Citations

OBJECTIVE Aneurysm occlusion has been used as surrogate marker of aneurysm treatment efficacy. Aneurysm occlusion scales are used to evaluate the outcome of endovascular aneurysm treatment and to monitor recurrence. These scales, however, require subjective interpretation of imaging data, which can reduce the utility and reliability of these scales and the validity of clinical studies regarding aneurysm occlusion rates. Use of a core lab with independent blinded reviewers has been implemented to enhance the validity of occlusion rate assessments in clinical trials. The degree of agreement between core labs and treating physicians has not been well studied with prospectively collected data. METHODS In this study, the authors analyzed data from the Hydrogel Endovascular Aneurysm Treatment (HEAT) trial to assess the interrater agreement between the treating physician and the blinded core lab. The HEAT trial included 600 patients across 46 sites with intracranial aneurysms treated with coiling. The treating site and the core lab independently reviewed immediate postoperative and follow-up imaging (3–12 and 18–24 months, respectively) using the Raymond-Roy occlusion classification (RROC) scale, Meyer scale, and recanalization survey. A post hoc analysis was performed to calculate interrater reliability using Cohen’s kappa. Further analysis was performed to assess whether degree of agreement varied on the basis of various factors, including scale used, timing of imaging, size of the aneurysm, imaging modality, location of the aneurysm, dome-to-neck ratio, and rupture status. RESULTS Minimal interrater agreement was noted between the core lab reviewers and the treating physicians for assessing aneurysm occlusion using the RROC grading scale (k = 0.39, 95% CI 0.38–0.40) and Meyer scale (k = 0.23, 95% CI 0.14–0.38). The degree of agreement between groups was slightly better but still weak for assessing recanalization (k = 0.45, 95% CI 0.38–0.52). Factors that significantly improved degree of agreement were scales with fewer variables, greater time to follow-up, imaging modality (digital subtraction angiography), and wide-neck aneurysms. CONCLUSIONS Assessment of aneurysm treatment outcome with commonly used aneurysm occlusion scales suffers from risk of poor interrater agreement. This supports the use of independent core labs for validation of outcome data to minimize reporting bias. Use of outcome tools with fewer point categories is likely to provide better interrater reliability. Therefore, the outcome assessment tools are ideal for clinical outcome assessment provided that they are sensitive enough to detect a clinically significant change.

AbstractData-driven machine-learning methods on neuroimaging (e.g. MRI) are of great interest for the investigation and classification of neurological diseases. However, traditional machine learning requires domain knowledge to delineate the brain regions first, followed by feature extraction from the regions. Compared with this semi-automated approach, recently developed deep learning methods have advantages since they do not require such prior knowledge; instead, deep learning methods can automatically find features that differentiate MRIs from different cohorts. In the present study, we developed a deep learning-based classification pipeline distinguishing brain MRIs of individuals with one of three types of headaches [migraine (n = 95), acute post-traumatic headache (n = 48) and persistent post-traumatic headache (n = 49)] from those of healthy controls (n = 532) and identified the brain regions that most contributed to each classification task. Our pipeline included: (i) data preprocessing; (ii) binary classification of healthy controls versus headache type using a 3D ResNet-18; and (iii) biomarker extraction from the trained 3D ResNet-18. During the classification at the second step of our pipeline, we resolved two common issues in deep learning methods, limited training data and imbalanced samples from different categories, by incorporating a large public data set and resampling among the headache cohorts. Our method achieved the following classification accuracies when tested on independent test sets: (i) migraine versus healthy controls—75% accuracy, 66.7% sensitivity and 83.3% specificity; (2) acute post-traumatic headache versus healthy controls—75% accuracy, 66.7% sensitivity and 83.3% specificity; and (3) persistent post-traumatic headache versus healthy controls—91.7% accuracy, 100% sensitivity and 83.3% specificity. The most significant biomarkers identified by the classifier for migraine were caudate, caudal anterior cingulate, superior frontal, thalamus and ventral diencephalon. For acute post-traumatic headache, lateral occipital, cuneus, lingual, pericalcarine and superior parietal regions were identified as most significant biomarkers. Finally, for persistent post-traumatic headache, the most significant biomarkers were cerebellum, middle temporal, inferior temporal, inferior parietal and superior parietal. In conclusion, our study shows that the deep learning methods can automatically detect aberrations in the brain regions associated with different headache types. It does not require any human knowledge as input which significantly reduces human effort. It uncovers the great potential of deep learning methods for classification and automatic extraction of brain imaging–based biomarkers for these headache types.

AbstractPosttraumatic headache (PTH) is the most common symptom following mild traumatic brain injury (mTBI) (also known as concussion). Migraine and PTH have similar phenotypes, and a migraine-like phenotype is common in PTH. The similarities between both headache types are intriguing and challenge a better understanding of the pathophysiological commonalities involved in migraine and PTH due to mTBI. Here, we review the PTH resting-state functional connectivity literature and compare it to migraine to assess overlap and differences in brain network function between both headache types. Migraine and PTH due to mTBI have overlapping and disease-specific widespread alterations of static and dynamic functional networks involved in pain processing as well as dysfunctional network connections between frontal regions and areas of pain modulation and pain inhibition. Although the PTH functional network literature is still limited, there is some evidence that dysregulation of the top-down pain control system underlies both migraine and PTH. However, disease-specific differences in the functional circuitry are observed as well, which may reflect unique differences in brain architecture and pathophysiology underlying both headache disorders.

ImportanceThere is limited evidence for therapeutic options for pediatric COVID-19 outside of multisystem inflammatory syndrome in children (MIS-C).ObjectiveTo determine whether the use of steroids within 2 days of admission for non–MIS-C COVID-19 in children is associated with hospital length of stay (LOS). The secondary objective was to determine their association with intensive care unit (ICU) LOS, inflammation, and fever defervescence.Design, Setting, and ParticipantsThis cohort study analyzed data retrospectively for children (<18 years) who required hospitalization for non–MIS-C COVID-19. Data from March 2020 through September 2021 were provided by 58 hospitals in 7 countries who participate in the Society of Critical Care Medicine Discovery Viral Infection and Respiratory Illness Universal Study (VIRUS) COVID-19 registry.ExposureAdministration of steroids within 2 days of admission.Main Outcomes and MeasuresLength of stay in the hospital and ICU. Adjustment for confounders was done by mixed linear regression and propensity score matching.ResultsA total of 1163 patients met inclusion criteria and had a median (IQR) age of 7 years (0.9-14.3). Almost half of all patients (601/1163, 51.7%) were male, 33.8% (392/1163) were non-Hispanic White, and 27.9% (324/1163) were Hispanic. Of the study population, 184 patients (15.8%) received steroids within 2 days of admission, and 979 (84.2%) did not receive steroids within the first 2 days. Among 1163 patients, 658 (56.5%) required respiratory support during hospitalization. Overall, patients in the steroids group were older and had greater severity of illness, and a larger proportion required respiratory and vasoactive support. On multivariable linear regression, after controlling for treatment with remdesivir within 2 days, country, race and ethnicity, obesity and comorbidity, number of abnormal inflammatory mediators, age, bacterial or viral coinfection, and disease severity according to ICU admission within first 2 days or World Health Organization ordinal scale of 4 or higher on admission, with a random intercept for the site, early steroid treatment was not significantly associated with hospital LOS (exponentiated coefficient, 0.94; 95% CI, 0.81-1.09; P = .42). Separate analyses for patients with an LOS of 2 days or longer (n = 729), those receiving respiratory support at admission (n = 286), and propensity score–matched patients also showed no significant association between steroids and LOS. Early steroid treatment was not associated with ICU LOS, fever defervescence by day 3, or normalization of inflammatory mediators.Conclusions and RelevanceSteroid treatment within 2 days of hospital admission in a heterogeneous cohort of pediatric patients hospitalized for COVID-19 without MIS-C did not have a statistically significant association with hospital LOS.

Signet-ring stromal tumor (SRST) is a rare ovarian stromal neoplasm characterized by a population of bland signet-ring cells, devoid of mucin or lipid, in a generally cellular fibromatous stroma. Previous reports have described heterogenous immunohistochemical and molecular genetic findings, including occasional nuclear β-catenin expression and/or CTNNB1 mutations. We report 10 ovarian stromal neoplasms originally diagnosed as SRST. All but 1 tumor underwent detailed immunohistochemical analysis (including β-catenin) and 5 of 10 had CTNNB1 mutation analysis performed. All tumors contained a population of morphologically bland signet-ring cells that ranged from 15% to 95% of the neoplasm, characterized by a single large empty intracytoplasmic vacuole, mostly with nuclear indentation. Six of the 10 tumors contained cellular fibroma-like areas, comprising from 10% to 85% of the neoplasm. Three of the 10 tumors were reclassified as microcystic stromal tumor with signet-ring cells on the basis of the microcyst formation and hyalinized stroma, beta-catenin and cyclin D1 nuclear expression and/or CTNNB1 mutation, CD10 staining and largely absent expression of inhibin and calretinin. In the remaining 7 tumors, the diagnosis of SRST remained, constituting the largest series of SRST reported in the literature to date. The results of our study suggest that a subset of tumors diagnosed as ovarian SRST, especially those which show β-catenin nuclear positivity and/or CTNNB1 mutation, likely represent microcystic stromal tumor with variant morphology. We also suggest that at least a subset of SRSTs without evidence of Wnt/β-catenin pathway abnormalities may be related to ovarian fibromas. We discuss the differential diagnosis of ovarian neoplasms containing signet-ring cells.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Abstract Objective The purpose of this study was to characterize cutaneous heat and light‐induced pain thresholds in people with post‐traumatic headache (PTH) compared with healthy controls (HCs). Background Photophobia and allodynia are common in PTH, and there is emerging evidence to support multimodal sensory dysfunction. Methods In this age‐ and sex‐matched cohort study, individuals with PTH ( n = 20) and HCs ( n = 20), aged 18–65 years, were recruited from an institutional database of research volunteers, from the concussion clinic, and via the use of approved flyers posted on the Mayo Clinic Campus in Scottsdale, Arizona. Participants were assessed using the Allodynia Symptom Checklist (ASC‐12), Photosensitivity Assessment Questionnaire (PAQ), State Trait Anxiety Inventory (STAI), and Beck Depression Inventory (BDI). Quantitative sensory testing quantified heat pain thresholds. A light stimulation device quantified light‐induced pain thresholds. Subsequently, heat pain thresholds were obtained immediately, 10, and 40 min after a bright light stressor. Results The mean photophobia symptom severity score, based on the PAQ, was higher in participants with PTH compared with HCs, mean 0.62 (SD = 0.25) versus mean 0.24 (SD = 0.24), p < 0.001. Light‐induced pain thresholds were lower in participants with PTH (median = 90.5 lux and quartiles = 17.8 to 378.5) compared with HCs (median = 863.5 lux and quartiles = 519.9 to 4906.5) and were independent from BDI and STAI ( p < 0.001). Allodynia scores did not differ between participants with PTH and HCs after adjusting for BDI and STAI scores. Baseline forehead heat pain thresholds were not different, participants with PTH mean 41.9°C (SD = 0.89) versus HCs mean 44.3°C (SD = 0.89), p = 0.061; however, forearm heat pain thresholds were lower in participants with PTH compared with HCs, mean 40.8°C (SD = 0.80) versus mean 44.4°C (SD = 0.80), p = 0.002. The forehead heat pain threshold change from baseline post bright light stressor in participants with PTH versus HCs was different immediately (mean −1.2 (SD = 0.53), p = 0.025), 10 min (mean −1.8 (SD = 0.74), p = 0.015), and 40 min (mean −1.8 (SD = 0.88), p = 0.047). The forearm heat pain threshold change immediately post bright light stressor in participants with PTH versus HCs was different, mean −1.9°C (SD = 0.58), p = 0.001, however, not different at 10 and 40 min. Conclusions Photophobia is higher and light‐induced pain thresholds are lower in participants with PTH. Exposure to a light stressor reduced heat pain thresholds in participants with PTH immediately post bright light stressor, but not in HCs. This study provides evidence for multimodal sensory dysfunction in people with PTH.