DNA damage response in brain tumors: A Society for Neuro-Oncology consensus review on mechanisms and translational efforts in neuro-oncology.

DNA damage response (DDR) mechanisms are critical to maintenance of overall genomic stability, and their dysfunction can contribute to oncogenesis. Significant advances in our understanding of DDR pathways have raised the possibility of developing therapies that exploit these processes. In this expert-driven consensus review, we examine mechanisms of response to DNA damage, progress in development of DDR inhibitors in IDH-wild-type glioblastoma and IDH-mutant gliomas, and other important considerations such as biomarker development, preclinical models, combination therapies, mechanisms of resistance and clinical trial design considerations.

Determinants of Symptomatic Intracranial Progression After an Initial Stereotactic Radiosurgery Course.

Purpose: Clinical and imaging surveillance of patients with brain metastases is important after stereotactic radiosurgery (SRS) because many will experience intracranial progression (ITCP) requiring multidisciplinary management. The prognostic significance of neurologic symptoms at the time of ITCP is poorly understood. Methods and Materials: This was a multi-institutional, retrospective cohort study from 2015 to 2020, including all patients with brain metastases completing an initial course of SRS. The primary outcome was overall survival (OS) by presence of neurologic symptoms at ITCP. OS, freedom from ITCP (FF-ITCP), and freedom from symptomatic ITCP (FF-SITCP) were assessed via Kaplan-Meier method. Cox proportional hazard models tested parameters impacting FF-ITCP and FF-SITCP. Results: Among 1383 patients, median age was 63.4 years, 55% were female, and common primaries were non-small cell lung (49%), breast (15%), and melanoma (9%). At a median follow-up of 8.72 months, asymptomatic and symptomatic ITCP were observed in 504 (36%) and 194 (14%) patients, respectively. The majority of ITCP were distant ITCP (79.5%). OS was worse with SITCP (median, 10.2 vs 17.9 months, P < .001). SITCP was associated with clinical factors including total treatment volume (P = .012), melanoma histology (P = .001), prior whole brain radiation therapy (P = .003), number of brain metastases (P < .001), interval of 1 to 2 years from primary and brain metastasis diagnosis (P = .012), controlled extracranial disease (P = .042), and receipt of pre-SRS chemotherapy (P = .015). Patients who were younger and received post-SRS chemotherapy (P = .001), immunotherapy (P < .001), and targeted or small-molecule inhibitor therapy (P < .026) had better FF-SITCP. Conclusions: In this cohort study of patients with brain metastases completing SRS, neurologic symptoms at ITCP is prognostic for OS. This data informs post-SRS surveillance in clinical practice as well as future prospective studies needed in the modern management of brain metastases.

A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation.

Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by expert manually refined segmentations of three distinct meningioma sub-compartments: enhancing tumor, non-enhancing tumor, and surrounding non-enhancing T2/FLAIR hyperintensity. Basic demographic data are provided including age at time of initial imaging, sex, and CNS WHO grade. The goal of releasing this dataset is to facilitate the development of automated computational methods for meningioma segmentation and expedite their incorporation into clinical practice, ultimately targeting improvement in the care of meningioma patients.

Dose-Incorporated Deep Ensemble Learning for Improving Brain Metastasis Stereotactic Radiosurgery Outcome Prediction.

PURPOSE: To develop a novel deep ensemble learning model for accurate prediction of brain metastasis (BM) local control outcomes after stereotactic radiosurgery (SRS). METHODS AND MATERIALS: A total of 114 brain metastases (BMs) from 82 patients were evaluated, including 26 BMs that developed biopsy-confirmed local failure post-SRS. The SRS spatial dose distribution (Dmap) of each BM was registered to the planning contrast-enhanced T1 (T1-CE) magnetic resonance imaging (MRI). Axial slices of the Dmap, T1-CE, and planning target volume (PTV) segmentation (PTVseg) intersecting the BM center were extracted within a fixed field of view determined by the 60% isodose volume in Dmap. A spherical projection was implemented to transform planar image content onto a spherical surface using multiple projection centers, and the resultant T1-CE/Dmap/PTVseg projections were stacked as a 3-channel variable. Four Visual Geometry Group (VGG-19) deep encoders were used in an ensemble design, with each submodel using a different spherical projection formula as input for BM outcome prediction. In each submodel, clinical features after positional encoding were fused with VGG-19 deep features to generate logit results. The ensemble's outcome was synthesized from the 4 submodel results via logistic regression. In total, 10 model versions with random validation sample assignments were trained to study model robustness. Performance was compared with (1) a single VGG-19 encoder, (2) an ensemble with a T1-CE MRI as the sole image input after projections, and (3) an ensemble with the same image input design without clinical feature inclusion. RESULTS: The ensemble model achieved an excellent area under the receiver operating characteristic curve (AUCROC: 0.89 ± 0.02) with high sensitivity (0.82 ± 0.05), specificity (0.84 ± 0.11), and accuracy (0.84 ± 0.08) results. This outperformed the MRI-only VGG-19 encoder (sensitivity: 0.35 ± 0.01, AUCROC: 0.64 ± 0.08), the MRI-only deep ensemble (sensitivity: 0.60 ± 0.09, AUCROC: 0.68 ± 0.06), and the 3-channel ensemble without clinical feature fusion (sensitivity: 0.78 ± 0.08, AUCROC: 0.84 ± 0.03). CONCLUSIONS: Facilitated by the spherical image projection method, a deep ensemble model incorporating Dmap and clinical variables demonstrated excellent performance in predicting BM post-SRS local failure. Our novel approach could improve other radiation therapy outcome models and warrants further evaluation.

Coexisting Biopsy-Diagnosed Dementia and Glioblastoma.

Both glioblastoma (GBM) and dementia are devastating diseases with limited treatments that are usually not curative. Having clinically diagnosed dementia with an associated biopsy-proven etiology and a coexisting GBM diagnosis is a rare occurrence. The relationship between the development of neurodegenerative dementia and GBM is unclear, as there are conflicting reports in the literature. We present two cases of simultaneous biopsy-proven dementia, one with Alzheimer's disease (AD) and GBM, and one with cerebral amyloid angiopathy (CAA) and GBM. We discuss how these diseases may be associated. Whether one pathologic process begins first or develops concurrently is unknown, but certain molecular pathways of dementia and GBM appear directly related while others inversely related. Further investigations of these close molecular relationships between dementia and GBM could lead to development of improved diagnostic tools and therapeutic interventions for both diseases.

Mechanisms of telomere maintenance and associated therapeutic vulnerabilities in malignant gliomas.

A majority of cancers (~85%) activate the enzyme telomerase to maintain telomere length over multiple rounds of cellular division. Telomerase-negative cancers activate a distinct, telomerase-independent mechanism of telomere maintenance termed alternative lengthening of telomeres (ALT). ALT uses homologous recombination to maintain telomere length and exhibits features of break-induced DNA replication. In malignant gliomas, the activation of either telomerase or ALT is nearly ubiquitous in pediatric and adult tumors, and the frequency with which these distinct telomere maintenance mechanisms (TMMs) is activated varies according to genetically defined glioma subtypes. In this review, we summarize the current state of the field of TMMs and their relevance to glioma biology and therapy. We review the genetic alterations and molecular mechanisms leading to telomerase activation or ALT induction in pediatric and adult gliomas. With this background, we review emerging evidence on strategies for targeting TMMs for glioma therapy. Finally, we comment on critical gaps and issues for moving the field forward to translate our improved understanding of glioma telomere maintenance into better therapeutic strategies for patients.

Effects of Ataxia-Telangiectasia Mutated Variants on Radionecrosis and Local Control After Stereotactic Radiation Surgery for Non-Small Cell Lung Cancer Brain Metastases.

Purpose: Genetic variants affecting the radiation response protein ataxia-telangiectasia mutated (ATM) have been associated with increased adverse effects of radiation but also with improved local control after conventional radiation therapy. However, it is unknown whether ATM variants affect rates of radionecrosis (RN) and local intracranial progression (LIP) after stereotactic radiosurgery (SRS) for brain metastases. Methods and Materials: Patients undergoing an initial course of SRS for non-small cell lung cancer (NSCLC) brain metastases at a single institution were retrospectively identified. Kaplan-Meier estimates were calculated and Cox proportional hazards testing was performed based on ATM variant status. Results: A total of 541 patients completed SRS for brain metastasis secondary to NSCLC, of whom 260 completed molecular profiling. Variants of ATM were identified in 36 cases (13.8%). Among patients who completed molecular profiling, RN incidence was 4.9% (95% CI, 1.6%-8.2%) at 6 months and 9.9% (95% CI, 4.8%-15.0%) at 12 months. Incidence of RN was not significantly increased among patients with ATM variants, with an RN incidence of 5.3% (95% CI, 0.0%-15.3%) at both 6 and 12 months (P = .46). For all patients who completed genomic profiling, LIP was 5.4% (95% CI, 2.4%-8.4%) at 6 months and 9.8% (5.5%-14.1%) at 12 months. A significant improvement in LIP was not detected among patients with ATM variants, with an LIP incidence of 3.1% (0.0%-9.1%) at both 6 and 12 months (P = .26). Although differences according to ATM variant type (pathologic variant or variant of unknown significance) did not reach significance, no patients with ATM pathologic variants experienced LIP. Conclusions: We did not detect significant associations between ATM variant status and RN or LIP after SRS for NSCLC brain metastases. The current data set allows estimation of patient cohort sizes needed to power future investigations to identify genetic variants that associate with significant differences in outcomes after SRS.

Understanding and therapeutically exploiting cGAS/STING signaling in glioblastoma.

Since the discovery that cGAS/STING recognizes endogenous DNA released from dying cancer cells and induces type I interferon and antitumor T cell responses, efforts to understand and therapeutically target the STING pathway in cancer have ensued. Relative to other cancer types, the glioma immune microenvironment harbors few infiltrating T cells, but abundant tumor-associated myeloid cells, possibly explaining disappointing responses to immune checkpoint blockade therapies in cohorts of patients with glioblastoma. Notably, unlike most extracranial tumors, STING expression is absent in the malignant compartment of gliomas, likely due to methylation of the STING promoter. Nonetheless, several preclinical studies suggest that inducing cGAS/STING signaling in the glioma immune microenvironment could be therapeutically beneficial, and cGAS/STING signaling has been shown to mediate inflammatory and antitumor effects of other modalities either in use or being developed for glioblastoma therapy, including radiation, tumor-treating fields, and oncolytic virotherapy. In this Review, we discuss cGAS/STING signaling in gliomas, its implications for glioma immunobiology, compartment-specific roles for STING signaling in influencing immune surveillance, and efforts to target STING signaling - either directly or indirectly - for antiglioma therapy.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

Long-Term Intracranial Outcomes With Combination Dual Immune-Checkpoint Blockade and Stereotactic Radiosurgery in Patients With Melanoma and Non-Small Cell Lung Cancer Brain Metastases.

PURPOSE: The intracranial benefit of offering dual immune-checkpoint inhibition (D-ICPI) with ipilimumab and nivolumab to patients with melanoma or non-small cell lung cancer (NSCLC) receiving stereotactic radiosurgery (SRS) for brain metastases (BMs) is unknown. We hypothesized that D-ICPI improves local control compared with SRS alone. METHODS AND MATERIALS: Patients with melanoma or NSCLC treated with SRS from 2014 to 2022 were evaluated. Patients were stratified by treatment with D-ICPI, single ICPI (S-ICPI), or SRS alone. Local recurrence, intracranial progression (IP), and overall survival were estimated using competing risk and Kaplan-Meier analyses. IP included both local and distant intracranial recurrence. RESULTS: Two hundred eighty-eight patients (44% melanoma, 56% NSCLC) with 1,704 BMs were included. Fifty-three percent of patients had symptomatic BMs. The median follow-up was 58.8 months. Twelve-month local control rates with D-ICPI, S-ICPI, and SRS alone were 94.73% (95% CI, 91.11%-96.90%), 91.74% (95% CI, 89.30%-93.64%), and 88.26% (95% CI, 84.07%-91.41%). On Kaplan-Meier analysis, only D-ICPI was significantly associated with reduced local recurrence (P = .0032). On multivariate Cox regression, D-ICPI (hazard ratio [HR], 0.4003; 95% CI, 0.1781-0.8728; P = .0239) and planning target volume (HR, 1.022; 95% CI, 1.004-1.035; P = .0059) correlated with local control. One hundred seventy-three (60%) patients developed IP. The 12-month cumulative incidence of IP was 41.27% (95% CI, 30.27%-51.92%), 51.86% (95% CI, 42.78%-60.19%), and 57.15% (95% CI, 44.98%-67.59%) after D-ICPI, S-ICPI, and SRS alone. On competing risk analysis, only D-ICPI was significantly associated with reduced IP (P = .0408). On multivariate Cox regression, D-ICPI (HR, 0.595; 95% CI, 0.373-0.951; P = .0300) and presentation with >10 BMs (HR, 2.492; 95% CI, 1.668-3.725; P < .0001) remained significantly correlated with IP. The median overall survival after D-ICPI, S-ICPI, and SRS alone was 26.1 (95% CI, 15.5-40.7), 21.5 (16.5-29.6), and 17.5 (11.3-23.8) months. S-ICPI, fractionation, and histology were not associated with clinical outcomes. There was no difference in hospitalizations or neurologic adverse events between cohorts. CONCLUSIONS: The addition of D-ICPI for patients with melanoma and NSCLC undergoing SRS is associated with improved local and intracranial control. This appears to be an effective strategy, including for patients with symptomatic or multiple BMs.

Mining cancer genomes for change-of-metabolic-function mutations.

Enzymes with novel functions are needed to enable new organic synthesis techniques. Drawing inspiration from gain-of-function cancer mutations that functionally alter proteins and affect cellular metabolism, we developed METIS (Mutated Enzymes from Tumors In silico Screen). METIS identifies metabolism-altering cancer mutations using mutation recurrence rates and protein structure. We used METIS to screen 298,517 cancer mutations and identify 48 candidate mutations, including those previously identified to alter enzymatic function. Unbiased metabolomic profiling of cells exogenously expressing a candidate mutant (OGDHLp.A400T) supports an altered phenotype that boosts in vitro production of xanthosine, a pharmacologically useful chemical that is currently produced using unsustainable, water-intensive methods. We then applied METIS to 49 million cancer mutations, yielding a refined set of candidates that may impart novel enzymatic functions or contribute to tumor progression. Thus, METIS can be used to identify and catalog potentially-useful cancer mutations for green chemistry and therapeutic applications.

Single-fraction Radiation Treatment Dose Response in a Genetically Engineered Mouse Model of Medulloblastoma.

Medulloblastoma is the most common malignant brain tumor of children. Although standard of care radiotherapy for pediatric medulloblastoma (PM) can lead to long-term remission or cure in many patients, it can also cause life-long cognitive impairment and other adverse effects. The pathophysiological mechanisms involved in radiation-induced cerebral damage are incompletely understood, and their elucidation may lead to interventions that mitigate radiation toxicity. To explore the mechanisms of radiation-induced cerebral damage, transgenic mouse models of PM and non-tumor-bearing controls were exposed to radiation doses that ranged from 0 to 30 Gy. Between 0-20 Gy, a significant dose-dependent reduction in tumor-associated hydrocephalus and increase in overall survival were observed. However, at 30 Gy, hydrocephalus incidence increased and median overall survival fell to near-untreated levels. Immunohistochemistry revealed that both tumor-bearing and non-tumor-bearing mice treated with 30 Gy of radiation had significantly more reactive astrocytes and microvascular damage compared to untreated controls. This effect was persistent across mice that were given 1 and 2 weeks of recovery time after irradiation. Our data suggest that radiation therapy promotes neural death by inducing long-term neuroinflammation in PM, suggesting radiation delivery methods that limit inflammation may be effective at widening the therapeutic window of radiation therapy in PM patients.

ABL1 and ABL2 promote medulloblastoma leptomeningeal dissemination.

Background: Medulloblastoma is the most common malignant pediatric brain tumor, and leptomeningeal dissemination (LMD) of medulloblastoma both portends a poorer prognosis at diagnosis and is incurable at recurrence. The biological mechanisms underlying LMD are unclear. The Abelson (ABL) tyrosine kinase family members, ABL1 and ABL2, have been implicated in cancer cell migration, invasion, adhesion, metastasis, and chemotherapy resistance, and are upstream mediators of the oncogene c-MYC in fibroblasts and lung cancer cells. However, their role in medulloblastoma has not yet been explored. The purpose of this work was to elucidate the role of ABL1/2 in medulloblastoma LMD. Methods: ABL1 and ABL2 mRNA expression of patient specimens was analyzed. shRNA knockdowns of ABL1/2 and pharmacologic inhibition of ABL1/2 were used for in vitro and in vivo analyses of medulloblastoma LMD. RNA sequencing of ABL1/2 genetic knockdown versus scrambled control medulloblastoma was completed. Results: ABL1/2 mRNA is highly expressed in human medulloblastoma and pharmacologic inhibition of ABL kinases resulted in cytotoxicity. Knockdown of ABL1/2 resulted in decreased adhesion of medulloblastoma cells to the extracellular matrix protein, vitronectin (P = .0013), and significantly decreased tumor burden in a mouse model of medulloblastoma LMD with improved overall survival (P = .0044). Furthermore, both pharmacologic inhibition of ABL1/2 and ABL1/2 knockdown resulted in decreased expression of c-MYC, identifying a putative signaling pathway, and genes/pathways related to oncogenesis and neurodevelopment were differentially expressed between ABL1/2 knockdown and control medulloblastoma cells. Conclusions: ABL1 and ABL2 have potential roles in medulloblastoma LMD upstream of c-MYC expression.

Ataxia-telangiectasia mutated ( Atm ) disruption sensitizes spatially-directed H3.3K27M/TP53 diffuse midline gliomas to radiation therapy.

Diffuse midline gliomas (DMGs) are lethal brain tumors characterized by p53-inactivating mutations and oncohistone H3.3K27M mutations that rewire the cellular response to genotoxic stress, which presents therapeutic opportunities. We used RCAS/tv-a retroviruses and Cre recombinase to inactivate p53 and induce K27M in the native H3f3a allele in a lineage- and spatially-directed manner, yielding primary mouse DMGs. Genetic or pharmacologic disruption of the DNA damage response kinase Ataxia-telangiectasia mutated (ATM) enhanced the efficacy of focal brain irradiation, extending mouse survival. This finding suggests that targeting ATM will enhance the efficacy of radiation therapy for p53-mutant DMG but not p53-wildtype DMG. We used spatial in situ transcriptomics and an allelic series of primary murine DMG models with different p53 mutations to identify transactivation-independent p53 activity as a key mediator of such radiosensitivity. These studies deeply profile a genetically faithful and versatile model of a lethal brain tumor to identify resistance mechanisms for a therapeutic strategy currently in clinical trials.

Long-term outcomes with reduced-dose whole-brain radiotherapy and a stereotactic radiosurgery boost for primary central nervous system lymphoma.

Background: Primary central nervous system lymphoma (PCNSL) is an aggressive diffuse large B-cell lymphoma. Treatment approaches are historically associated with neurotoxicity, particularly with high-dose whole-brain radiotherapy (WBRT). We hypothesized that reduced dose-WBRT (rd-WBRT) followed by a stereotactic radiosurgery (SRS) boost could provide durable disease control without significant adverse effects. Methods: We retrospectively reviewed PCNSL patients treated with rd-WBRT plus an SRS boost at Duke University between 2008 and 2021. Progression-free survival and overall survival (OS) were estimated using competing risk and Kaplan-Meier methods. Results: We identified 23 patients with pathologically confirmed PCNSL. Median age at diagnosis was 69 years (Q1Q3: 52-74) and median Karnofsky Performance Scale (KPS) was 80 (Q1Q3: 70-80). Median follow-up was 21 months. Median doses for rd-WBRT and SRS were 23.4 Gy (Q1Q3: 23.4-23.4) and 12 Gy (Q1Q3: 12-12.5), respectively. The cumulative incidence of intracranial progression at 2 years was 23% (95% CI: 8-42). Six patients (26%) developed distant radiographic progression while 2 patients (9%) developed both distant and local progression. Ten patients (44%) were alive without progression at last follow-up. By Kaplan-Meier estimate, the 2-year OS was 69% (95% CI: 46-84). There were no reported grade 3 + radiation-induced toxicities. Conclusions: The combination of rd-WBRT with an SRS boost appears well-tolerated with durable intracranial control. This approach may represent a treatment option for select patients, such as those with progressive or refractory disease. Further prospective studies are needed to validate these findings and determine whether this approach could be incorporated into consolidation strategies.

Pooled genetic screens to identify vulnerabilities in TERT-promoter-mutant glioblastoma.

Pooled genetic screens represent a powerful approach to identify vulnerabilities in cancer. Here we used pooled CRISPR/Cas9-based approaches to identify vulnerabilities associated with telomerase reverse transcriptase (TERT) promoter mutations (TPMs) found in >80% of glioblastomas. We first developed a platform to detect perturbations that cause long-term growth defects in a TPM-mutated glioblastoma cell line. However, we could not detect dependencies on either TERT itself or on an E-twenty six transcription (ETS) factor known to activate TPMs. To explore this finding, we cataloged TPM status for 441 cell lines and correlated this with genome-wide screening data. We found that TPM status was not associated with differential dependency on TERT, but that E-twenty six (ETS) transcription factors represent key dependencies in both TPM+ and TPM- lines. Further, we found that TPMs are associated with expression of gene programs regulated by a wide array of ETS-factors in both cell lines and primary glioblastoma tissues. This work contributes a unique TPM cell line reagent, establishes TPM status for many deeply-profiled cell lines, and catalogs TPM-associated vulnerabilities. The results highlight challenges in executing genetic screens to detect TPM-specific vulnerabilities, and suggest redundancy in the genetic network that regulates TPM function with therapeutic implications.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).

Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.

Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on multiparametric MRI (mpMRI) for diagnosis, treatment planning, and longitudinal treatment monitoring; yet automated, objective, and quantitative tools for non-invasive assessment of meningiomas on mpMRI are lacking. The BraTS meningioma 2023 challenge will provide a community standard and benchmark for state-of-the-art automated intracranial meningioma segmentation models based on the largest expert annotated multilabel meningioma mpMRI dataset to date. Challenge competitors will develop automated segmentation models to predict three distinct meningioma sub-regions on MRI including enhancing tumor, non-enhancing tumor core, and surrounding nonenhancing T2/FLAIR hyperintensity. Models will be evaluated on separate validation and held-out test datasets using standardized metrics utilized across the BraTS 2023 series of challenges including the Dice similarity coefficient and Hausdorff distance. The models developed during the course of this challenge will aid in incorporation of automated meningioma MRI segmentation into clinical practice, which will ultimately improve care of patients with meningioma.

Clinical Applications of Immunotherapy for Recurrent Glioblastoma in Adults.

Glioblastoma (GBM) is the most common malignant primary brain tumor in adults. Despite standard therapies, including resection and chemoradiation, recurrence is virtually inevitable. Current treatment for recurrent glioblastoma (rGBM) is rapidly evolving, and emerging therapies aimed at targeting primary GBM are often first tested in rGBM to demonstrate safety and feasibility, which, in recent years, has primarily been in the form of immunotherapy. The purpose of this review is to highlight progress in clinical trials of immunotherapy for rGBM, including immune checkpoint blockade, oncolytic virotherapy, chimeric antigen receptor (CAR) T-cell therapy, cancer vaccine and immunotoxins. Three independent reviewers covered literature, published between the years 2000 and 2022, in various online databases. In general, the efficacy of immunotherapy in rGBM remains uncertain, and is limited to subsets/small cohorts of patients, despite demonstrating feasibility in early-stage clinical trials. However, considerable progress has been made in understanding the mechanisms that may preclude rGBM patients from responding to immunotherapy, as well as in developing new approaches/combination strategies that may inspire optimism for the utility of immunotherapy in this devastating disease. Continued trials are necessary to further assess the best therapeutic avenues and ascertain which treatments might benefit each patient individually.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).

Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years after diagnosis. Gliomas are challenging to diagnose, hard to treat and inherently resistant to conventional therapy. Years of extensive research to improve diagnosis and treatment of gliomas have decreased mortality rates across the Global North, while chances of survival among individuals in low- and middle-income countries (LMICs) remain unchanged and are significantly worse in Sub-Saharan Africa (SSA) populations. Long-term survival with glioma is associated with the identification of appropriate pathological features on brain MRI and confirmation by histopathology. Since 2012, the Brain Tumor Segmentation (BraTS) Challenge have evaluated state-of-the-art machine learning methods to detect, characterize, and classify gliomas. However, it is unclear if the state-of-the-art methods can be widely implemented in SSA given the extensive use of lower-quality MRI technology, which produces poor image contrast and resolution and more importantly, the propensity for late presentation of disease at advanced stages as well as the unique characteristics of gliomas in SSA (i.e., suspected higher rates of gliomatosis cerebri). Thus, the BraTS-Africa Challenge provides a unique opportunity to include brain MRI glioma cases from SSA in global efforts through the BraTS Challenge to develop and evaluate computer-aided-diagnostic (CAD) methods for the detection and characterization of glioma in resource-limited settings, where the potential for CAD tools to transform healthcare are more likely.