Decision making for health-related research outcomes that alter diagnosis: A model from paediatric brain tumours.

AIMS: The question of how to handle clinically actionable outcomes from retrospective research studies is poorly explored. In neuropathology, this problem is exacerbated by ongoing refinement in tumour classification. We sought to establish a disclosure threshold for potential revised diagnoses as determined by the neuro-oncology speciality. METHODS: As part of a previous research study, the diagnoses of 73 archival paediatric brain tumour samples were reclassified according to the WHO 2016 guidelines. To determine the disclosure threshold and clinical actionability of pathology-related findings, we conducted a result-evaluation approach within the ethical framework of BRAIN UK using a surrogate clinical multidisciplinary team (MDT) of neuro-oncology specialists. RESULTS: The MDT identified key determinants impacting decision-making, including anticipated changes to patient management, time elapsed since initial diagnosis, likelihood of the patient being alive and absence of additional samples since cohort inception. Ultimately, none of our research findings were considered clinically actionable, largely due to the cohort's historic archival and high-risk nature. From this experience, we developed a decision-making framework to determine if research findings indicating a change in diagnosis require reporting to the relevant clinical teams. CONCLUSIONS: Ethical issues relating to the use of archival tissue for research and the potential to identify actionable findings must be carefully considered. We have established a structured framework to assess the actionability of research data relating to patient diagnosis. While our specific findings are most applicable to the pathology of poor prognostic brain tumour groups in children, the model can be adapted to a range of disease settings, for example, other diseases where research is dependent on retrospective tissue cohorts, and research findings may have implications for patients and families, such as other tumour types, epilepsy-related pathology, genetic disorders and degenerative diseases.

Characterisation of paediatric brain tumours by their MRS metabolite profiles.

1H-magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single-voxel MRS (point-resolved single-voxel spectroscopy sequence, 1.5 T: echo time [TE] 23-37 ms/135-144 ms, repetition time [TR] 1500 ms; 3 T: TE 37-41 ms/135-144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann-Whitney U-tests and Kruskal-Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours.

Brain tumour genetic network signatures of survival.

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling to reveal a hierarchical network structure of tumour genetics spanning molecularly confirmed glioblastoma, IDH-wildtype; oligodendroglioma, IDH-mutant and 1p/19q codeleted; and astrocytoma, IDH-mutant. Our findings illuminate the complex dependence between features across the genetic landscape of brain tumours and show that generative network models reveal distinct signatures of survival with better prognostic fidelity than current gold standard diagnostic categories.

The coming of age of liquid biopsy in neuro-oncology.

The clinical role of liquid biopsy in oncology is growing significantly. In gliomas and other brain tumours, targeted sequencing of cell-free DNA (cfDNA) from CSF may help differential diagnosis when surgery is not recommended and be more representative of tumour heterogeneity than surgical specimens, unveiling targetable genetic alterations. Given the invasive nature of lumbar puncture to obtain CSF, the quantitative analysis of cfDNA in plasma is a lively option for patient follow-up. Confounding factors may be represented by cfDNA variations due to concomitant pathologies (inflammatory diseases, seizures) or clonal haematopoiesis. Pilot studies suggest that methylome analysis of cfDNA from plasma and temporary opening of the blood-brain barrier by ultrasound have the potential to overcome some of these limitations. Together with this, an increased understanding of mechanisms modulating the shedding of cfDNA by the tumour may help to decrypt the meaning of cfDNA kinetics in blood or CSF.

Quality of Life Factors and Measurement in Adult Meningioma Patients: A Systematic Review.

BACKGROUND: Meningiomas are common brain neoplasms that can significantly influence health-related quality of life (HRQOL), yet the factors influencing HRQOL in adult patients remain unclear. We aimed to bridge this knowledge gap by determining these key factors. METHODS: We conducted a systematic review, searching EMBASE, MEDLINE, CINAHL, Scopus and PsycINFO up to February 2024. We included original, peer-reviewed studies focusing on adult patients (>18 years) with current or past meningioma at any stage of treatment that measured HRQOL or its proxies in relation to patient-, tumour- and treatment-related factors. Two independent reviewers screened abstracts and full-texts, selecting studies with an acceptable risk of bias for data extraction and narrative synthesis. The protocol of this review was registered on PROSPERO (# CRD42023431097). RESULTS: Of N = 3002 studies identified, N = 31 studies were included. Key factors found to influence HRQOL in adult meningioma patients include surgery, radiotherapy, neurological function, functional status, comorbidities, sleep quality, psychological impairment, age and employment. Factors related to tumour characteristics yielded inconsistent findings. Heterogeneity and inconsistencies in HRQOL measurement across studies hindered definitive conclusions about the impact of factors on HRQOL. CONCLUSION: Our review elucidates the multifaceted influences on HRQOL in meningioma patients, with significant variability due to patient-, tumour- and treatment-related factors. We emphasize the need for standardized, disease-specific HRQOL assessments in meningioma patients. Collaborative efforts towards consistent, large-scale, prospective research are essential to comprehensively understand and improve HRQOL, thereby enhancing tailored care for this population.

Central nervous system tumours in neonates: what should the neonatologist know?

Central nervous system (CNS) tumours in neonates are relatively rare and present differently when compared with those occurring later in childhood in terms of aetiology, clinical features, location, histology and prognosis. The clinical presentation is extremely variable. Even if the most frequent clinical sign is a macrocephaly, there are many other non-specific symptoms associated. The prognosis is usually poor with overall survival of less than 30%. Surgery continues to be the primary treatment for neonatal CNS tumours, aiming for a gross total resection, directly correlated with prognosis and the overall outcome. The chemotherapy is the only adjuvant therapy whereas the radiotherapy is avoided under three years of age because of the severe sequelae. Hence the importance of molecular characterization of these neoplasms in order to improve the accuracy of the diagnosis and identify new therapeutic targets. The aim of this review is to describe the main characteristics of these tumours and the recent advances in their treatment in order to recognize these pathologies in the prenatal period and create a multidisciplinary team providing the best possible treatment while minimising the risk of long-term complications. Neonatologists play a key role in the early detection, diagnostic evaluation, management and supportive care of these neonates.  Conclusion: The aim of this review is to describe the main characteristics of these tumours and the recent advances in their treatment in order to ensure the essential knowledge that will help the neonatologist identify them and create a multidisciplinary team providing the best possible treatment while minimising the risk of long-term complications. What is Known: • Neonatal CNS tumours are relatively rare and their early identification is important to identify the best diagnostic-therapeutic management. • Surgery is the main treatment of neonatal CNS tumours. The extent of surgical resection directly correlates with prognosis and outcome. What is New: • Predisposing conditions such as Cancer Predisposition Syndromes must be considered. • Targeted drugs and other therapeutic strategies can be identified through molecular characterization.

The feasibility of half-dose contrast-enhanced scanning of brain tumours at 5.0 T: a preliminary study.

PURPOSE: This study investigated and compared the effects of Gd enhancement on brain tumours with a half-dose of contrast medium at 5.0 T and with a full dose at 3.0 T. METHODS: Twelve subjects diagnosed with brain tumours were included in this study and underwent MRI after contrast agent injection at 3.0 T (full dose) or 5.0 T (half dose) with a 3D T1-weighted gradient echo sequence. The postcontrast images were compared by two independent neuroradiologists in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective image quality score on a ten-point Likert scale. Quantitative indices and subjective quality ratings were compared with paired Student's t tests, and interreader agreement was assessed with the intraclass correlation coefficient (ICC). RESULTS: A total of 16 enhanced tumour lesions were detected. The SNR was significantly greater at 5.0 T than at 3.0 T in grey matter, white matter and enhanced lesions (p < 0.001). The CNR was also significantly greater at 5.0 T than at 3.0 T for grey matter/tumour lesions, white matter/tumour lesions, and grey matter/white matter (p < 0.001). Subjective evaluation revealed that the internal structure and outline of the tumour lesions were more clearly displayed with a half-dose at 5.0 T (Likert scale 8.1 ± 0.3 at 3.0 T, 8.9 ± 0.3 at 5.0 T, p < 0.001), and the effects of enhancement in the lesions were comparable to those with a full dose at 3.0 T (7.8 ± 0.3 at 3.0 T, 8.7 ± 0.4 at 5.0 T, p < 0.001). All subjective scores were good to excellent at both 5.0 T and 3.0 T. CONCLUSION: Both quantitative and subjective evaluation parameters suggested that half-dose enhanced scanning via 5.0 T MRI might be feasible for meeting clinical diagnostic requirements, as the image quality remains optimal. Enhanced scanning at 5.0 T with a half-dose of contrast agents might benefit patients with conditions that require less intravenous contrast agent, such as renal dysfunction.

Hyperostosis in meningioma: a retrospective exploration of histological correlates.

PURPOSE: Meningiomas are the most common type of primary brain tumour. Hyperostosis is commonly associated but remains incompletely understood. This study aimed to evaluate the relationship between meningioma-associated hyperostosis and other tumour variables. MATERIALS AND METHODS: We retrospectively analysed 245 patients with 263 cranial meningiomas (202 CNS WHO grade 1, 53 grade 2, and 8 grade 3) who underwent surgery over a three-year period. Meningiomas adjacent to the skull were included. Demographic, radiological, and tumour characteristics were analysed using standard statistical methods. RESULTS: Hyperostosis was evident in 99 (38%) of meningiomas. The most common subtypes were meningothelial, transitional, fibrous, atypical, and anaplastic. There were no statistically significant relationships between hyperostosis and bone invasion, and CNS WHO grade and histological subtype. Hyperostosis was more common in skull base meningiomas than in convexity meningiomas (p = 0.001). Ki-67 index was significantly related to CNS WHO grade but not histological subtype when grade was considered. Mean Ki-67 index was higher in meningiomas without hyperostosis (p = 0.03). There was no such relationship with bone invasion (p = 0.29). Univariate and multivariate analysis revealed that Ki-67 index was negatively correlated with hyperostosis (p = 0.03), while bone invasion (p < 0.001) and skull base location (p = 0.03) were positively correlated with hyperostosis. CONCLUSIONS: Hyperostosis did not appear to be related to CNS WHO grade or histological subtype. Proliferative activity appeared to be higher in meningiomas without hyperostosis and hyperostosis was associated with evidence of bone invasion and skull base location.

OV Modulators of the Paediatric Brain TIME: Current Status, Combination Strategies, Limitations and Future Directions.

Oncolytic viruses (OVs) are characterised by their preference for infecting and replicating in tumour cells either naturally or after genetic modification, resulting in oncolysis. Furthermore, OVs can elicit both local and systemic anticancer immune responses while specifically infecting and lysing tumour cells. These characteristics render them a promising therapeutic approach for paediatric brain tumours (PBTs). PBTs are frequently marked by a cold tumour immune microenvironment (TIME), which suppresses immunotherapies. Recent preclinical and clinical studies have demonstrated the capability of OVs to induce a proinflammatory immune response, thereby modifying the TIME. In-depth insights into the effect of OVs on different cell types in the TIME may therefore provide a compelling basis for using OVs in combination with other immunotherapy modalities. However, certain limitations persist in our understanding of oncolytic viruses' ability to regulate the TIME to enhance anti-tumour activity. These limitations primarily stem from the translational limitations of model systems, the difficulties associated with tracking reliable markers of efficacy throughout the course of treatment and the role of pre-existing viral immunity. In this review, we describe the different alterations observed in the TIME in PBTs due to OV treatment, combination therapies of OVs with different immunotherapies and the hurdles limiting the development of effective OV therapies while suggesting future directions based on existing evidence.

Meta-analysis of the impact of laser interstitial hyperthermia on wound healing complications in brain tumors.

High-grade gliomas (HGGs) may be amenable to the neurosurgical technique known as laser interstitial thermal therapy (LITT), which delivers thermal energy to interstitial brain injuries and wounds with pinpoint accuracy. The purpose of this extensive meta-analysis was to evaluate the effects of LITT on wound complications among patients who have brain tumours. Diverse conclusions emerge from a systematic review of pertinent studies, necessitating a comprehensive examination. The meta-analysis, performed utilizing the meta library provided by the R package meta, reveals an initial significant overall effect (RR: -2.1262, 95% CI [-2.7466, -1.5059], p < 0.0001) accompanied by considerable heterogeneity among studies (I2 = 61.13%). Following analyses that specifically examined the incidence of wounds, a complex correlation was found (RR: 0.0471, 95% CI [0.0264, 0.0842], p < 0.0001), indicating that LITT has a discernible but insignificant effect on the occurrence of wounds. Although the meta-analysis emphasizes a notable decrease in wound complications subsequent to LITT treatment, additional research is warranted due to constraints in standardized reporting, data accessibility, and small sample sizes. The results of this study underscore the need for exhaustive protocols to analyse wound complications in patients with brain tumours undergoing LITT.

Artificial intelligence- image learning and its applications in neurooncology: a review.

Image learning involves using artificial intelligence (AI) to analyse radiological images. Various machine and deeplearning- based techniques have been employed to process images and extract relevant features. These can later be used to detect tumours early and predict their survival based on their grading and classification. Radiomics is now also used to predict genetic mutations and differentiate between tumour progression and treatment-related side effects. These were once completely dependent on invasive procedures like biopsy and histopathology. The use and feasibility of these techniques are now widely being explored in neurooncology to devise more accurate management plans and limit morbidity and mortality. Hence, the future of oncology lies in the exploration of AI-based image learning techniques, which can be applied to formulate management plans based on less invasive diagnostic techniques, earlier detection of tumours, and prediction of prognosis based on radiomic features. In this review, we discuss some of these applications of image learning in current medical dynamics.

The prognostic power of [11C]methionine PET in IDH-wildtype diffuse gliomas with lower-grade histological features: venturing beyond WHO classification.

PURPOSE: IDH-wildtype (IDH-wt) diffuse gliomas with histological features of lower-grade gliomas (LGGs) are rare and heterogeneous primary brain tumours. [11C]Methionine (MET) positron emission tomography (PET) is commonly used to evaluate glial neoplasms at diagnosis. The present study aimed to assess the prognostic value of MET PET in newly diagnosed, treatment naïve IDH-wt gliomas with histological features of LGGs. METHODS: Patients with a histological diagnosis of IDH-wt LGG who underwent preoperative (< 100 days) MET PET/CT and surgery were retrospectively included. Qualitative and semi-quantitative analyses of MET PET images were performed. Progression-free survival (PFS) and overall survival (OS) were analysed by Kaplan-Meier curves. Cox proportional-hazards regression was used to test the association of imaging and clinical data to PFS and OS. RESULTS: We included 48 patients (M:F = 25:23; median age 55). 39 lesions were positive and 9 negative at MET PET. Positive MET PET was significantly associated with shorter median PFS (15.7 months vs. not reached, p = 0.0146) and OS time (32.6 months vs. not reached, p = 0.0253). Incomplete surgical resection and higher TBRmean values were independent predictors of shorter PFS on multivariate analysis (p < 0.001 for both). Higher tumour grade and incomplete surgical resection were independent predictors of OS at multivariate analysis (p = 0.027 and p = 0.01, respectively). CONCLUSION: MET PET is useful for the prognostic stratification of patients with IDH-wt glial neoplasms with histological LGGs features. Considering their huge biological heterogeneity, the combination of MET PET and molecular analyses may help to improve the prognostic accuracy in these diffuse gliomas subset and influence therapeutic choices accordingly.

Long term quality of life outcomes following surgical resection alone for benign paediatric intracranial tumours.

PURPOSE: Survivors of paediatric intracranial tumours are at increased risk of psychosocial, neuro-developmental, and functional impairment. This study aimed to evaluate long-term health-related quality-of-life (HRQOL) outcomes in patients with benign paediatric brain tumours treated curatively with surgical resection alone. METHODOLOGY: This was a cross-sectional study of patients with benign paediatric intracranial tumours managed with surgery alone between 2000 and 2015. Eligible patients with a minimum of 5-years follow-up after surgery were identified. Validated health-related quality of life (HRQOL) questionnaires were administered: SF-36, QLQ-BN20, QLQ-C30 and PedsQL™. RESULTS: Twenty-three patients participated (median age at surgery 13 years; range 1-18; 12 male). The most common diagnosis was pilocytic astrocytoma (n = 15). Median time from surgery to participation was 11 years(range 6-19). Fourteen patients achieved A-level qualifications and two obtained an undergraduate degree. Twelve patients were employed, eight were studying and three were unemployed or volunteering. HRQOL outcomes demonstrated significant limitation from social functioning (p = 0.03) and cognitive functioning (p = 0.023) compared to the general population. Patients also experienced higher rates of loss of appetite (p = 0.009) and nausea and vomiting (p = 0.031). Ten patients were under transitional teenager and young-adult (TYA) clinic follow-up. TYA patients achieved higher levels of education (p = 0.014), were more likely to hold a driver's license (p = 0.041) compared to patients not followed-up through these services. CONCLUSIONS: Childhood brain-tumour survivors have a greater risk of developing psychological, neuro-cognitive and physical impairment. Early comprehensive assessment, specialist healthcare and TYA services are vital to support these patients.

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to multiparametric MRI to obtain clinical referral suggestion for IMLLs, and to validate it in the setting of nontraumatic emergency neuroradiology. METHODS: A DL system was developed in 747 patients with IMLLs ranging 30 diseases who underwent pre- and post-contrast T1-weighted (T1CE), FLAIR, and diffusion-weighted imaging (DWI). A DL system that segments IMLLs, classifies tumourous conditions, and suggests clinical referral among surgery, systematic work-up, medical treatment, and conservative treatment, was developed. The system was validated in an independent cohort of 130 emergency patients, and performance in referral suggestion and tumour discrimination was compared with that of radiologists using receiver operating characteristics curve, precision-recall curve analysis, and confusion matrices. Multiparametric interpretable visualisation of high-relevance regions from layer-wise relevance propagation overlaid on contrast-enhanced T1WI and DWI was analysed. RESULTS: The DL system provided correct referral suggestions in 94 of 130 patients (72.3%) and performed comparably to radiologists (accuracy 72.6%, McNemar test; p = .942). For distinguishing tumours from non-tumourous conditions, the DL system (AUC, 0.90 and AUPRC, 0.94) performed similarly to human readers (AUC, 0.81~0.92, and AUPRC, 0.88~0.95). Solid portions of tumours showed a high overlap of relevance, but non-tumours did not (Dice coefficient 0.77 vs. 0.33, p < .001), demonstrating the DL's decision. CONCLUSIONS: Our DL system could appropriately triage patients using multiparametric MRI and provide interpretability through multiparametric heatmaps, and may thereby aid neuroradiologic diagnoses in emergency settings. CLINICAL RELEVANCE STATEMENT: Our AI triages patients with raw MRI images to clinical referral pathways in brain intra-axial mass-like lesions. We demonstrate that the decision is based on the relative relevance between contrast-enhanced T1-weighted and diffusion-weighted images, providing explainability across multiparametric MRI data. KEY POINTS: • A deep learning (DL) system using multiparametric MRI suggested clinical referral to patients with intra-axial mass-like lesions (IMLLs) similar to radiologists (accuracy 72.3% vs. 72.6%). • In the differentiation of tumourous and non-tumourous conditions, the DL system (AUC, 0.90) performed similar with radiologists (AUC, 0.81-0.92). • The DL's decision basis for differentiating tumours from non-tumours can be quantified using multiparametric heatmaps obtained via the layer-wise relevance propagation method.

Central nervous system tumours among users of vaginal oestradiol tablets: A nationwide population-based study.

BACKGROUND AND PURPOSE: It is currently unknown whether vaginal oestradiol is associated with development of meningioma and glioma. The aim of this study was to examine associations between cumulative use and treatment intensity of vaginally administered oestradiol tablets and incidence of meningioma and glioma in a nationwide, population-based study. METHODS: We conducted a nested case-control study within a nationwide cohort of Danish women followed from 2000 to 2018. The cohort consisted of 590,676 women aged 50-60 years at study start, without prior cancer diagnosis or use of systemic hormone therapy. Information on cumulative dose, duration, and intensity of vaginal oestradiol tablet use was assessed from filled prescriptions. Conditional logistic regression provided adjusted hazard ratios (HRs) for the association between vaginal oestradiol use and diagnosis of meningioma or glioma. RESULTS: We identified 1108 women with meningioma and 835 with glioma. Of these, 19.8% and 14.0% used vaginal oestradiol tablets, respectively. The HRs in those with ever-use of vaginal oestradiol tablets was 1.14 (95% confidence interval [CI] 0.97-1.34) for meningioma and 0.90 (95% CI 0.73-1.11) for glioma. The corresponding HRs for new users exclusively were 1.18 (95% CI 0.99-1.40) for meningioma and 0.89 (95% CI 0.71-1.13) for glioma. Intensity of vaginal oestradiol tablet use according to duration and user status yielded slightly elevated HRs for meningioma without an apparent dose-response pattern, while the HRs for glioma were generally below unity. Among new users, the HR with high intensity of current or recent vaginal oestradiol tablet use for 2+ years was 1.66 (95% CI 1.09-2.55) for meningioma and 0.77 (95% CI 0.41-1.44) for glioma. CONCLUSION: Use of vaginal oestradiol tablets was associated with a slightly increased incidence of meningioma but not of glioma. Owing to the observational nature of the study, residual bias cannot be ruled out.

Cancer Registration, Molecular Marker Status, and Adherence to the WHO 2016 Classification of Pathology Reports for Glioma Diagnosed during 2017-2019 in Belgium.

INTRODUCTION: The objective of this study was to cross-check and, if necessary, adjust registered ICD-O-3 topography and morphology codes with the findings in pathology reports available at the Belgian Cancer Registry (BCR) for glioma patients. Additionally, integration of molecular markers in the pathological diagnosis and concordance with WHO 2016 classification is investigated. METHODS: Since information regarding molecular tests and corresponding conclusions are not available as structured data at population level, a manual screening of all pseudonymized pathology reports available at the BCR for registered glioma patients (2017-2019) was conducted. ICD-O-3 morphology and topography codes from the BCR database (based on information as provided by hospital oncological care programmes and pathology laboratories), were, at tumour level, cross-checked with the data from the pathology reports and, if needed, specified or corrected. Relevant molecular markers (IDH1/2, 1p19q codeletion, promoter region of the MGMT gene [MGMTp]) were manually extracted from the pathology reports. RESULTS: In 95.3% of gliomas, the ICD-O-3 morphology code was correct. Non-specific topography codes were specified in 9.3%, while 3.3% of specific codes were corrected. The IDH status was known in 75.2% of astrocytic tumours. The rate of correct integrated diagnoses varied from 47.6% to 56.4% among different gliomas. MGMTp methylation status was available in 32.2% of glioblastomas. CONCLUSION: Both the integration of molecular markers in the conclusion of the pathology reports and the delivery of those reports to the BCR can be improved. The availability of distinct ICD-O-3 codes for each molecularly defined tumour entity within the WHO classification would increase the consistency of cancer registration, facilitate population level research and international benchmarking.

Regional healthy brain activity, glioma occurrence and symptomatology.

It is unclear why exactly gliomas show preferential occurrence in certain brain areas. Increased spiking activity around gliomas leads to faster tumour growth in animal models, while higher non-invasively measured brain activity is related to shorter survival in patients. However, it is unknown how regional intrinsic brain activity, as measured in healthy controls, relates to glioma occurrence. We first investigated whether gliomas occur more frequently in regions with intrinsically higher brain activity. Second, we explored whether intrinsic cortical activity at individual patients' tumour locations relates to tumour and patient characteristics. Across three cross-sectional cohorts, 413 patients were included. Individual tumour masks were created. Intrinsic regional brain activity was assessed through resting-state magnetoencephalography acquired in healthy controls and source-localized to 210 cortical brain regions. Brain activity was operationalized as: (i) broadband power; and (ii) offset of the aperiodic component of the power spectrum, which both reflect neuronal spiking of the underlying neuronal population. We additionally assessed (iii) the slope of the aperiodic component of the power spectrum, which is thought to reflect the neuronal excitation/inhibition ratio. First, correlation coefficients were calculated between group-level regional glioma occurrence, as obtained by concatenating tumour masks across patients, and group-averaged regional intrinsic brain activity. Second, intrinsic brain activity at specific tumour locations was calculated by overlaying patients' individual tumour masks with regional intrinsic brain activity of the controls and was associated with tumour and patient characteristics. As proposed, glioma preferentially occurred in brain regions characterized by higher intrinsic brain activity in controls as reflected by higher offset. Second, intrinsic brain activity at patients' individual tumour locations differed according to glioma subtype and performance status: the most malignant isocitrate dehydrogenase-wild-type glioblastoma patients had the lowest excitation/inhibition ratio at their individual tumour locations as compared to isocitrate dehydrogenase-mutant, 1p/19q-codeleted glioma patients, while a lower excitation/inhibition ratio related to poorer Karnofsky Performance Status, particularly in codeleted glioma patients. In conclusion, gliomas more frequently occur in cortical brain regions with intrinsically higher activity levels, suggesting that more active regions are more vulnerable to glioma development. Moreover, indices of healthy, intrinsic excitation/inhibition ratio at patients' individual tumour locations may capture both tumour biology and patients' performance status. These findings contribute to our understanding of the complex and bidirectional relationship between normal brain functioning and glioma growth, which is at the core of the relatively new field of 'cancer neuroscience'.

Cognitive and affective theory of mind double dissociation after parietal and temporal lobe tumours.

Extensive neuroimaging literature suggests that understanding others' thoughts and emotions engages a wide network encompassing parietal, temporal and medial frontal brain areas. However, the causal role played by these regions in social inferential abilities is still unclear. Moreover very little is known about theory of mind deficits in brain tumours and whether potential anatomical substrates are comparable to those identified in functional MRI literature. This study evaluated the performance of 105 tumour patients, before and immediately after brain surgery, on a cartoon-based non-verbal task evaluating cognitive (intention attribution) and affective (emotion attribution) theory of mind, as well as a non-social control condition (causal inference). Across multiple analyses, we found converging evidence of a double dissociation between patients with right superior parietal damage, selectively impaired in intention attribution, and those with right anteromedial temporal lesion, exhibiting deficits only in emotion attribution. Instead, patients with damage to the frontal cortex were impaired in all kinds of inferential processes, including those from the non-social control conditions. Overall, our data provide novel reliable causal evidence of segregation between different aspects of the theory of mind network from both the cognitive and also the anatomical point of view.

Speaking up for the lost voices: representation and inclusion of people with communication impairment in brain tumour research.

Brain tumours and their associated treatments can lead to progressive impairments of communication, adversely affecting quality-of-life. This commentary explores our concerns that people with speech, language, and communication needs face barriers to representation and inclusion in brain tumour research; we then offer possible solutions to support their participation. Our main concerns are that there is currently poor recognition of the nature of communication difficulties following brain tumours, limited focus on the psychosocial impact, and lack of transparency on why people with speech, language, and communication needs were excluded from research or how they were supported to take part. We propose solutions focusing on working towards more accurate reporting of symptoms and the impact of impairment, using innovative qualitative methods to collect data on the lived experiences of speech, language, and communication needs, and empowering speech and language therapists to become part of research teams as experts and advocates for this population. These solutions would support the accurate representation and inclusion of people with communication needs after brain tumour in research, allowing healthcare professionals to learn more about their priorities and needs.

Delay in the diagnosis of paediatric brain tumours: a systematic review.

PURPOSE: A delay in obtaining a diagnosis has been associated with inferior outcomes across several cancer types, including paediatric brain tumours. However, no clear evidence exists in this population. We aimed to quantify the reported pre-diagnostic symptom interval (PSI) as the time from onset of first symptoms to diagnosis in the literature, in addition to evaluating the relationship between delay and outcomes, including survival. METHODS: A systematic review of the literature was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, Wiley Online Library, Web of Science and EMBASE databases were searched. We considered all sources published between 1st January 2010 and 5th November 2022. Children and adolescents aged under 21 years, with new symptomatic primary brain tumour diagnoses, were included. RESULTS: Of 3123 studies identified, 11 were included for analysis. Owing to study heterogeneity, a quantitative meta-analysis was not feasible; however, a narrative synthesis was performed. The median reported PSI varied widely, ranging between 28 and 760.8 days. We failed to identify a significant association between prolonged PSI and inferior overall survival. Few factors were consistently associated with prolonged PSI, amongst them only tumour grade and patient age. CONCLUSION: Delayed diagnosis of paediatric brain tumours was not associated with inferior survival within this review. This 'waiting time' paradox appears to result from several confounding factors including tumour biology, patient population and key systematic factors that were inconsistently reported. Diagnostic interval clearly presents a complex variable, reflected further by disparity in the reporting of delay within the literature. Ultimately diagnostic interval is unlikely to provide a meaningful representation for all tumour types and should not detract from sharp clinical acumen and prompt diagnosis.