T MRI after 1 year of treatment. Fourteen MS patients (49 +/- 10 years; 11 women) on non-CD20 treatment from a separate observational cohort of annual 7T MRIs were used for comparison - matched for LME at baseline, age, and sex. Post-contrast FLAIR and subtraction images were reviewed for LME and paravascular and dural enhancement (PDE). Results: All subjects in the ocrelizumab and comparison groups had LME and PDE on their baseline scan. At the beginning of the study the mean number of foci of LME and PDE in the study group were 2.3 +/- 1.7 and 6.6 +/- 3.9 respectively. Mean LME and PDE count for the comparison group were 1.7 +/- 1.5 and 7.8 +/- 5.5. Mean volume of LME in the study group was 50.5 mm3 +/- 65.0 mm3 and that of the PDE was 866 mm3 +/- 937.9. Mean volume of LME and PDE for comparison group were 28.4 mm3 +/- 36.0 and 885 mm3 +/- 947.7 respectively. At follow-up, the number of patients with LME decreased to 8 (57 %) in both groups, whereas the proportion of patients with PDE was unchanged. Minimal mean change in the number of LME after 1 year were seen in both the study group (0.07 +/- 2.9, p = 0.97) and comparison group (-0.71 +/- 1.5, p = 0.08). Minimal mean change was seen in the volume of LME in both the study group (-21.91 mm3 +/- 77.66, p = 0.27) and comparison group (3.4 mm3 +/- 32.11, p = 0.77). There was minimal change in the mean number of foci of PDE after 1 year in both the study group (-0.71 +/- 2.36, p = 0.32) and in the comparison group (-0.17 +/- 3.89, p = 0.15). Mean change in volume of PDE was measurable, but not significant in both the study group (-397.1 mm3 +/- 959.6, p = 0.80) and in the comparison group (-417.0 mm3 +/- 922.7) (p = 0.80). Comparisons between the changes in foci count and volume for both LME and PDE in the study versus comparison groups showed no significant differences. Conclusion: In this small pilot trial, ocrelizumab did not significantly reduce the number or volume of foci of LME or PDE in MS patients.

An elderly woman presented with subacute onset of chorea following a hospitalization for severe, uncontrolled diabetes, a urinary tract infection, and 6 months of depression. Her neurological examination demonstrated bilateral chorea involving the arms, legs, and jaw. MRI of the brain demonstrated bilateral T1 hyperintensity. She was diagnosed with diabetic striatopathy, also known as nonketotic hyperglycemic chorea, a rare complication of diabetes mellitus that classically causes hemichorea in the setting of very high blood glucose without ketosis. This case demonstrates typical imaging findings of diabetic striatopathy despite several atypical clinical features, including bilateral chorea, development of symptoms weeks after improvement in blood glucose, and demographics of the patient. Diabetic striatopathy.1, 2

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry–academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.

Background and purpose: Meningeal lymphatic vessels (MLVs) along the dural venous sinuses are suspected to be important in connecting the glymphatic and peripheral lymphatic system. Understanding the topography of MLVs may clarify the role of the glymphatic system in neurological diseases. The aim of this analysis was to use high resolution pre-and post-contrast FLAIR 7T MRI to identify and characterize the morphology of MLV in a cohort of healthy volunteers. Materials and methods: MRI examinations of seventeen healthy volunteers enrolled as controls in a larger 7T MRI study were reviewed. Pre-and post-contrast 3-D FLAIR subtractions and MP2RAGE sequences were spatially normalized and reviewed for signal intensity and enhancement patterns within putative MLVs along pre-determined dural and venous struc-tures. Frequency of occurrence of MLVs at the above-described locations and patterns of their enhancement were analyzed.Results: Putative MLVs are commonly located along the superior sagittal sinus (SSS) and cortical veins. A "fixed enhancement" signal pattern was more frequent at these locations (p<.05). The morphology of MLVs along the SSS qualitatively changes in an antero-posterior direction. Lack of signal was more frequent along the straight and transverse sinuses (p<.05).Conclusion: Putative MLVs in healthy individuals are concentrated along the SSS and cortical veins. FLAIR sig-nal and enhancement characteristics suggest these structures may transport proteinaceous fluid. Pathways connecting MLVs to cervical lymph nodes however remain unclear.(c) 2023 Elsevier Masson SAS. All rights reserved.