Faculty Bibliography

Importance/UNASSIGNED:Cannabidiol has shown efficacy in randomized clinical trials for drug-resistant epilepsy in specific syndromes that predominantly affect children. However, high-level evidence for the efficacy and safety of cannabidiol in the most common form of drug-resistant epilepsy in adults, focal epilepsy, is lacking. Objective/UNASSIGNED:To investigate the efficacy, safety, and tolerability of transdermally administered cannabidiol in adults with drug-resistant focal epilepsy. Design, Setting, and Participants/UNASSIGNED:A randomized, double-blind, placebo-controlled, multicenter clinical trial at 14 epilepsy trial centers in Australia and New Zealand. Participants were adults with drug-resistant focal epilepsy receiving a stable regimen of up to 3 antiseizure medications. Data were analyzed from July 2017 to November 2018. Interventions/UNASSIGNED:Eligible participants were randomized (1:1:1) to 195-mg or 390-mg transdermal cannabidiol or placebo twice daily for 12 weeks, after which they could enroll in an open-label extension study for up to 2 years. Main Outcomes and Measures/UNASSIGNED:Seizure frequency was self-reported using a daily diary. The primary efficacy end point was the least squares mean difference in the log-transformed total seizure frequency per 28-day period, adjusted to a common baseline log seizure rate, during the 12-week treatment period. Results/UNASSIGNED:A total of 188 patients (45% male [85 patients] and 54.8% female [103 patients]) with a mean (SD) age of 39.2 (12.78) years were randomized, treated, and analyzed (195-mg cannabidiol, 63 participants; 390-mg cannabidiol, 62 participants; placebo, 63 participants). At week 12 of the double-blind period, there was no difference in seizure frequency between placebo (mean [SD] 2.49 [1.31] seizures per 28 days) and 195-mg cannabidiol (mean [SD] 2.51 [1.15] seizures per 28 days; least squares mean difference, 0.014; 95% CI, -0.175 to 0.203; P = .89) or 390-mg cannabidiol (mean [SD] 2.59 [1.12] seizures per 28 days; least squares mean difference, 0.096; 95% CI, -0.093 to 0.285; P = .32). By month 6 of the open-label extension, 115 patients (60.8%) achieved a seizure reduction of at least 50%. Treatment-emergent adverse events occurred in 50.4% (63 of 125 participants) of the cannabidiol group vs 41.3% (26 of 63 participants) in the placebo group, with a treatment difference of 9.1% (95% CI, -6.0% to 23.6%), and occurred at similar rates in the cannabidiol groups. Few participants discontinued (7% [14 of 188 participants]), and most (98% [171 of 174 participants]) continued into the open-label extension. Conclusions and Relevance/UNASSIGNED:Both doses of transdermal cannabidiol were well tolerated and safe. No significant difference in efficacy was observed between cannabidiol and placebo during the double-blind treatment period. The open-label extension demonstrated the long-term safety, tolerability, and acceptability of transdermal cannabidiol delivery. Trial Registration/UNASSIGNED:ACTRN12616000510448 (double-blind); ACTRN12616001455459 (open-label).

In-scanner head motion systematically reduces estimated regional gray matter volumes obtained from structural brain MRI. Here, we investigate how head motion affects structural covariance networks that are derived from regional gray matter volumetric estimates. We acquired motion-affected and low-motion whole brain T1-weighted MRI in 29 healthy adult subjects and estimated relative regional gray matter volumes using a voxel-based morphometry approach. Structural covariance network analyses were undertaken while systematically increasing the number of included motion-affected scans. We demonstrate that the standard deviation in regional gray matter estimates increases as the number of motion-affected scans increases. This increases pairwise correlations between regions, a key determinant for construction of structural covariance networks. We further demonstrate that head motion systematically alters graph theoretic metrics derived from these networks. Finally, we present evidence that weighting correlations using image quality metrics can mitigate the effects of head motion. Our findings suggest that in-scanner head motion is a source of error that violates the assumption that structural covariance networks reflect neuroanatomical connectivity between brain regions. Results of structural covariance studies should be interpreted with caution, particularly when subject groups are likely to move their heads in the scanner.

In large clinical centers a small subset of patients present with hydrocephalus that requires surgical treatment. We aimed to develop a screening tool to detect such cases from the head MRI with performance comparable to neuroradiologists. We leveraged 496 clinical MRI exams collected retrospectively at a single clinical site from patients referred for any reason. This diagnostic dataset was enriched to have 259 hydrocephalus cases. A 3D convolutional neural network was trained on 16 manually segmented exams (ten hydrocephalus) and subsequently used to automatically segment the remaining 480 exams and extract volumetric anatomical features. A linear classifier of these features was trained on 240 exams to detect cases of hydrocephalus that required treatment with surgical intervention. Performance was compared to four neuroradiologists on the remaining 240 exams. Performance was also evaluated on a separate screening dataset of 451 exams collected from a routine clinical population to predict the consensus reading from four neuroradiologists using images alone. The pipeline was also tested on an external dataset of 31 exams from a 2nd clinical site. The most discriminant features were the Magnetic Resonance Hydrocephalic Index (MRHI), ventricle volume, and the ratio between ventricle and brain volume. At matching sensitivity, the specificity of the machine and the neuroradiologists did not show significant differences for detection of hydrocephalus on either dataset (proportions test, p > 0.05). ROC performance compared favorably with the state-of-the-art (AUC 0.90-0.96), and replicated in the external validation. Hydrocephalus cases requiring treatment can be detected automatically from MRI in a heterogeneous patient population based on quantitative characterization of brain anatomy with performance comparable to that of neuroradiologists.

Fulminant IIH in pregnancy requires multidisciplinary collaboration and immediate CSF diversion.

OBJECTIVE:Recent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features. METHODS:We extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance. RESULTS:), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI. SIGNIFICANCE/CONCLUSIONS:From cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

Encephalopathy, a common condition among patients hospitalized with COVID-19, can be a challenge to manage and negatively affect prognosis. While encephalopathy may present clinically as delirium, subsyndromal delirium, or coma and may be a result of systemic causes such as hypoxia, COVID-19 has also been associated with more prolonged encephalopathy due to less common but nevertheless severe complications, such as inflammation of the brain parenchyma (with or without cerebrovascular involvement), demyelination, or seizures, which may be disproportionate to COVID-19 severity and require specific management. Given the large number of patients hospitalized with severe acute respiratory syndrome coronavirus-2 infection, even these relatively unlikely complications are increasingly recognized and are particularly important because they require specific management. Therefore, the aim of this review is to provide pragmatic guidance on the management of COVID-19 encephalopathy through consensus agreement of the Global COVID-19 Neuro Research Coalition. A systematic literature search of MEDLINE, medRxiv, and bioRxiv was conducted between January 1, 2020, and June 21, 2021, with additional review of references cited within the identified bibliographies. A modified Delphi approach was then undertaken to develop recommendations, along with a parallel approach to score the strength of both the recommendations and the supporting evidence. This review presents analysis of contemporaneous evidence for the definition, epidemiology, and pathophysiology of COVID-19 encephalopathy and practical guidance for clinical assessment, investigation, and both acute and long-term management.

Plexiform Neurofibromas (PN) are a common manifestation of the genetic disorder neurofibromatosis type 1 (NF1). These benign nerve sheath tumors often cause significant morbidity, with treatment options limited historically to surgery. There have been tremendous advances over the past two decades in our understanding of PN, and the recent regulatory approvals of the MEK inhibitor selumetinib are reshaping the landscape for PN management. At present, there is no agreed upon PN definition, diagnostic evaluation, surveillance strategy, or clear indications for when to initiate treatment and selection of treatment modality. In this review, we address these questions via consensus recommendations from a panel of multi-disciplinary NF1 experts.

Despite its increasing recognition and extensive research, there is no unifying hypothesis on the pathophysiology of the postural tachycardia syndrome. In this cross-sectional study, we examined the role of fear conditioning and its association with tachycardia and cerebral hypoperfusion upon standing in 28 patients with postural tachycardia syndrome (31 ± 12 years old, 25 women) and 21 matched controls. We found that patients had higher somatic vigilance (p = 0.0167) and more anxiety (p < 0.0001). They also had a more pronounced anticipatory tachycardia right before assuming the upright position in a tilt-table test (p = 0.015), a physiologic indicator of fear conditioning to orthostasis. While standing, patients had faster heart rate (p < 0.001), higher plasma catecholamine levels (p = 0.020), lower end-tidal CO2 (p = 0.005), and reduced middle cerebral artery blood flow velocity (p = 0.002). Multi-linear logistic regression modeling showed that both epinephrine secretion and excessive somatic vigilance predicted the magnitude of the tachycardia and the hyperventilation. These findings suggest that the postural tachycardia syndrome is a functional psychogenic disorder in which standing may acquire a frightful quality, so that even when experienced alone, it elicits a fearful conditioned response. Heightened somatic anxiety is associated with and may predispose to a fear-conditioned hyperadrenergic state when standing. Our results have therapeutic implications.