Unravelling the mosaic: Epigenetic diversity in glioblastoma.

Glioblastoma is the most common primary malignant brain tumour. Despite decades of intensive research in the disease, its prognosis remains poor, with an average survival of only 14 months after diagnosis. The remarkable level of intra- and interpatient heterogeneity is certainly contributing to the lack of progress in tackling this tumour. Epigenetic dysregulation plays an important role in glioblastoma biology and significantly contributes to intratumour heterogeneity. However, it is becoming increasingly clear that it also contributes to intertumour heterogeneity, which historically had mainly been linked to diverse genetic events occurring in different patients. In this review, we explore how DNA methylation, chromatin remodelling, microRNA (miRNA) dysregulation, and long noncoding RNA (lncRNA) alterations contribute to intertumour heterogeneity in glioblastoma, including its implications for advanced tumour stratification, which is the essential first step for developing more effective patient-specific therapeutic approaches.

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.

NTRK-fused central nervous system tumours: clinicopathological and genetic insights and response to TRK inhibitors.

Background Neurotrophic tropomyosin receptor kinase (NTRK) gene fusions are found in 1% of gliomas across children and adults. TRK inhibitors are promising therapeutic agents for NTRK-fused gliomas because they are tissue agnostic and cross the blood-brain barrier (BBB). Methods We investigated twelve NGS-verified NTRK-fused gliomas from a single institute, Seoul National University Hospital. Results The patient cohort included six children (aged 1-15 years) and six adults (aged 27-72 years). NTRK2 fusions were found in ten cerebral diffuse low-grade and high-grade gliomas (DLGGs and DHGGs, respectively), and NTRK1 fusions were found in one cerebral desmoplastic infantile ganglioglioma and one spinal DHGG. In this series, the fusion partners of NTRK2 were HOOK3, KIF5A, GKAP1, LHFPL3, SLMAP, ZBTB43, SPECC1L, FKBP15, KANK1, and BCR, while the NTRK1 fusion partners were TPR and TPM3. DLGGs tended to harbour only an NTRK fusion, while DHGGs exhibited further genetic alterations, such as TERT promoter/TP53/PTEN mutation, CDKN2A/2B homozygous deletion, PDGFRA/KIT/MDM4/AKT3 amplification, or multiple chromosomal copy number aberrations. Four patients received adjuvant TRK inhibitor therapy (larotrectinib, repotrectinib, or entrectinib), among which three also received chemotherapy (n = 2) or proton therapy (n = 1). The treatment outcomes for patients receiving TRK inhibitors varied: one child who received larotrectinib for residual DLGG maintained stable disease. In contrast, another child with DHGG in the spinal cord experienced multiple instances of tumour recurrence. Despite treatment with larotrectinib, ultimately, the child died as a result of tumour progression. An adult patient with glioblastoma (GBM) treated with entrectinib also experienced tumour progression and eventually died. However, there was a successful outcome for a paediatric patient with DHGG who, after a second gross total tumour removal followed by repotrectinib treatment, showed no evidence of disease. This patient had previously experienced relapse after the initial surgery and underwent autologous peripheral blood stem cell therapy with carboplatin/thiotepa and proton therapy. Conclusions Our study clarifies the distinct differences in the pathology and TRK inhibitor response between LGG and HGG with NTRK fusions.

[Translation into French and republication of: "Management of venous thromboembolic disease in patients with malignant brain tumours"]. / Traduction et republication de : « Prise en charge de la maladie thromboembolique veineuse chez les patients atteints de tumeurs cérébrales malignes ¼.

This article addresses the management of venous thromboembolism in patients with malignant brain tumours, including both primary and secondary (metastatic) tumours. The available data on patients on venous thromboembolism recurrence and bleeding risks in patients with brain tumours is limited, since these patients have been excluded from most randomised, interventional, head-to-head, clinical trials comparing low molecular weight heparins to vitamin K antagonists or to direct oral factor Xa inhibitors. More information is available from retrospective observational studies, which however were generally small, and carried a high risk of confounding. Their findings suggest that direct factor Xa inhibitor use is associated with lower rates of intracranial haemorrhage compared with low molecular weight heparins. Overall, the safety profile of direct oral factor Xa inhibitors when used to prevent venous thromboembolism recurrence in patients with either primary or secondary brain tumours appears to be favourable. The available data are in favour of using an anticoagulant at a full therapeutic dose in patients with primary and secondary brain tumours experiencing a venous thromboembolism, although they are not yet sufficiently robust to permit recommending a direct factor Xa inhibitor over low-molecular weight heparin.

Role of artificial intelligence in brain tumour imaging.

Artificial intelligence (AI) is a rapidly evolving field with many neuro-oncology applications. In this review, we discuss how AI can assist in brain tumour imaging, focusing on machine learning (ML) and deep learning (DL) techniques. We describe how AI can help in lesion detection, differential diagnosis, anatomic segmentation, molecular marker identification, prognostication, and pseudo-progression evaluation. We also cover AI applications in non-glioma brain tumours, such as brain metastasis, posterior fossa, and pituitary tumours. We highlight the challenges and limitations of AI implementation in radiology, such as data quality, standardization, and integration. Based on the findings in the aforementioned areas, we conclude that AI can potentially improve the diagnosis and treatment of brain tumours and provide a path towards personalized medicine and better patient outcomes.

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.

Systematic Review Between Resting-State fMRI and Task fMRI in Planning for Brain Tumour Surgery.

As an alternative to task-based functional magnetic resonance imaging (T-fMRI), resting-state functional magnetic resonance imaging (Rs-fMRI) is suggested for preoperative mapping of patients with brain tumours, with an emphasis on treatment guidance and neurodegeneration prediction. A systematic review was conducted of 18 recent studies involving 1035 patients with brain tumours and Rs-fMRI protocols. This was accomplished by searching the electronic databases PubMed, Scopus, and Web of Science. For clinical benefit, we compared Rs-fMRI to standard T-fMRI and intraoperative direct cortical stimulation (DCS). The results of Rs-fMRI and T-fMRI were compared and their correlation with intraoperative DCS results was examined through a systematic review. Our exhaustive investigation demonstrated that Rs-fMRI is a dependable and sensitive preoperative mapping technique that detects neural networks in the brain with precision and identifies crucial functional regions in agreement with intraoperative DCS. Rs-fMRI comes in handy, especially in situations where T-fMRI proves to be difficult because of patient-specific factors. Additionally, our exhaustive investigation demonstrated that Rs-fMRI is a valuable tool in the preoperative screening and evaluation of brain tumours. Furthermore, its capability to assess brain function, forecast surgical results, and enhance decision-making may render it applicable in the clinical management of brain tumours.

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.

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.

Brain tumor segmentation using neuro-technology enabled intelligence-cascaded U-Net model.

According to experts in neurology, brain tumours pose a serious risk to human health. The clinical identification and treatment of brain tumours rely heavily on accurate segmentation. The varied sizes, forms, and locations of brain tumours make accurate automated segmentation a formidable obstacle in the field of neuroscience. U-Net, with its computational intelligence and concise design, has lately been the go-to model for fixing medical picture segmentation issues. Problems with restricted local receptive fields, lost spatial information, and inadequate contextual information are still plaguing artificial intelligence. A convolutional neural network (CNN) and a Mel-spectrogram are the basis of this cough recognition technique. First, we combine the voice in a variety of intricate settings and improve the audio data. After that, we preprocess the data to make sure its length is consistent and create a Mel-spectrogram out of it. A novel model for brain tumor segmentation (BTS), Intelligence Cascade U-Net (ICU-Net), is proposed to address these issues. It is built on dynamic convolution and uses a non-local attention mechanism. In order to reconstruct more detailed spatial information on brain tumours, the principal design is a two-stage cascade of 3DU-Net. The paper's objective is to identify the best learnable parameters that will maximize the likelihood of the data. After the network's ability to gather long-distance dependencies for AI, Expectation-Maximization is applied to the cascade network's lateral connections, enabling it to leverage contextual data more effectively. Lastly, to enhance the network's ability to capture local characteristics, dynamic convolutions with local adaptive capabilities are used in place of the cascade network's standard convolutions. We compared our results to those of other typical methods and ran extensive testing utilising the publicly available BraTS 2019/2020 datasets. The suggested method performs well on tasks involving BTS, according to the experimental data. The Dice scores for tumor core (TC), complete tumor, and enhanced tumor segmentation BraTS 2019/2020 validation sets are 0.897/0.903, 0.826/0.828, and 0.781/0.786, respectively, indicating high performance in BTS.

Rapid Vision Loss Due to Multifocal Glioma: A Diagnostic Challenge.

INTRODUCTION: This is a unique case report in medical literature for its detailing of diagnostics of an uncommon presentation of a rapid unexplained bilateral vision loss of a 73-year-old male diabetic patient. This report highlights the crucial role of advanced molecular diagnostics in difficult neurological cases and also elucidates the difficulties involved in diagnosing optic nerve glioblastoma, an exceptionally rare and aggressive tumour. MAIN CONCERNS AND CLINICAL FINDINGS OF THE PATIENT: Slow and progressive loss of vision over 2 months, ultimately developing almost complete visual impairment in both eyes and a defect of right eye field of vision conclusively highlighted that the likely etiology was neuro-ophthalmic. Initially, the conditions were suspected to be an extended spectrum of diabetic eye disease complications but further deterioration was a hint towards something more substantive. PRIMARY DIAGNOSES, INTERVENTIONS AND OUTCOMES: This entailed in-depth diagnosis processes that included an MRI and the analysis of cerebrospinal fluid. The important discovery was through stereotactic biopsies of the optic nerve revealing a high-grade glial neoplasm. Next generation sequencing confirmed the pathology as IDH-wildtype glioblastoma. Despite management, his vision continued to deteriorate. Hence, an aggressive clinical course was followed. CONCLUSION: This case highlights the important learning need in considering glioblastoma of the optic chiasm as part of the differential diagnosis of rapid vision loss, which may present as multifocal brain lesions, especially in cases of rapid loss of vision where initial workup is negative. Quite a useful lesson that can be drawn from this case relates to the diagnostic process with advanced molecular profiling, more attention given to clinical suspicion and cutting-edge diagnostic tools applied in atypical presentation of neurological conditions.

A Promising Breakthrough: The Potential of VORASIDENIB in the Treatment of Low-grade Glioma.

INTRODUCTION: Gliomas are common malignant brain tumors characterized by diffuse brain infiltration. World Health Organization grade II and grade III diffuse gliomas are considered lower-grade gliomas (LGGs) and have isocitrate dehydrogenase (IDH) mutations. LGGs are challenging due to their infiltrative nature, making them capable of progressing into higher-grade malignancies. Vorasidenib is a novel therapeutic agent targeting mutant IDH1/2, sparking interest in the field. MECHANISM OF ACTION: Vorasidenib inhibits mutant IDH1/2 through a unique mechanism, reducing the production of the oncometabolite 2-hydroxyglutarate (2-HG). This alteration affects key enzymes and DNA methylation, impacting tumor growth and invasion. Preclinical Evidence: Preclinical studies show vorasidenib's efficacy in inhibiting mutant IDH1/2 and 2-HG production in glioma models. It suppresses tumor growth, making it a potential treatment option. CLINICAL EVIDENCE: Early clinical trials demonstrate vorasidenib's clinical activity in non-enhancing gliomas. It reduces 2-hydroxyglutarate levels and tumor cell proliferation, with an objective response rate and prolonged progression-free survival. The drug's safety profile is favorable. Challenges and Future Directions: Challenges include identifying predictive biomarkers and optimizing sequencing or combinations with existing therapies. Further research is needed to establish long-term effectiveness, evaluate side effects, and explore combinations with immunotherapy. CONCLUSION: orasidenib significantly advances LGG treatment, targeting a prevalent mutation and slowing tumor growth. Promising preclinical and clinical evidence and manageable side effects suggest its potential impact on LGG management. However, more research, including large trials, is needed to confirm its efficacy and role in treatment.

Potential of PSMA-targeting radioligand therapy for malignant primary and secondary brain tumours using super-selective intra-arterial administration: a single centre, open label, non-randomised prospective imaging study.

BACKGROUND: The aim of this study was to provide quantitative evidence for the potential of PSMA-targeting radioligand therapy (RLT) as treatment approach for malignant brain tumours, and to explore whether tumour uptake could be enhanced by super-selective intra-arterial (ssIA)-administration. METHODS: Ten patients (n = 5 high-grade glioma, n = 5 brain metastasis) received 1.5 MBq/kg [68Ga]Ga-PSMA-11 intravenously and, within 7 days, intra-arterially (i.e., selectively in tumour-feeding arteries), followed twice by PET-MRI at 90, 165 and 240 min post-injection. Patient safety was monitored for each procedure. Standardised uptake values (SUVs) were obtained for tumour, healthy-brain, salivary glands and liver. Tumour-to-salivary-gland (T/SG) and tumour-to-liver (T/L) uptake-ratios were calculated. FINDINGS: No adverse events requiring study termination occurred. All patients showed uptake of [68Ga]Ga-PSMA-11 at the tumour site. Uptake was a median 15-fold higher following ssIA-administration (SUVmax median: 142.8, IQR: 102.8-245.9) compared to IV-administration (10.5, IQR:7.5-13.0). According to the bootstrap analysis, mean SUVmax after ssIA (168.8, 95% CI: 110.6-227.0) was well beyond the 95% confidence-interval of IV administration (10.5, 95% CI: 8.4-12.7). Uptake in healthy-brain was negligible, independent of administration route (SUVmean <0.1-0.1). Off-target uptake was comparable, resulting in more favourable T/SG- and T/L-ratios of 8.4 (IQR: 4.4-11.5) and 26.5 (IQR: 14.0-46.4) following ssIA, versus 0.5 (IQR: 0.4-0.7) and 1.8 (IQR: 1.0-2.7) for IV-administration. INTERPRETATION: ssIA-administration is safe and leads to a median fifteen-fold higher radioligand uptake at the tumour site, therewith qualifying more patients for treatment and enhancing the potential of therapy. These results open new avenues for the development of effective RLT-based treatment strategies for patients with brain tumours. FUNDING: Semmy Foundation.

Awake craniotomies in South America: Advancements, challenges, and future prospects.

BACKGROUND: Awake craniotomy has emerged as an advanced surgical technique, characterized by keeping the patient awake during brain surgery. In South America, awake craniotomies have grained traction in neurosurgical practices across various medical centres and hospitals, with notable practitioners contributing to its growth and refinement in the region. PURPOSE: This study aims to explore the integration and impact of awake craniotomies in South American neurosurgical practices. The focus is on understanding the benefits, challenges, and potential transformative effects of the procedure in the region. RESEARCH DESIGN: A comprehensive narrative review and analysis through a thorough examination of the existing literature. RESULTS: The findings indicate that awake craniotomies in South America offer substantial benefits, including cost savings thorugh reduced hospitalization time, quicker recovery and decreased morbidity. Enhanced safety, effective pain management and reduced anaesthesia also contribute to this. CONCLUSION: Whilst the adaptation of awake craniotomies in South America holds great promise in transforming neurosurgical care in the region, significant challenges hinder its widespread adoption. Inadequate infrastructure, limited access to equipment, financial instability, and shortages in trained healthcare providers represent challenges that need to be addressed.

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.

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.

Empowering brain cancer diagnosis: harnessing artificial intelligence for advanced imaging insights.

Artificial intelligence (AI) is increasingly being used in the medical field, specifically for brain cancer imaging. In this review, we explore how AI-powered medical imaging can impact the diagnosis, prognosis, and treatment of brain cancer. We discuss various AI techniques, including deep learning and causality learning, and their relevance. Additionally, we examine current applications that provide practical solutions for detecting, classifying, segmenting, and registering brain tumors. Although challenges such as data quality, availability, interpretability, transparency, and ethics persist, we emphasise the enormous potential of intelligent applications in standardising procedures and enhancing personalised treatment, leading to improved patient outcomes. Innovative AI solutions have the power to revolutionise neuro-oncology by enhancing the quality of routine clinical practice.

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.

Possibilities of Using Multi-b-value Diffusion Magnetic Resonance Imaging for Classification of Brain Lesions.

In contrast to conventional diffusion magnetic resonance imaging (MRI), multi-b-value diffusion MRI methods are able to separate the signal from free water, pseudo-diffusion, and non-Gaussian components of water molecule diffusion. These approaches can then be utilised in so-called intravoxel incoherent motion imaging and diffusion kurtosis imaging. Various parameters provided by these methods can describe additional characteristics of the tissue microstructure and potentially help in the diagnosis and classification of various pathological processes. In this review, we present the basic principles and methods of analysing multi-b-value diffusion imaging data and specifically focus on the known possibilities for its use in the diagnosis of brain lesions. We also suggest possible directions for further research.