Onco-functional outcome after resection for eloquent glioblastoma (OFO): A propensity-score matched analysis of an international, multicentre, cohort study.

BACKGROUND: The combined impact of complete resection (oncological goal) and no functional loss (functional goal) in glioblastoma subgroups is currently unknown. This study aimed to develop a novel onco-functional outcome (OFO) to merge these two goals into one outcome, resulting in four classes: complete without deficits (OFO1), incomplete without deficits (OFO2), complete with deficits (OFO3), or incomplete with deficits (OFO4). METHODS: Between 2010-2020, 858 patients with tumor resection for eloquent glioblastoma were included. We analyzed the impact of OFO class on postoperative surgical outcomes using Cox proportional-hazards models with hazard ratios (HR) or logistic regression with odds ratios (OR), followed by specific subgroup analyses. We developed a risk model to predict OFO class preoperatively using logistic regression. RESULTS: The OFO classification stratified the four OFO classes for overall survival (OS:19.0 versus 14.0 versus 12.0 versus 9.0 months), progression-free survival (PFS), and adjuvant therapy. OFO1 was associated with improved OS [HR= 0.67, (0.55-0.81); p < 0.001], and PFS [HR = 0.68, (0.57-0.81); p < 0.001] in the overall cohort and all clinical and molecular subgroups, except for MGMT-unmethylated tumors; and higher rate of adjuvant therapy [OR= 2.81, (1.71-4.84);p < 0.001]. In patients≥ 70 years, only OFO1 improved their survival outcomes. Safe surgery was especially important in patients with a preoperative KPS ≤ 80 to qualify for adjuvant treatment. Awake craniotomy more often led to OFO1 compared to asleep resection [OR = 1.93, (1.19-3.14); p = 0.008]. CONCLUSIONS: OFO1 was associated with improved OS, PFS, and receipt of adjuvant therapy in all glioblastoma patients with IDH-wildtype and MGMT-methylated tumors. Awake craniotomy was associated with achieving this optimal OFO status. Preventing deficits was more important than complete surgery.

Enhancing neuro-oncology care through equity-driven applications of artificial intelligence.

The disease course and clinical outcome for brain tumor patients depend not only on the molecular and histological features of the tumor but also on the patient's demographics and social determinants of health. While current investigations in neuro-oncology have broadly utilized artificial intelligence (AI) to enrich tumor diagnosis and more accurately predict treatment response, postoperative complications, and survival, equity-driven applications of AI have been limited. However, AI applications to advance health equity in the broader medical field have the potential to serve as practical blueprints to address known disparities in neuro-oncologic care. In this consensus review, we will describe current applications of AI in neuro-oncology, postulate viable AI solutions for the most pressing inequities in neuro-oncology based on broader literature, propose a framework for the effective integration of equity into AI-based neuro-oncology research, and close with the limitations of AI.

The oncological role of resection in newly diagnosed diffuse adult-type glioma defined by the WHO 2021 classification: a Review by the RANO resect group.

Glioma resection is associated with prolonged survival, but neuro-oncological trials have frequently refrained from quantifying the extent of resection. The Response Assessment in Neuro-Oncology (RANO) resect group is an international, multidisciplinary group that aims to standardise research practice by delineating the oncological role of surgery in diffuse adult-type gliomas as defined per WHO 2021 classification. Favourable survival effects of more extensive resection unfold over months to decades depending on the molecular tumour profile. In tumours with a more aggressive natural history, supramaximal resection might correlate with additional survival benefit. Weighing the expected survival benefits of resection as dictated by molecular tumour profiles against clinical factors, including the introduction of neurological deficits, we propose an algorithm to estimate the oncological effects of surgery for newly diagnosed gliomas. The algorithm serves to select patients who might benefit most from extensive resection and to emphasise the relevance of quantifying the extent of resection in clinical trials.

Leptomeningeal metastases from solid tumors: A SNO and ASCO consensus review on clinical management and future directions.

Leptomeningeal metastases are increasingly becoming recognized as a treatable, yet generally incurable, complication of advanced cancer. As modern cancer therapeutics have prolonged the lives of patients with metastatic cancer, specifically in patients with parenchymal brain metastases, treatment options and clinical research protocols for patients with leptomeningeal metastases from solid tumors have similarly evolved to improve survival within specific populations. Recent expansion in clinical investigation, early diagnosis, and drug development have given rise to new unanswered questions. These include leptomeningeal metastasis biology and preferred animal modeling, epidemiology in the modern cancer population, ensuring validation and accessibility of newer leptomeningeal metastasis diagnostics, best clinical practices with multi-modality treatment options, clinical trial design and standardization of response assessments, and avenues worthy of further research. An international group of multi-disciplinary experts in the research and management of leptomeningeal metastases, supported by the Society for Neuro-Oncology and American Society of Clinical Oncology, were assembled to reach a consensus opinion on these pressing topics and provide a roadmap for future directions. Our hope is that these recommendations will accelerate collaboration and progress in the field of leptomeningeal metastases and serve as a platform for further discussion and patient advocacy.

Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands: version 1.0.

PURPOSE: To provide practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor (SSTR) ligands. METHODS: This joint practice guideline/procedure standard was collaboratively developed by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the PET task force of the Response Assessment in Neurooncology Working Group (PET/RANO). RESULTS: Positron emission tomography (PET) using somatostatin receptor (SSTR) ligands can detect meningioma tissue with high sensitivity and specificity and may provide clinically relevant information beyond that obtained from structural magnetic resonance imaging (MRI) or computed tomography (CT) imaging alone. SSTR-directed PET imaging can be particularly useful for differential diagnosis, delineation of meningioma extent, detection of osseous involvement, and the differentiation between posttherapeutic scar tissue and tumour recurrence. Moreover, SSTR-peptide receptor radionuclide therapy (PRRT) is an emerging investigational treatment approach for meningioma. CONCLUSION: These practice guidelines will define procedure standards for the application of PET imaging in patients with meningiomas and related SSTR-targeted PRRTs in routine practice and clinical trials and will help to harmonize data acquisition and interpretation across centers, facilitate comparability of studies, and to collect larger databases. The current document provides additional information to the evidence-based recommendations from the PET/RANO Working Group regarding the utilization of PET imaging in meningiomas Galldiks (Neuro Oncol. 2017;19(12):1576-87). The information provided should be considered in the context of local conditions and regulations.

The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma MRI Dataset.

Supplemental material is available for this article.

A Neuroradiologist's Guide to Operationalizing the Response Assessment in Neuro-Oncology (RANO) Criteria Version 2.0 for Gliomas in Adults.

Radiographic assessment plays a crucial role in the management of patients with central nervous system (CNS) tumors, aiding in treatment planning and evaluation of therapeutic efficacy by quantifying response. Recently, an updated version of the Response Assessment in Neuro-Oncology (RANO) criteria (RANO 2.0) was developed to improve upon prior criteria and provide an updated, standardized framework for assessing treatment response in clinical trials for gliomas in adults. This article provides an overview of significant updates to the criteria including (1) the use of a unified set of criteria for high and low grade gliomas in adults; (2) the use of the post-radiotherapy MRI scan as the baseline for evaluation in newly diagnosed high-grade gliomas; (3) the option for the trial to mandate a confirmation scan to more reliably distinguish pseudoprogression from tumor progression; (4) the option of using volumetric tumor measurements; and (5) the removal of subjective non-enhancing tumor evaluations in predominantly enhancing gliomas (except for specific therapeutic modalities). Step-by-step pragmatic guidance is hereby provided for the neuroradiologist and imaging core lab involved in operationalization and technical execution of RANO 2.0 in clinical trials, including the display of representative cases and in-depth discussion of challenging scenarios.

Towards consistency in pediatric brain tumor measurements: Challenges, solutions, and the role of artificial intelligence-based segmentation.

MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tumor histologies; however, the visual delineation of tumor components using MRIs is not always straightforward, and complexities not currently addressed by these criteria can introduce inter- and intra-observer variability in manual assessments. Differentiation of non-enhancing tumors from peritumoral edema, mild enhancement from absence of enhancement, and various cystic components can be challenging; particularly given a lack of sufficient and uniform imaging protocols in clinical practice. Automated tumor segmentation with artificial intelligence (AI) may be able to provide more objective delineations, but rely on accurate and consistent training data created manually (ground truth). Herein, this paper reviews existing challenges and potential solutions to identifying and defining subregions of pediatric brain tumors (PBTs) that are not explicitly addressed by current guidelines. The goal is to assert the importance of defining and adopting criteria for addressing these challenges, as it will be critical to achieving standardized tumor measurements and reproducible response assessment in PBTs, ultimately leading to more precise outcome metrics and accurate comparisons among clinical studies.

Glioma.

Gliomas are primary brain tumours that are thought to develop from neural stem or progenitor cells that carry tumour-initiating genetic alterations. Based on microscopic appearance and molecular characteristics, they are classified according to the WHO classification of central nervous system (CNS) tumours and graded into CNS WHO grades 1-4 from a low to high grade of malignancy. Diffusely infiltrating gliomas in adults comprise three tumour types with distinct natural course of disease, response to treatment and outcome: isocitrate dehydrogenase (IDH)-mutant and 1p/19q-codeleted oligodendrogliomas with the best prognosis; IDH-mutant astrocytomas with intermediate outcome; and IDH-wild-type glioblastomas with poor prognosis. Pilocytic astrocytoma is the most common glioma in children and is characterized by circumscribed growth, frequent BRAF alterations and favourable prognosis. Diffuse gliomas in children are divided into clinically indolent low-grade tumours and high-grade tumours with aggressive behaviour, with histone 3 K27-altered diffuse midline glioma being the leading cause of glioma-related death in children. Ependymal tumours are subdivided into biologically and prognostically distinct types on the basis of histology, molecular biomarkers and location. Although surgery, radiotherapy and alkylating agent chemotherapy are the mainstay of glioma treatment, individually tailored strategies based on tumour-intrinsic dominant signalling pathways have improved outcome in subsets of patients.

SUPRAMAX-study: supramaximal resection versus maximal resection for glioblastoma patients: study protocol for an international multicentre prospective cohort study (ENCRAM 2201).

INTRODUCTION: A greater extent of resection of the contrast-enhancing (CE) tumour part has been associated with improved outcomes in glioblastoma. Recent results suggest that resection of the non-contrast-enhancing (NCE) part might yield even better survival outcomes (supramaximal resection, SMR). Therefore, this study evaluates the efficacy and safety of SMR with and without mapping techniques in high-grade glioma (HGG) patients in terms of survival, functional, neurological, cognitive and quality of life outcomes. Furthermore, it evaluates which patients benefit the most from SMR, and how they could be identified preoperatively. METHODS AND ANALYSIS: This study is an international, multicentre, prospective, two-arm cohort study of observational nature. Consecutive glioblastoma patients will be operated with SMR or maximal resection at a 1:1 ratio. Primary endpoints are (1) overall survival and (2) proportion of patients with National Institute of Health Stroke Scale deterioration at 6 weeks, 3 months and 6 months postoperatively. Secondary endpoints are (1) residual CE and NCE tumour volume on postoperative T1-contrast and FLAIR (Fluid-attenuated inversion recovery) MRI scans; (2) progression-free survival; (3) receipt of adjuvant therapy with chemotherapy and radiotherapy; and (4) quality of life at 6 weeks, 3 months and 6 months postoperatively. The total duration of the study is 5 years. Patient inclusion is 4 years, follow-up is 1 year. ETHICS AND DISSEMINATION: The study has been approved by the Medical Ethics Committee (METC Zuid-West Holland/Erasmus Medical Center; MEC-2020-0812). The results will be published in peer-reviewed academic journals and disseminated to patient organisations and media.

Liquid biopsy for improving diagnosis and monitoring of CNS lymphomas: A RANO review.

BACKGROUND: The utility of liquid biopsies is well documented in several extracranial and intracranial (brain/leptomeningeal metastases, gliomas) tumors. METHODS: The RANO (Response Assessment in Neuro-Oncology) group has set up a multidisciplinary Task Force to critically review the role of blood and cerebrospinal fluid (CSF)-liquid biopsy in CNS lymphomas, with a main focus on primary central nervous system lymphomas (PCNSL). RESULTS: Several clinical applications are suggested: diagnosis of PCNSL in critical settings (elderly or frail patients, deep locations, and steroid responsiveness), definition of minimal residual disease, early indication of tumor response or relapse following treatments, and prediction of outcome. CONCLUSIONS: Thus far, no clinically validated circulating biomarkers for managing both primary and secondary CNS lymphomas exist. There is need of standardization of biofluid collection, choice of analytes, and type of technique to perform the molecular analysis. The various assays should be evaluated through well-organized central testing within clinical trials.

Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study.

This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t-test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types (p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.

Challenges in the discovery of tumor-specific alternative splicing-derived cell-surface antigens in glioma.

Despite advancements in cancer immunotherapy, solid tumors remain formidable challenges. In glioma, profound inter- and intra-tumoral heterogeneity of antigen landscape hampers therapeutic development. Therefore, it is critical to consider alternative sources to expand the repertoire of targetable (neo-)antigens and improve therapeutic outcomes. Accumulating evidence suggests that tumor-specific alternative splicing (AS) could be an untapped reservoir of antigens. In this study, we investigated tumor-specific AS events in glioma, focusing on those predicted to generate major histocompatibility complex (MHC)-presentation-independent, cell-surface antigens that could be targeted by antibodies and chimeric antigen receptor-T cells. We systematically analyzed bulk RNA-sequencing datasets comparing 429 tumor samples (from The Cancer Genome Atlas) and 9166 normal tissue samples (from the Genotype-Tissue Expression project), and identified 13 AS events in 7 genes predicted to be expressed in more than 10% of the patients, including PTPRZ1 and BCAN, which were corroborated by an external RNA-sequencing dataset. Subsequently, we validated our predictions and elucidated the complexity of the isoforms using full-length transcript amplicon sequencing on patient-derived glioblastoma cells. However, analyses of the RNA-sequencing datasets of spatially mapped and longitudinally collected clinical tumor samples unveiled remarkable spatiotemporal heterogeneity of the candidate AS events. Furthermore, proteomics analysis did not reveal any peptide spectra matching the putative antigens. Our investigation illustrated the diverse characteristics of the tumor-specific AS events and the challenges of antigen exploration due to their notable spatiotemporal heterogeneity and elusive nature at the protein levels. Redirecting future efforts toward intracellular, MHC-presented antigens could offer a more viable avenue.

Adult neuro-oncology trials in the United States over 5 decades: Analysis of trials completion rate to guide the path forward.

Background: Clinical trials are important to close the gap between therapeutic unmet needs and scientific advances in neuro-oncology. This study analyzes the landscape of neuro-oncology trials to identify completion rates and guide strategies for the path forward. Methods: US-registered adult neuro-oncology clinical trials were extracted from www.clinicaltrials.gov (1966-2019), including funding source, trial type, scope, phase, and subjects' demographics. Completed trials defined as those that had completed participants' examinations or intervention administration for the purpose of the final collection of data for the primary outcome were dichotomized against those that failed to reach completion. Univariate and multivariate analyses were used to detect differences across factors comparing the last 2 decades (2000-2009, 2010-2019). Results: Our search yielded 4522 trials, of which 1257 are eligible for this study. In 25 US states, neuro-oncology trial availability is <0.85/100,000 population. Comparing the past 2 decades, trial completion rate decreased from 88% to 64% (P < .001) and National Institutes of Health funding decreased from 47% to 24% (P < .001). Inclusion of subjects >65-year-old and women increased, while inclusion of Hispanic subjects decreased (P < .001). The top 2 reasons for lack of completion included accrual and operational difficulties. A larger proportion of women, non-Hispanic subjects, and older adults were enrolled in completed trials than in those that failed completion. Conclusions: Our study is the first report on the neuro-oncology clinical trial landscape in the United States and supports the development of strategies to further improve access to these trials. Additionally, attention is needed to identify and modify other factors contributing to lack of completion.

Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective.

Treatment failure for the lethal brain tumor glioblastoma (GBM) is attributed to intratumoral heterogeneity and tumor evolution. We utilized 3D neuronavigation during surgical resection to acquire samples representing the whole tumor mapped by 3D spatial coordinates. Integrative tissue and single-cell analysis revealed sources of genomic, epigenomic, and microenvironmental intratumoral heterogeneity and their spatial patterning. By distinguishing tumor-wide molecular features from those with regional specificity, we inferred GBM evolutionary trajectories from neurodevelopmental lineage origins and initiating events such as chromothripsis to emergence of genetic subclones and spatially restricted activation of differential tumor and microenvironmental programs in the core, periphery, and contrast-enhancing regions. Our work depicts GBM evolution and heterogeneity from a 3D whole-tumor perspective, highlights potential therapeutic targets that might circumvent heterogeneity-related failures, and establishes an interactive platform enabling 360° visualization and analysis of 3D spatial patterns for user-selected genes, programs, and other features across whole GBM tumors.

PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group.

Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach.

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.