56 research outputs found

    Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis

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    Lesions corticals; Vena central; Esclerosis múltipleLesions corticals; Vena central; Esclerosis múltipleCortical Lesions; Central vein; Multiple sclerosisImportance Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants’ diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures MS/CIS vs non-MS conditions. Main Outcomes and Measures Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis

    Harmonizing Definitions for Progression Independent of Relapse Activity in Multiple Sclerosis: A Systematic Review

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    IMPORTANCE: Emerging evidence suggests that progression independent of relapse activity (PIRA) is a substantial contributor to long-term disability accumulation in relapsing-remitting multiple sclerosis (RRMS). To date, there is no uniform agreed-upon definition of PIRA, limiting the comparability of published studies. OBJECTIVE: To summarize the current evidence about PIRA based on a systematic review, to discuss the various terminologies used in the context of PIRA, and to propose a harmonized definition for PIRA for use in clinical practice and future trials. EVIDENCE REVIEW: A literature search was conducted using the search terms multiple sclerosis, PIRA, progression independent of relapse activity, silent progression, and progression unrelated to relapses in PubMed, Embase, Cochrane, and Web of Science, published between January 1990 and December 2022. FINDINGS: Of 119 identified single records, 48 eligible studies were analyzed. PIRA was reported to occur in roughly 5% of all patients with RRMS per annum, causing at least 50% of all disability accrual events in typical RRMS. The proportion of PIRA vs relapse-associated worsening increased with age, longer disease duration, and, despite lower absolute event numbers, potent suppression of relapses by highly effective disease-modifying therapy. However, different studies used various definitions of PIRA, rendering the comparability of studies difficult. CONCLUSION AND RELEVANCE: PIRA is the most frequent manifestation of disability accumulation across the full spectrum of traditional MS phenotypes, including clinically isolated syndrome and early RRMS. The harmonized definition suggested here may improve the comparability of results in current and future cohorts and data sets

    Sporadic MM-1 Type Creutzfeldt-Jakob Disease With Hemiballic Presentation and No Cognitive Impairment Until Death: How New NCJDRSU Diagnostic Criteria May Allow Early Diagnosis

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    Sporadic Creutzfeldt-Jakob disease is the most common human prion disorder. Although associated with heterogeneous clinical phenotypes, its distinctive feature is the presence of a rapidly progressive multidomain cognitive impairment. We describe the atypical case of a patient affected by sporadic Methionine/Methionine type 1 Creutzfeldt-Jakob disease (typically associated with early cognitive decline) who presented with an isolated hemiballic syndrome and no signs of cognitive involvement until death. We review sporadic Creutzfeldt-Jakob disease diagnostic criteria and their updates since their first formulation, highlighting their limitations in clinical diagnostic work-up. Finally, we discuss the recently introduced National Creutzfeldt-Jakob Disease Research and Surveillance Unit diagnostic criteria, suggesting how their application could support an early clinical diagnosis, even in atypical cases, such as the one presented

    Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple Sclerosis

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    Uncertainty quantification (UQ) has become critical for evaluating the reliability of artificial intelligence systems, especially in medical image segmentation. This study addresses the interpretability of instance-wise uncertainty values in deep learning models for focal lesion segmentation in magnetic resonance imaging, specifically cortical lesion (CL) segmentation in multiple sclerosis. CL segmentation presents several challenges, including the complexity of manual segmentation, high variability in annotation, data scarcity, and class imbalance, all of which contribute to aleatoric and epistemic uncertainty. We explore how UQ can be used not only to assess prediction reliability but also to provide insights into model behavior, detect biases, and verify the accuracy of UQ methods. Our research demonstrates the potential of instance-wise uncertainty values to offer post hoc global model explanations, serving as a sanity check for the model. The implementation is available at https://github.com/NataliiaMolch/interpret-lesion-unc

    Cell-binding IgM in CSF is distinctive of multiple sclerosis and targets the iron transporter SCARA5

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    Intrathecal IgM production in multiple sclerosis (MS) is associated with a worse disease course. To investigate pathogenic relevance of autoreactive IgM in MS, CSF from two independent cohorts, including MS patients and controls, were screened for antibody binding to induced pluripotent stem cell-derived neurons and astrocytes, and a panel of CNS- related cell lines. IgM binding to a primitive neuro-ectodermal tumour cell line discriminated 10% of MS donors from controls. Transcriptomes of single IgM producing CSF B cells from patients with cell-binding IgM were sequenced and used to produce recombinant monoclonal antibodies for characterisation and antigen identification. We produced 5 cell-binding recombinant IgM antibodies, of which one, cloned from an HLA-DR + plasma-like B cell, mediated antigen-dependent complement activation. Immunoprecipitation and mass spectrometry, and biochemical and transcriptome analysis of the target cells identified the iron transport scavenger protein SCARA5 as the antigen target of this antibody. Intrathecal injection of a SCARA5 antibody led to an increased T cell infiltration in an EAE model. CSF IgM might contribute to CNS inflammation in MS by binding to cell surface antigens like SCARA5 and activating complement, or by facilitating immune cell migration into the brain

    More Than the Sum of Its Parts: Disrupted Core Periphery of Multiplex Brain Networks in Multiple Sclerosis

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    Disruptions to brain networks, measured using structural (sMRI), diffusion (dMRI), or functional (fMRI) MRI, have been shown in people with multiple sclerosis (PwMS), highlighting the relevance of regions in the core of the connectome but yielding mixed results depending on the studied connectivity domain. Using a multilayer network approach, we integrated these three modalities to portray an enriched representation of the brain's core‐periphery organization and explore its alterations in PwMS. In this retrospective cross‐sectional study, we selected PwMS and healthy controls with complete multimodal brain MRI acquisitions from 13 European centers within the MAGNIMS network. Physical disability and cognition were assessed with the Expanded Disability Status Scale (EDSS) and the symbol digit modalities test (SDMT), respectively. SMRI, dMRI, and resting‐state fMRI data were parcellated into 100 cortical and 14 subcortical regions to obtain networks of morphological covariance, structural connectivity, and functional connectivity. Connectivity matrices were merged in a multiplex, from which regional coreness—the probability of a node being part of the multiplex core—and coreness disruption index (κ)—the global weakening of the core‐periphery structure—were computed. The associations of κ with disease status (PwMS vs. healthy controls), clinical phenotype, level of physical disability (EDSS ≥ 4 vs. EDSS < 4), and cognitive impairment (SDMT z‐score < −1.5) were tested within a linear model framework. Using random forest permutation feature importance, we assessed the relative contribution of κ in the multiplex and single‐layer domains, in addition to conventional MRI measures (brain and lesion volumes), in predicting disease status, physical disability, and cognitive impairment. We studied 1048 PwMS (695F, mean ± SD age: 43.3 ± 11.4 years) and 436 healthy controls (250F, mean ± SD age: 38.3 ± 11.8 years). PwMS showed significant disruption of the multiplex core‐periphery organization (κ = −0.14, Hedges' g = 0.49, p < 0.001), correlating with clinical phenotype (F = 3.90, p = 0.009), EDSS (Hedges' g = 0.18, p = 0.01), and SDMT (Hedges' g = 0.30, p < 0.001). Multiplex κ was the only connectomic measure adding to conventional MRI in predicting disease status and cognitive impairment, while physical disability also depended on single‐layer contributions. In conclusion, we show that multilayer networks represent a biologically and clinically meaningful framework to model multimodal MRI data, with disruption of the core‐periphery structure emerging as a potential connectomic biomarker for disease severity and cognitive impairment in PwMS

    A novel imaging marker of cortical “cellularity” in multiple sclerosis patients

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    Pathological data showed focal inflammation and regions of diffuse neuronal loss in the cortex of people with multiple sclerosis (MS). In this work, we applied a novel model (“soma and neurite density imaging (SANDI)”) to multishell diffusion-weighted MRI data acquired in healthy subjects and people with multiple sclerosis (pwMS), in order to investigate inflammation and degeneration-related changes in the cortical tissue of pwMS. We aimed to (i) establish whether SANDI is applicable in vivo clinical data; (ii) investigate inflammatory and degenerative changes using SANDI soma fraction (fsoma)—a marker of cellularity—in both cortical lesions and in the normal-appearing-cortex and (iii) correlate SANDI fsoma with clinical and biological measures in pwMS. We applied a simplified version of SANDI to a clinical scanners. We then provided evidence that pwMS exhibited an overall decrease in cortical SANDI fsoma compared to healthy subjects, suggesting global degenerative processes compatible with neuronal loss. On the other hand, we have found that progressive pwMS showed a higher SANDI fsoma in the outer part of the cortex compared to relapsing–remitting pwMS, possibly supporting current pathological knowledge of increased innate inflammatory cells in these regions. A similar finding was obtained in subpial lesions in relapsing–remitting patients, reflecting existing pathological data in these lesion types. A significant correlation was found between SANDI fsoma and serum neurofilament light chain—a biomarker of inflammatory axonal damage—suggesting a relationship between SANDI soma fraction and inflammatory processes in pwMS again. Overall, our data show that SANDI fsoma is a promising biomarker to monitor changes in cellularity compatible with neurodegeneration and neuroinflammation in the cortex of MS patients

    Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis

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    IMPORTANCE: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. OBJECTIVE: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). EXPOSURES: MS/CIS vs non-MS conditions. MAIN OUTCOMES AND MEASURES: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. RESULTS: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. CONCLUSIONS AND RELEVANCE: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis

    A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients.

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    BACKGROUND Detecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarged white matter lesions (NELs) in the follow-up of MS patients; however, multicenter validation studies are lacking. PURPOSE To assess the accuracy of LeMan-PV for the longitudinal detection NEL white-matter MS lesions in a multicenter clinical setting. STUDY TYPE Retrospective, longitudinal. SUBJECTS A total of 206 patients with a definitive MS diagnosis and at least two follow-up MRI studies from five centers participating in the Swiss Multiple Sclerosis Cohort study. Mean age at first follow-up = 45.2 years (range: 36.9-52.8 years); 70 males. FIELD STRENGTH/SEQUENCE Fluid attenuated inversion recovery (FLAIR) and T1-weighted magnetization prepared rapid gradient echo (T1-MPRAGE) sequences at 1.5 T and 3 T. ASSESSMENT The study included 313 MRI pairs of datasets. Data were analyzed with LeMan-PV and compared with a manual "reference standard" provided by a neuroradiologist. A second rater (neurologist) performed the same analysis in a subset of MRI pairs to evaluate the rating-accuracy. The Sensitivity (Se), Specificity (Sp), Accuracy (Acc), F1-score, lesion-wise False-Positive-Rate (aFPR), and other measures were used to assess LeMan-PV performance for the detection of NEL at 1.5 T and 3 T. The performance was also evaluated in the subgroup of 123 MRI pairs at 3 T. STATISTICAL TESTS Intraclass correlation coefficient (ICC) and Cohen's kappa (CK) were used to evaluate the agreement between readers. RESULTS The interreader agreement was high for detecting new lesions (ICC = 0.97, Pvalue < 10-20 , CK = 0.82, P value = 0) and good (ICC = 0.75, P value < 10-12 , CK = 0.68, P value = 0) for detecting enlarged lesions. Across all centers, scanner field strengths (1.5 T, 3 T), and for NEL, LeMan-PV achieved: Acc = 61%, Se = 65%, Sp = 60%, F1-score = 0.44, aFPR = 1.31. When both follow-ups were acquired at 3 T, LeMan-PV accuracy was higher (Acc = 66%, Se = 66%, Sp = 66%, F1-score = 0.28, aFPR = 3.03). DATA CONCLUSION In this multicenter study using clinical data settings acquired at 1.5 T and 3 T, and variations in MRI protocols, LeMan-PV showed similar sensitivity in detecting NEL with respect to other recent 3 T multicentric studies based on neural networks. While LeMan-PV performance is not optimal, its main advantage is that it provides automated clinical decision support integrated into the radiological-routine flow. EVIDENCE LEVEL 4 TECHNICAL EFFICACY: Stage 2
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