Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.12.15.472797

Leptomeningeal Enhancement in Multiple Sclerosis and Other Neurological Diseases: A Systematic Review and Meta-Analysis

Ineichen, B. V.·Tsagkas, C.·Absinta, M.·Reich, D. S.
View original source ↗Export metadata ↓

Abstract

BackgroundThe lack of systematic evidence on leptomeningeal enhancement (LME) on MRI in neurological diseases, including multiple sclerosis (MS), hampers its interpretation in clinical routine and research settings. PurposeTo perform a systematic review and meta-analysis of MRI LME in MS and other neurological diseases. Materials and MethodsIn a comprehensive literature search in Medline, Scopus, and Embase, out of 2292 publications, 459 records assessing LME in neurological diseases were eligible for qualitative synthesis. Of these, 135 were included in a random-effects model meta-analysis with subgroup analyses for MS. ResultsOf eligible publications, 161 investigated LME in neoplastic neurological (n=2392), 91 in neuroinfectious (n=1890), and 75 in primary neuroinflammatory diseases (n=4038). The LME-proportions for these disease classes were 0.47 [95%-CI: 0.37-0.57], 0.59 [95%-CI: 0.47-0.69], and 0.26 [95%-CI: 0.20-0.35], respectively. In a subgroup analysis comprising 1605 MS cases, LME proportion was 0.30 [95%-CI 0.21-0.42] with lower proportions in relapsing-remitting (0.19 [95%-CI 0.13-0.27]) compared to progressive MS (0.39 [95%-CI 0.30-0.49], p=0.002) and higher proportions in studies imaging at 7T (0.79 [95%-CI 0.64-0.89]) compared to lower field strengths (0.21 [95%-CI 0.15-0.29], p<0.001). LME in MS was associated with longer disease duration (mean difference 2.2 years [95%-CI 0.2-4.2], p=0.03), higher Expanded Disability Status Scale (mean difference 0.6 points [95%-CI 0.2-1.0], p=0.006), higher T1 (mean difference 1.6ml [95%-CI 0.1-3.0], p=0.04) and T2 lesion load (mean difference 5.9ml [95%-CI 3.2-8.6], p<0.001), and lower cortical volume (mean difference -21.3ml [95%-CI -34.7--7.9], p=0.002). ConclusionsOur study provides high-grade evidence for the substantial presence of LME in MS and a comprehensive panel of other neurological diseases. Our data could facilitate differential diagnosis of LME in clinical settings. Additionally, our meta-analysis corroborates that LME is associated with key clinical and imaging features of MS. PROSPERO No: CRD42021235026. Summary statementOur systematic review and meta-analysis synthesize leptomeningeal enhancement proportions across a comprehensive panel of neurological diseases, including multiple sclerosis, and assesses its prognostic value in multiple sclerosis. Summary dataO_LILeptomeningeal enhancement (LME) is a nonspecific imaging feature present across many neurological disorders, including neoplasm, infection, and primary neuroinflammation. C_LIO_LIThe presence of LME is associated with worse clinical and imaging outcomes in multiple sclerosis, justifying its ascertainment in clinical practice. C_LIO_LINeuroinflammatory animal models can be used to further investigate the pathophysiology of LME, including its pathological tissue signature and/or its association with cortical pathology. C_LI

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Ineichen, B. V., Tsagkas, C., Absinta, M., Reich, D. S.. 2021-12-16. Leptomeningeal Enhancement in Multiple Sclerosis and Other Neurological Diseases: A Systematic Review and Meta-Analysis. https://doi.org/10.1101/2021.12.15.472797

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Novel Tau Interaction Partners as Potential Biomarkers and Therapeutic Targets in Neurodegenerative Diseases

Alzheimers disease is a progressive neurodegenerative disorder leading to cognitive decline and ultimately death. One of the main hallmarks of this disease is the accumulation of pathological tau protein into neurofibrillary tangles. To better understand these pathological mechanisms, it is essential to characterize the tau protein interactome in health and disease. In this study, we performed a yeast two-hybrid screening using a human brain cDNA library, from which we identified 15 novel tau-interacting proteins that bind to full-length human tau, or its fragments: the N-terminus, microtubule-binding domain, or C-terminus. We subsequently validated these novel interactions using in vitro co-immunoprecipitation and colocalization assays with both physiological and pathological tau isoforms. Furthermore, their interactions with the human tau protein were analyzed using surface plasmon resonance. Finally, an in silico interactome analysis of these newly discovered tau-binding partners revealed several additional interactors that can link them to downstream processes critical to neurodegenerative pathways Our findings offer fresh insights into tau biology and highlight novel targets for therapeutic intervention and biomarker development.

neuroscience↗
bioRxiv2026

Early visual cortex is not functionally necessary for temporal attention: A TMS study

Temporal attention enhances the selective processing of information at a specific point in time and improves perception. Previous neuroimaging studies investigating its neural mechanisms have either conflated temporal attention with temporal expectation or provided correlational evidence. Thus, whether early visual cortex is functionally necessary for temporal attention remains unknown. Here, we combined psychophysics with transcranial magnetic stimulation (TMS) to examine whether V1/V2 are functionally necessary and play a causal role in temporal attention. Observers performed an orientation-discrimination task in which two consecutive stimuli, T1 and T2, were presented in the periphery, preceded by a precue providing either valid or neutral temporal information. Double-pulse TMS was delivered under four conditions: at T1 (T1-TMS), at T2 (T2-TMS), at both T1 and T2 (both-TMS), or not at all (none-TMS), to assess its effects on temporal attention and the efficacy of the stimulation was verified by pupil size analysis. Behavioral results revealed robust temporal attention benefits on d', reaction time, and the Balanced Integration Score (BIS) across all four TMS conditions, indicating that the benefits of temporal attention were unaffected by occipital TMS. Furthermore, pupil dilation was largest in the both-TMS condition, followed by the T1-TMS and T2-TMS conditions, and smallest in the none-TMS condition, providing physiological verification of the stimulation protocol. Together, these findings reveal the first causal evidence that the early visual cortex is not functionally necessary for endogenous temporal attention.

neuroscience↗
bioRxiv2026

Disentanglement of persistent and dynamic neural substrates of working memory

Competing theories of working memory have alternatively emphasized the importance of persistent and dynamic substrates of this cognitive function. Here, we directly tested these theories by computationally isolating the contributions of persistent and dynamic activity to working memory. We analyzed neuronal population activity recordings in macaques doing match/non-match working memory tasks. We first extracted signatures of persistent and dynamic activity through cue-specific temporal means, temporal principal components, and correlations of activity patterns across task epochs. We then generated synthetic data constrained by these signatures, and decoded cue stimuli from these data, separately from persistent and non-persistent neurons. We found that high decoding performance arose from a nuanced interplay of persistent and dynamic activity. Specifically, we could decode stimuli at empirical or above-chance levels across all tasks only from persistent neurons, but only after constraining correlations of activity patterns across epochs. In this way, we showed distinct roles for persistent and dynamic neuronal activity that help to unify two competing theories of working memory. More broadly, we also advanced computational controlled experiments as a principled framework for adjudicating between competing models of neuronal population activity.

neuroscience↗