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Objective Localization related epilepsy (LRE) is increasingly accepted as a network disorder. To better understand the network specific characteristics of LRE, we defined individual epilepsy networks and compared them across patients. Methods The epilepsy network was defined in the slow cortical potential frequency band in 10 patients using intracranial EEG data obtained during interictal periods. Cortical regions were included in the epilepsy network if their connectivity pattern was similar to the connectivity pattern of the seizure onset electrode contact. Patients were subdivided into frontal, temporal, and posterior quadrant cohorts according to the anatomic location of seizure onset. Jaccard similarity was calculated within each cohort to assess for similarity of the epilepsy network between patients within each cohort. Results All patients exhibited an epilepsy network in the slow cortical potential frequency band. The topographic distribution of this correlated network activity was found to be unique at the single subject level. Conclusions The epilepsy network was unique at the single patient level, even between patients with similar seizure onset locations. Significance We demonstrated that the epilepsy network is patient-specific. This is in keeping with our current understanding of brain networks and identifies the patient-specific epilepsy network as a possible biomarker in LRE.

Background: Complete resection of focal malformations of cortical development (MCD) has been recognized as crucial for the success of epilepsy surgery. However, many of these lesions escape detection using even state-of-the-art epilepsy protocol MRI imaging. This study evaluates the concurrence of radiographic and histopathologic findings of MCD in patients with refractory temporal lobe epilepsy (TLE) and defines the predictive value of EEG findings in the detection of MCD. Materials and Methods: Pre-operative MRI, scalp VEEG, and post-operative surgical pathology reports from 34 consecutive patients treated for refractory TLE by surgical resection over a ten year period were included in analysis. Radiographic findings of MCD were correlated with histopathologic findings of MCD and compared against pre-operative interictal scalp EEG findings. Results: 66.7% of focal cortical dysplasias (FCD) identified on pathology and all cases of mild MCD (mMCD) were missed on pre-operative MRI. The description of a rhythmic or continuous interictal abnormality on pre-operative VEEG corresponds to a sensitivity of 73.1% and a specificity of 62.5% in detecting either FCD or mMCD. Of the patients who had a radiographically occult FCD, 80% had either a continuous or rhythmic interictal abnormality described in the interpretation of their pre-operative VEEG. Conclusion: This study highlights the high prevalence of MCDs in refractory TLE and the high rate of missed MCDs on pre-operative MRI. Findings here suggest that pre-operative scalp EEG may be able to provide additional information in the pre-operative detection of MCDs and therefore inform surgical decision making.

Background We and others have identified mutually exclusive molecular subgroups of meningiomas; however, the implications of this classification for clinical prognostication remain unclear. Integrated genomic and epigenomic analyses implicate unique oncogenic processes associated with each subgroup, suggesting the potential for divergent clinical courses. The aim of this study was to understand the associated clinical outcomes of each subgroup, as this could optimize treatment for patients. Methods We analyzed outcome data for 469 meningiomas of known molecular subgroup, including extent of resection, postoperative radiation, surveillance imaging, and time to recurrence, when applicable. Statistical relationships between outcome variables and subgroup were assessed. Features previously associated with recurrence were further investigated after stratification by subgroup. We used Kaplan–Meier analyses to compare progression-free survival, and identified factors significantly associated with recurrence using Cox proportional hazards modeling. Results Meningioma molecular subgroups exhibited divergent clinical courses at 2 years of follow-up, with several aggressive subgroups (NF2, PI3K, HH, tumor necrosis factor receptor–associated factor 7 [TRAF7]) recurring at an average rate of 22 times higher than others (KLF4, POLR2A, SMARCB1). PI3K-activated tumors recurred earlier than other subgroups but had intermediate long-term outcome. Among low-grade tumors, HH and TRAF7 meningiomas exhibited elevated recurrence compared with other subgroups. Recurrence of NF2 tumors was associated with male sex, high grade, and elevated Ki-67. Multivariate analysis identified molecular subgroup as an independent predictor of recurrence, along with grade and previous recurrence. Conclusion We describe distinct clinical outcomes and recurrence rates associated with meningioma molecular subgroups. Our findings emphasize the importance of genomic characterization to guide postoperative management decisions for meningiomas.

Up to 80% of meningiomas are classified as clinically low-grade, however, a subset of these ‘benign’ cases will ultimately recur and require additional treatment. The role of molecular subgroup in meningioma recurrence has not been thoroughly investigated, despite correlations of this variable with other clinical features. Indeed, epigenetic and transcriptional evidence supports involvement of distinct oncogenic processes within each subgroup, and as shown in other brain tumors, this may result in divergent clinical courses. In the present study, we classified 429 meningiomas into six established molecular subgroups based on genomic driver, and investigated associations of each subgroup with tumor recurrence. At two years of follow-up, we observed differences in progression free survival curves among relatively aggressive (NF2-loss, PI3K-activated, Hedgehog-activated) and quiescent (KLF4-mutant, SMARCB1-mutant, POLR2A-mutant) subgroups (log rank p = 4.3 x 10-2), with the former group recurring at a rate 14x higher. We found PI3K-activated meningiomas recurred significantly earlier than other subgroups (average time to recurrence of 19.2 months; p = 2.2 x 10-2), though we observed an intermediate long-term outcome relative to the Hedgehog and NF2 lesions. Overall, Hedgehog tumors recurred significantly more frequently than other low-grade meningiomas (adj. p = 3.1 x 10-2), and this subgroup was found to be an independent predictor of progression free survival using cox proportional hazards modelling (HR = 3.1; p = 2.4 x 10-2). By contrast, the aggressiveness of NF2 meningiomas was found to depend upon gender, WHO grade, and elevated Ki-67 index, and this subgroup was not an independent prognostic predictor. Our results suggest molecular subgroup is predictive of recurrence in low-grade meningiomas, and thus is an important consideration in post-operative management decisions. Routine genotyping to detect Hedgehog and PI3K mutant lesions may identify patients that would benefit from closer follow-up and consideration of adjuvant therapies.

INTRODUCTION Vestibular schwannomas (VS) are known to be slow-growing lesions that can present significant issues for patients. Here, we sought to better understand their outcomes and risks for recurrence. METHODS We retrospectively reviewed clinical outcomes data for patients who had VS tumor that underwent whole-exome sequencing after surgical resection between 2015 and 2018. The association between any two categorical variables was investigated using Fisher’s exact test. The mean of a continuous variable was compared between groups using either a two-tailed t-test or ANOVA. RESULTS Forty patients met our inclusion criteria. Interestingly, men were more likely than women to experience recurrence (p = 0.05). In accordance with previous research demonstrating a significant association between NF2 and bilateral vestibular schwannomas, most VS were NF2-mutants, with only four being were non-NF2. Pre-operative tumor size significantly correlated with progression-free survival time from surgical resection to recurrence, such that larger tumors were more likely to recur slower post-operatively (p = 0.043). There appeared to be no significant association between the extent of surgical resection (EOR) and recurrence (p = 0.653). In addition, there was no significant difference in post-operative complications or clinical outcomes, including EOR and facial nerve function, between different surgical approaches (p > 0.30). Patients with pre-operative intra-tumoral hemorrhage were more likely to have smaller tumors, suggesting they present more acutely (p = 0.119). Finally, patients with NF2-mutated VS had a longer time from original diagnosis to surgery than patients who had non-NF2 VS mutants (p = 0.041). CONCLUSIONS Surgery for VS offers good clinical outcomes overall with low recurrence rates, regardless of prior treatment. Though not related to Ki67, larger tumors appear to confer a slower growth potential and lower risk of recurrence over time.

OBJECTIVERecent large-cohort sequencing studies have investigated the genomic landscape of meningiomas, identifying somatic coding alterations in NF2, SMARCB1, SMARCE1, TRAF7, KLF4, POLR2A, BAP1, and members of the PI3K and Hedgehog signaling pathways. Initial associations between clinical features and genomic subgroups have been described, including location, grade, and histology. However, further investigation using an expanded collection of samples is needed to confirm previous findings, as well as elucidate relationships not evident in smaller discovery cohorts.METHODSTargeted sequencing of established meningioma driver genes was performed on a multiinstitution cohort of 3016 meningiomas for classification into mutually exclusive subgroups. Relevant clinical information was collected for all available cases and correlated with genomic subgroup. Nominal variables were analyzed using Fisher’s exact tests, while ordinal and continuous variables were assessed using Kruskal-Wallis and 1-way ANOVA tests, respectively. Machine-learning approaches were used to predict genomic subgroup based on noninvasive clinical features.RESULTSGenomic subgroups were strongly associated with tumor locations, including correlation of HH tumors with midline location, and non-NF2 tumors in anterior skull base regions. NF2 meningiomas were significantly enriched in male patients, while KLF4 and POLR2A mutations were associated with female sex. Among histologies, the results confirmed previously identified relationships, and observed enrichment of microcystic features among “mutation unknown” samples. Additionally, KLF4-mutant meningiomas were associated with larger peritumoral brain edema, while SMARCB1 cases exhibited elevated Ki-67 index. Machine-learning methods revealed that observable, noninvasive patient features were largely predictive of each tumor’s underlying driver mutation.CONCLUSIONSUsing a rigorous and comprehensive approach, this study expands previously described correlations between genomic drivers and clinical features, enhancing our understanding of meningioma pathogenesis, and laying further groundwork for the use of targeted therapies. Importantly, the authors found that noninvasive patient variables exhibited a moderate predictive value of underlying genomic subgroup, which could improve with additional training data. With continued development, this framework may enable selection of appropriate precision medications without the need for invasive sampling procedures.

BACKGROUND Meningiomas can be classified into six genomic subgroups based on mutations in NF2, SMARCB1, KLF4, POLR2A, or activating variants in the PI3K or Hedgehog signaling pathways. Previous work has identified specific associations of driver events with clinical and molecular features, such as tumor location. However, their utility in predicting post-operative patient outcomes is not well-explored. Similar to recently described epigenetic signatures, underlying genomic subgroup may provide prognostic value in meningioma management. METHODS Targeted sequencing data was used to classify over 500 meningiomas into established genomic subgroups, and available patient outcome data was assembled based on retrospective chart reviews. Collected data included recurrence (based on imaging), extent of resection (EOR), use of post-operative radiation, and radiologic follow-up period. Statistical associations between genomic subgroup and recurrence were assessed using Fisher’s exact, Kaplan-Meier, and Cox proportional hazards modeling, including stratification based on use of radiation, EOR, grade, and location. RESULTS Meningiomas in the PI3K subgroup exhibited higher rates of early recurrence during the first five post-operative years. This subgroup affiliation was found to be an independent predictor of recurrence free survival from Ki-67, grade, and other clinical features. By contrast, recurrence was rare in the POLR2A, SMARCB1, and KLF4 subgroups, and was typically associated with use of post-operative radiation in these cases. The longest average recurrence free survival was observed in POLR2A mutant meningiomas. CONCLUSIONS Our analysis identifies divergence in meningioma patient outcomes based on genomic subgroup and suggests patients with PI3K activating events may require closer surveillance. These tumors, which often occur near and encase critical neurovascular structures along the sphenoid wing, may further benefit from consideration of radiation and emerging precision therapies. Conversely, other subgroups rarely recur, suggesting caution be invoked with use of potentially morbid adjuvant treatment.

BACKGROUND Previous studies have established several meningioma genomic subgroups, defined by the mutually exclusive genomic drivers. However, we distinguished a small subset of meningiomas simultaneously harboring multiple drivers from different genomic subgroups, thus referred to as “multiple-driver meningiomas”, that has not been previously investigated. We aimed to characterize the genomic landscape and clinical features of multiple-driver meningiomas. METHODS We identified 42 cases of multiple-driver meningiomas from a cohort of 3,016 cases screened for genomic drivers via molecular inversion probe sequencing (MIPS) and/or whole-exome sequencing (WES) previously in our laboratory. All driver mutations were validated via Sanger sequencing and chromosome 22 loss was accessed with qPCR. Clinical information was collected and genome-to-clinical correlations were statistically analyzed. We selected 10 multiple-driver meningioma cases for tumor-normal WES for further characterization of genomic architecture. RESULTS Multiple-driver meningiomas were significantly enriched for NF2 alteration (p< 0.001), had significantly higher WHO grade (p= 0.005) and proportion of recurrent tumors (p= 0.007) when compared with “single-driver meningiomas”, i.e. harboring driver alterations from a single genomic subgroup. Among female cases, those with multiple drivers were nearly four times more likely to be high-grade (II or III) compared to single-driver female samples (48.6% vs. 12.6%, p< 0.001). Among tumors harboring NF2 alteration, multiple-driver meningiomas demonstrated skull base predilection compared with single-driver meningiomas (50.0% vs. 27.9%, p= 0.005). WES analysis of 10 multiple-driver meningiomas identified 1p and/or 14q loss in 60% of cases. Clonality analysis revealed the presence of sub-clonal cell populations in 9 cases with all driver mutations clustered into the founding clone in 7 cases, suggesting their acquisition in the early phase of tumor development. CONCLUSION Multiple-driver meningiomas demonstrate distinct genomic and clinical features that distinguish them as clinically aggressive. They frequently occur in surgically challenging skull base locations, and are more prevalent among high-grade and recurrent cases.

Background Hospital readmissions within 30 days after discharge are increasingly recognized as markers of inpatient quality of care and significant contributors to rising healthcare expenditures. Identifying potentially preventable readmission causes and developing targeted interventions is a national priority. Objectives To determine rate, reasons, and potential for prevention for 30-day unplanned neurosurgical readmissions at Yale-New Haven Hospital. Methods Over a 6-month period, all patients who had been discharged from YNHH after receiving care from the Department of Neurosurgery and readmitted within 30 days were retrospectively identified. In-depth chart analysis was performed to uncover relevant medical/social history and admission/readmission details. Results During 6 months, 84 (6.6%) of 1,279 patients were readmitted within 30 days. Reasons for readmission were categorized into miscellaneous (34%), non-surgical site infections (15%), postoperative wound complications (14%), intracranial hemorrhage (13%), neurological deficits: brain (10%), CSF device malfunction (8%), neurological deficits: spine (4%), and ischemic CNS events (2%). Most complications were moderate (54%) or mild (31%). Overall, 17% of readmissions were determined to be likely preventable, 10% – potentially preventable, 73% – not preventable. Notably, 42% of postoperative wound complications and 32% of brain-related neurological deficits could have been prevented. 49% of readmissions were related to initial hospitalization and 12% resulted from inappropriate post-discharge care; 34% and 88% of those, respectively, were preventable. Conclusions Overall, 27% of 30-day neurosurgical readmissions were determined to be potentially preventable. Underlying reasons were identified and will be used to design targeted interventions. Preventing postoperative wound complications and providing appropriate discharge arrangements/instructions are the most promising areas of improvement.