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Background: Even though the need has been challenged, admitting patients to an intensive care or medium care unit (ICU/MCU) after adult supratentorial tumor craniotomy remains common practice. We have introduced a "no ICU, unless" policy for tumor craniotomy patients and evaluate costs, complications, and length of stay. Methods: A prospective cohort study was performed comparing patients that underwent tumor craniotomy for supratentorial tumors during 2 years after introduction of the new policy with the year before. Results: A reduction in ICU/MCU admittance from 88 to 23% of patients was found resulting in 13% cost reduction. Also, the new policy resulted in a 1.4-day shorter post-operative length of stay. Minor complications were reduced, while major complications remained the same. All major complications are reviewed. Conclusions: We show that routine post-operative ICU/MCU admittance after tumor craniotomy does not reduce complications, but actually interferes with recovery of our patients. Changing the paradigm results in earlier discharge and cost reduction. [ABSTRACT FROM AUTHOR]

It has been shown that transcutaneous electrical neurostimulation (TENS) reduces sympathetic tone. Spinal cord stimulation (SCS) has proven qualities to improve coronary, peripheral, and cerebral blood circulation. Therefore, we postulate that TENS and SCS affect the autonomic nervous system in analogous ways. In this line of thought, cervical application of TENS might be a useful and simple adjunct in the treatment of cerebrovascular disease by improving cerebral blood flow. Experiments were performed in order to assess whether cervical TENS is safe and whether an effect on cerebral blood flow velocity (CBFV) can be shown in healthy subjects. A controlled, non-randomized, phase 1 study was performed with 20 healthy volunteers. Cervical TENS was applied in several frequencies, with and without hyperventilation. Continuous registration of blood pressure, pulse, CBFV (estimated by transcranial Doppler sonography) and end-tidal carbon dioxide concentration was performed. Cervical TENS was well-tolerated by all subjects. Despite small effects on heart rate (HR) and mean arterial blood pressure (MAP), a significant effect on middle cerebral artery (MCA) blood flow velocity was not demonstrated. No effect of age, gender, current or session order on MCA, HR, or MAP was found. TENS did not influence the effect of hyperventilation. In these experiments, application of cervical TENS is proven to be a safe procedure. However, no effects on cerebral blood flow velocity could be detected, perhaps due to the intact cerebral autoregulation in the healthy volunteers. [ABSTRACT FROM AUTHOR]

The development of an intracranial aneurysm (IA) is a multifactorial process, involving genetic and environmental factors. The presence of IA or aneurysmal subarachnoid hemorrhage (aSAH) in twins is particularly interesting, since both genetic and environmental factors can be studied. It also raises the question of whether, when one twin is affected, the other asymptomatic twin should be examined for an IA. We report on a monozygotic (MZ) twin-pair with aSAH in both twins and we review all reported cases of IA in MZ twins. Including our case, we found only 14 MZ twin-pairs in which both twins harbored an IA, suggesting a heavy underreporting in the medical literature. In this small group, a high concordance was noted in the sites of IAs. In MZ twins, the preferred sites for IAs are the branching arteries, while aneurysms arising from fusion arteries are rare. These sites differ from the preferential sites seen in series of familial IAs and series of sporadic IAs. We therefore hypothesize that the twinning process might play a significant role in the development of IAs in MZ twins. To further explore and substantiate this, the large twin registries should be studied. Although IAs in MZ twins with a negative family history for IAs should not be regarded as familial IAs, screening of the asymptomatic twin should be seriously considered if one MZ twin presents with an aSAH or an IA, because of the high fatality rates reported in asymptomatic (and not screened) MZ twin-halves. [ABSTRACT FROM AUTHOR]

Objectives: To provide an overview of the existing research concerning the use and effects of AR in patient education.Methods: Following PRISMA guidelines four electronic databases were systematically searched.Inclusion Criteria: empirical studies using any type of AR intervention in patient education across all medical specialties. Quality assessment of the retrieved literature was carried out.Results: Ten papers, comprising 788 patients, were identified and included (Randomized controlled trial (RCT)(n = 3), non-randomized controlled trial (n = 3), before-and-after study (n = 3), and qualitative survey (n = 1)). Retrieved literature showed itself to be highly heterogeneous. The studied population included patients suffering from a diverse spectrum of chronic diseases (e.g., prostate cancer, diabetes mellitus, multiple sclerosis, epilepsy). Quantitative results indicated that the use of AR had a positive effect on knowledge retention and patient satisfaction. Qualitative findings suggested that patients liked the technology and felt comfortable with its use for educational purposes. The quality of the retrieved results was shown to be moderate to low.Conclusion: The limited evidence of this topic suggests the possible potential of AR in patient education.Practice Implication: More research, using high-quality study designs and more evidence-based interventions, is needed to fully appreciate the value of AR on patient education. [ABSTRACT FROM AUTHOR]

The tumor microenvironment of glioblastoma IDH-wildtype is highly immune suppressive and is characterized by a strong component of myeloid-derived suppressor cells (MDSCs). To interfere with the immune suppressive functions of MDSCs, a comprehensive understanding on how MDSCs acquire their suppressive phenotype is essential. Previously, we and others have shown a distinct Sialic acid-binding immunoglobulin-like lectin (Siglec) receptor expression profile for MDSCs in glioblastoma. Siglec receptors can transmit inhibitory signals comparable to PD-1 and are suggested to act as glyco-immune checkpoints. Here, we investigated how glioma specific Siglec-sialic acid interactions influence myeloid immune suppressive functions. Co-culturing monocytes with glioblastoma cells induced CD163 expression on the monocytes. Upon desialylation of the glioblastoma cells, this induction of CD163 was hampered, and furthermore, the monocytes were now able to secrete higher amounts of IL-6 and TNFα compared to fully sialylated glioblastoma cells. Additionally, Siglec-specific triggering using anti-Siglec-7 or Siglec-9 antibodies displayed a decreased TNFα secretion by the monocytes, validating the role of the Siglec–Sialic axis in the co-culture experiments. Together, our results demonstrate that glioblastoma cells induce a myeloid immune-suppressive phenotype that could be partly rescued by lowering the glioblastoma-associated sialic acid levels. This manuscript supports further research of the Siglec–Sialic acid axis in the context of glioblastoma and its potential to improve clinical outcome. [ABSTRACT FROM AUTHOR]

Purpose: Flat-panel computed tomography (FP-CT) is increasingly available in angiographic rooms and hybrid OR's. Considering its easy access, cerebral imaging using FP-CT is an appealing modality for intra-procedural applications. The purpose of this systematic review is to assess the diagnostic accuracy of FP-CT compared with perfusion computed tomography (CTP) and perfusion magnetic resonance (MRP) in cerebral perfusion imaging. Methods: We performed a systematic literature search in the Cochrane Library, MEDLINE, Embase, and Web of Science up to June 2019 for studies directly comparing FP-CT with either CTP or MRP in vivo. Methodological quality was assessed using the QUADAS-2 tool. Data on diagnostic accuracy was extracted and pooled if possible. Results: We found 11 studies comparing FP-CT with CTP and 5 studies comparing FP-CT with MRP. Most articles were pilot or feasibility studies, focusing on scanning and contrast protocols. All patients studied showed signs of cerebrovascular disease. Half of the studies were animal trials. Quality assessment showed unclear to high risks of bias and low concerns regarding applicability. Five studies reported on diagnostic accuracy; FP-CT shows good sensitivity (range 0.84–1.00) and moderate specificity (range 0.63–0.88) in detecting cerebral blood volume (CBV) lesions. Conclusions: Even though FP-CT provides similar CBV values and reconstructed blood volume maps as CTP in cerebrovascular disease, additional studies are required in order to reliably compare its diagnostic accuracy with cerebral perfusion imaging. [ABSTRACT FROM AUTHOR]

Simple Summary: Patients suffering from glioblastoma receive treatment according to the Stupp protocol. After chemoradiotherapy, the glioblastoma either continue to develop, or treatment-related vascular damage comes into play, both causing new, seemingly identical contrast-enhancing lesions in follow-up MRI, where clinicians and radiologists alike can only differentiate between tumor progression (TP) and treatment-related abnormalities (TRA) by seeing the temporal evolution of the lesion and the patients clinical status. We investigate the use of diffusion MRI and the quantitative apparent diffusion coefficient (ADC) in a retrospective patient cohort and we sought to validate a previously reported ADC cutoff value for its distinctive properties between TP and TRA. In the end, ADC values were shown not to be highly discriminative and, compared to the mean ADC values between TP and TRA previously reported in the literature, are more overlapping than expected. Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10−3 mm2/s; SD = 0.31 × 10−3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10−3 mm2/s; SD = 0.28 × 10−3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10−3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma (GBM) is the most common primary, malignant brain tumour with a 5-year survival of 5%. If possible, a glioblastoma is resected and further treated with chemoradiation therapy (CRT), but resection is not feasible in about 30% of cases. Current standard of care in these cases is a biopsy followed by CRT. Magnetic resonance (MR) imaging-guided laser interstitial thermal therapy (LITT) has been suggested as a minimally invasive alternative when surgery is not feasible. However, high-quality evidence directly comparing LITT with standard of care is lacking, precluding any conclusions on (cost-)effectiveness. We therefore propose a multicenter randomized controlled study to assess the (cost-)effectiveness of MR-guided LITT as compared to current standard of care (EMITT trial). Methods and analysis: The EMITT trial will be a multicenter pragmatic randomized controlled trial in the Netherlands. Seven Dutch hospitals will participate in this study. In total 238 patients will be randomized with 1:1 allocation to receive either biopsy combined with same-session MR-guided LITT therapy followed by CRT or the current standard of care being biopsy followed by CRT. The primary outcomes will be health-related quality of life (HR-QoL) (non-inferiority) using EORTC QLQ-C30 + BN20 scores at 5 months after randomization and overall survival (superiority). Secondary outcomes comprise cost-effectiveness (healthcare and societal perspective) and HR-QoL of life over an 18-month time horizon, progression free survival, tumour response, disease specific survival, longitudinal effects, effects on adjuvant treatment, ablation percentage and complication rates. Discussion: The EMITT trial will be the first RCT on the effectiveness of LITT in patients with glioblastoma as compared with current standard of care. Together with the Dutch Brain Tumour Patient association, we hypothesize that LITT may improve overall survival without substantially affecting patients' quality of life. Trial registration: This trial is registered at ClinicalTrials.gov (NCT05318612). [ABSTRACT FROM AUTHOR]

Vestibular schwannoma (VS) growth of ≥2 mm during serial MRI observation, irrespective of size, is the benchmark for treatment initiation in almost all centers. Although the probability of less optimal outcomes significantly increases in VS closer to the brainstem, early intervention does not improve long-term quality of life. Moving beyond the recommendation of definitive treatment for all VS after detected growth, we subclassified Koos 2 tumors based on extrameatal extension and relation to the brainstem. The aim of the current study was to evaluate the Koos 2 subclassification's validity and the inter-and intra-rater reliability of the entire Koos classification. Six experts, including neurosurgeons, otorhinolaryngologists and radiologists from two tertiary referral centers, classified 43 VS MRI scans. Validity of the Koos 2 subclassification was evaluated by the percentage agreement against the multidisciplinary skull base tumor board management advice. Inter- and intra-rater reliability were calculated using the intraclass correlation coefficient (ICC). Validity was almost perfect in Koos 2a VSs with a 100% agreement and 87.5% agreement for Koos 2b. Inter-rater reliability for all Koos grades was significantly excellent (ICC 0.91; 95%CI 0.866 to 0.944, p= <0.001). Five raters had an excellent intra-rater reliability (ICC > 0.90; p= <0.01) and one rater had a good intra-rater reliability (ICC 0.88; 95% CI 0.742 to 0.949). Although multiple factors influence decision-making, the classification of Koos 2a and 2b with excellent inter- and intra-rater reliability, can aid in recommending treatment initiation, moving beyond detected tumor growth, aiming to optimize patient centered care. [ABSTRACT FROM AUTHOR]

Simple Summary: This meta-analysis provides a first head-to-head comparison of PET and perfusion weighted magnetic resonance imaging (PWI) in the surveillance of post-treatment gliomas in order to distinguish tumor progression (TP) from treatment-related abnormalities (TRA). Although various reviews have been published on the use of either PET or PWI in this setting, no meta-analysis to date provides a head-to-head comparison of both techniques. The findings of this paper illuminate the strengths and limitations of each technique and enable clinicians to take more evidence-based decisions in their daily practice with regard to the imaging surveillance of gliomas. The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-11C]methionine, 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG), O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) and 6-[18F]-fluoro-3,4-dihydroxy-L-phenylalanine ([18F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP. [ABSTRACT FROM AUTHOR]

Radiological features on magnetic resonance imaging (MRI) were attributed to oligodendroglioma, although the diagnostic accuracy in a real-world clinical setting remains partially elusive. This study investigated the accuracy and robustness of tumor heterogeneity and tumor border delineation on T2-weighted MRI to distinguish oligodendroglioma from astrocytoma. Eight readers from three different specialties (radiology, neurology, neurosurgery) with varying levels of experience blindly rated 79 T2-weighted MR images of patients with either oligodendroglioma or astrocytoma. After the first reading session, all readers were re-invited for a second reading session within three weeks. Diagnostic accuracy, including area under the receiver operator characteristics curve (AUC), and intra-observer variability and inter-observer variability were used as outcome measures. Pooled sensitivity and specificity to distinguish oligodendroglioma from astrocytoma for the use of tumor heterogeneity were 59.9 % respectively 74.5 %, and 85.7 % respectively 40.1 % for tumor border. A second reading session did not result in a significant change in sensitivity or specificity for tumor heterogeneity (P = 0.752 and P = 0.733, respectively) or tumor border (P = 0.309 and P = 0.271, respectively). An AUC of 0.825 was achieved with regard to predicting oligodendroglial origin of gliomas. Intra-observer agreement ranged from moderate to very good for tumor heterogeneity (kappa-value 0.43–0.87) and tumor border (0.40–0.84). A moderate inter-oberserver agreement was achieved for tumor heterogeneity and tumor border (kappa-value of 0.50 and 0.45, respectively). This study demonstrates that tumor heterogeneity and tumor borders on T2-weighted MRI could be used with moderate Finter-observer agreement to non-invasively distinguish oligodendroglioma from astrocytoma. [ABSTRACT FROM AUTHOR]

Objectives: Different machine learning algorithms (MLAs) for automated segmentation of gliomas have been reported in the literature. Automated segmentation of different tumor characteristics can be of added value for the diagnostic work-up and treatment planning. The purpose of this study was to provide an overview and meta-analysis of different MLA methods. Methods: A systematic literature review and meta-analysis was performed on the eligible studies describing the segmentation of gliomas. Meta-analysis of the performance was conducted on the reported dice similarity coefficient (DSC) score of both the aggregated results as two subgroups (i.e., high-grade and low-grade gliomas). This study was registered in PROSPERO prior to initiation (CRD42020191033). Results: After the literature search (n = 734), 42 studies were included in the systematic literature review. Ten studies were eligible for inclusion in the meta-analysis. Overall, the MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82–0.86). In addition, a DSC score of 0.83 (95% CI: 0.80–0.87) and 0.82 (95% CI: 0.78–0.87) was observed for the automated glioma segmentation of the high-grade and low-grade gliomas, respectively. However, heterogeneity was considerably high between included studies, and publication bias was observed. Conclusion: MLAs facilitating automated segmentation of gliomas show good accuracy, which is promising for future implementation in neuroradiology. However, before actual implementation, a few hurdles are yet to be overcome. It is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set. Key Points: • MLAs from the included studies showed an overall DSC score of 0.84 (95% CI: 0.82–0.86), indicating a good performance. • MLA performance was comparable when comparing the segmentation results of the high-grade gliomas and the low-grade gliomas. • For future studies using MLAs, it is crucial that quality guidelines are followed when reporting on MLAs, which includes validation on an external test set. [ABSTRACT FROM AUTHOR]

Object: Surgery of tumours in the cerebellopontine angle (CPA) can lead to loss of facial nerve function. Different methods of intra-operative nerve monitoring (IOM) (including free-running EMG, direct nerve stimulation and transcranial motor evoked potentials (TcMEP)) have been used to predict facial nerve outcome during surgery. Recent research has shown TcMEP threshold increase and the occurrence of A-trains on the EMG to have great potential in doing so. This study compares these two methods and correlates them to House-Brackmann (HB) scores post-op in patients with tumours in the cerebellopontine angle. Method: Forty-three patients (one was operated twice) with large CPA tumours treated surgically in the Radboud University Medical Center between 2015 and 2019 were included in this study. During surgery, TcMEP threshold increases and A-train activity were measured. Because our treatment paradigm aims at facial nerve preservation (accepting residual tumour), TcMEP threshold increase of over 20 mA or occurrence of A-trains were considered as warning signs and used as a guide for terminating surgery. HB scores were measured post-op, at 6 weeks, 6 months and 1 year after surgery. Spearman's correlation was calculated between the IOM-values and the HB scores for a homogeneous subgroup of 30 patients with vestibular schwannoma (VS) without neurofibromatosis type II (NF-II) and all patients collectively. Results: TcMEP threshold was successfully measured in 39 (90.7%) procedures. In the homogeneous VS non-NFII group, we found a statistically significant moderate-to-strong correlation between TcMEP threshold increase and House Brackmann score immediately post-op, at 6 weeks, 6 months and 1 year after surgery (Spearman's rho of 0.79 (p < 0.001), 0.74 (p < 0.001), 0.64 (p < 0.001) and 0.58 (p = 0.002), respectively). For A-trains, no correlation was found. Similar results were found when including all patients with CPA tumours. A threshold increase of < 20 mA was a predictor of good facial nerve outcome. Conclusion: These results show that TcMEP threshold increases are strongly correlated to post-operative HB scores, while A-trains are not. This suggests TcMEP threshold increases can be a valuable predictor for facial nerve outcome in patients with large tumours when facial nerve preservation is prioritized over total resection. In this study, we found no use for A-trains to prevent facial nerve deficits. [ABSTRACT FROM AUTHOR]

Background: The surgeons' estimate of the extent of resection (EOR) shows little accuracy in previous literature. Considering the developments in surgical techniques of glioblastoma (GBM) treatment, we hypothesize an improvement in this estimation. This study aims to compare the EOR estimated by the neurosurgeon with the EOR determined using volumetric analysis on the post-operative MR scan. Methods: Pre- and post-operative tumor volumes were calculated through semi-automatic volumetric assessment by three observers. Interobserver agreement was measured using intraclass correlation coefficient (ICC). A univariate general linear model was used to study the factors influencing the accuracy of estimation of resection percentage. Results: ICC was high for all three measurements: pre-operative tumor volume was 0.980 (0.969–0.987), post-operative tumor volume 0.974 (0.961–0.984), and EOR 0.947 (0.917–0.967). Estimation of EOR by the surgeon showed moderate accuracy and agreement. Multivariable analysis showed a statistically significant effect of operating neurosurgeon (p = 0.01), use of fluorescence (p < 0.001), and resection percentage (p < 0.001) on the accuracy of the EOR estimation. Conclusion: All measurements through semi-automatic volumetric analysis show a high interobserver agreement, suggesting this to be a reliable assessment of EOR. We found a moderate reliability of the surgeons' estimate of EOR. Therefore, (early) post-operative MRI scanning for evaluation of EOR remains paramount. [ABSTRACT FROM AUTHOR]

Gliomas appear to be highly immunosuppressive tumors, with a strong myeloid component. This includes MDSCs, which are a heterogeneous, immature myeloid cell population expressing myeloid markers Siglec-3 (CD33) and CD11b and lacking markers of mature myeloid cells including MHC II. Siglec-3 is a member of the sialic acid-binding immunoglobulin-like lectin (Siglec) family and has been suggested to promote MDSC expansion and suppression. Siglecs form a recently defined family of receptors with potential immunoregulatory functions but only limited insight in their expression on immune regulatory cell subsets, prompting us to investigate Siglec expression on MDSCs. We determined the expression of different Siglec family members on monocytic-MDSCs (M-MDSCs) and polymorphnuclear-MDSCs (PMN-MDSCs) from blood of glioma patients and healthy donors, as well as from patient-derived tumor material. Furthermore, we investigated the presence of sialic acid ligands for these Siglecs on MDSCs and in the glioma tumor microenvironment. Both MDSC subsets express Siglec-3, -5, -7 and -9, with higher levels of Siglec-3, -7 and -9 on M-MDSCs and higher Siglec-5 levels on PMN-MDSCs. Similar Siglec expression profiles were found on MDSCs from healthy donors. Furthermore, the presence of Siglec-5 and -9 was also confirmed on PMN-MDSCs from glioma tissue. Interestingly, freshly isolated glioma cells predominantly expressed sialic acid ligands for Siglec-7 and -9, which was confirmed in situ. In conclusion, our data show a distinct Siglec expression profile for M- and PMN-MDSCs and propose possible sialic acid–Siglec interactions between glioma cells and MDSCs in the tumor microenvironment. [ABSTRACT FROM AUTHOR]

Diffuse gliomas often carry point mutations in isocitrate dehydrogenase (IDH1mut), resulting in metabolic stress. Although IDHmut gliomas are difficult to culture in vitro, they thrive in the brain via diffuse infiltration, suggesting brain-specific tumor-stroma interactions that can compensate for IDH-1 deficits. To elucidate the metabolic adjustments in clinical IDHmut gliomas that contribute to their malignancy, we applied a recently developed method of targeted quantitative RNA next-generation sequencing to 66 clinical gliomas and relevant orthotopic glioma xenografts, with and without the endogenous IDH-1R132H mutation. Datasets were analyzed in R using Manhattan plots to calculate distance between expression profiles, Ward's method to perform unsupervised agglomerative clustering, and the Mann Whitney U test and Fisher's exact tests for supervised group analyses. The significance of transcriptome data was investigated by protein analysis, in situ enzymatic activity mapping, and in vivo magnetic resonance spectroscopy of orthotopic IDH1mut- and IDHwt-glioma xenografts. Gene set enrichment analyses of clinical IDH1mut gliomas strongly suggest a role for catabolism of lactate and the neurotransmitter glutamate, whereas, in IDHwt gliomas, processing of glucose and glutamine are the predominant metabolic pathways. Further evidence of the differential metabolic activity in these cancers comes from in situ enzymatic mapping studies and preclinical in vivo magnetic resonance spectroscopy imaging. Our data support an evolutionary model in which IDHmut glioma cells exist in symbiosis with supportive neuronal cells and astrocytes as suppliers of glutamate and lactate, possibly explaining the diffuse nature of these cancers. The dependency on glutamate and lactate opens the way for novel approaches in the treatment of IDHmut gliomas. [ABSTRACT FROM AUTHOR]

Glioblastoma is the most aggressive adult primary brain tumor which is incurable despite intensive multimodal treatment. Inter- and intratumoral heterogeneity poses one of the biggest barriers in the diagnosis and treatment of glioblastoma, causing differences in treatment response and outcome. Noninvasive prognostic and predictive tests are highly needed to complement the current armamentarium. Noninvasive testing of glioblastoma uses multiple techniques that can capture the heterogeneity of glioblastoma. This set of diagnostic approaches comprises advanced MRI techniques, nuclear imaging, liquid biopsy, and new integrated approaches including radiogenomics and radiomics. New treatment options such as agents targeted at driver oncogenes and immunotherapy are currently being developed, but benefit for glioblastoma patients still has to be demonstrated. Understanding and unraveling tumor heterogeneity and microenvironment can help to create a treatment regime that is patient-tailored to these specific tumor characteristics. Improved noninvasive tests are crucial to this success. This review discusses multiple diagnostic approaches and their effect on predicting and monitoring treatment response in glioblastoma. [ABSTRACT FROM AUTHOR]

Objective Simultaneous tumor resection and cranial reconstruction can be a challenging task. Surgical navigation is an indispensable tool in making this single-step procedure possible. In this technical note, we describe a new technique for this procedure to ensure a precise resection and optimal fit of the implant in a patient with an intraosseous meningioma. Methods We generated a 3-dimensional (3D) model of the patient's skull based on a computed tomography scan and created a digital “resection line” object using 3D Studio Max 2016 software. Based on this object, the patient-specific implant was generated and printed with a 3D printer. Before surgery, the digital object was transferred to the neuronavigation system to enable a navigated resection of the lesion to ensure maximum precision. During surgery, the craniotomy was performed, and the custom-made implant was fitted in a single step. Results The planned resection was achieved, and the implant could be fitted without need for further adjustments to the resection border. Conclusions We provide a simple technique to digitally define a planned resection site and create a custom-made implant using specialized software and 3D printing to enable single-step resection of a skull lesion and cranial reconstruction, thereby reducing surgical time and costs and ensuring a good cosmetic result. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioma prognosis and treatment are based on histopathological characteristics and molecular profile. Following the World Health Organization (WHO) guidelines (2016), the most important molecular diagnostic markers include IDH1/2-genotype and 1p/19q codeletion status, although more recent publications also include ARTX genotype and TERT- and MGMT promoter methylation. Machine learning algorithms (MLAs), however, were described to successfully determine these molecular characteristics non-invasively by using magnetic resonance imaging (MRI) data. The aim of this review and meta-analysis was to define the diagnostic accuracy of MLAs with regard to these different molecular markers. We found high accuracies of MLAs to predict each individual molecular marker, with IDH1/2-genotype being the most investigated and the most accurate. Radiogenomics could therefore be a promising tool for discriminating genetically determined gliomas in a non-invasive fashion. Although encouraging results are presented here, large-scale, prospective trials with external validation groups are warranted. Treatment planning and prognosis in glioma treatment are based on the classification into low- and high-grade oligodendroglioma or astrocytoma, which is mainly based on molecular characteristics (IDH1/2- and 1p/19q codeletion status). It would be of great value if this classification could be made reliably before surgery, without biopsy. Machine learning algorithms (MLAs) could play a role in achieving this by enabling glioma characterization on magnetic resonance imaging (MRI) data without invasive tissue sampling. The aim of this study is to provide a performance evaluation and meta-analysis of various MLAs for glioma characterization. Systematic literature search and meta-analysis were performed on the aggregated data, after which subgroup analyses for several target conditions were conducted. This study is registered with PROSPERO, CRD42020191033. We identified 724 studies; 60 and 17 studies were eligible to be included in the systematic review and meta-analysis, respectively. Meta-analysis showed excellent accuracy for all subgroups, with the classification of 1p/19q codeletion status scoring significantly poorer than other subgroups (AUC: 0.748, p = 0.132). There was considerable heterogeneity among some of the included studies. Although promising results were found with regard to the ability of MLA-tools to be used for the non-invasive classification of gliomas, large-scale, prospective trials with external validation are warranted in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Glioblastoma (GBM) is the most malignant primary brain tumor, for which improving patient outcome is limited by a substantial amount of tumor heterogeneity. Magnetic resonance imaging (MRI) in combination with machine learning offers the possibility to collect qualitative and quantitative imaging features which can be used to predict patient prognosis and relevant tumor markers which can aid in selecting the right treatment. This study showed that combining these MRI features with clinical features has the highest prognostic value for GBM patients; this model performed similarly in an independent GBM cohort, showing its reproducibility. The prediction of tumor markers showed promising results in the training set but not could be validated in the independent dataset. This study shows the potential of using MRI to predict prognosis and tumor markers, but further optimization and prospective studies are warranted. Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative (Visually Accessible Rembrandt Images (VASARI)) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase (IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64–0.78) and used to stratify Kaplan–Meijer curves in two survival groups (p-value < 0.001). The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582–8.25) and MGMT-methylation (AUC 0.667, 95% CI 0.522–0.82) but not for IDH-mutation (AUC 0.695, 95% CI 0.436–0.927). The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted. [ABSTRACT FROM AUTHOR]

Background: Laser interstitial thermal therapy (LITT) is a minimal invasive neurosurgical technique for the treatment of brain tumors. Results of LITT have been reported in a case series of patients with deep seated and/or recurrent glioblastoma or cerebral metastases. With this review we aim to summarize the currently available evidence regarding safety and effectiveness of LITT in patients with newly diagnosed glioblastoma (nGBM). Methods: A literature search was performed using electronic databases (PubMed and Embase). Papers were assessed for the methodological quality using the Risk Of Bias In Non- randomised Studies - of Interventions (ROBINS-I) tool, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the quality of the evidence. Results: We identified 835 papers of which only 11 articles were eligible for our review. All papers suffered from serious or critical risk of bias, and the quality of evidence was graded as very low according to the GRADE criteria. None of the studies was randomized and reporting of confounders and other parameters was poor. Median overall survival (OS) ranged from 4.1 to 32 months and progression free survival (PFS) from 2 to 31 months. The mean complication rate was 33.7%. No quality of life or cost-effectiveness data were reported. Conclusions: Due to the low quality of the studies, it is not possible to draw firm conclusions regarding the (cost) effectiveness of LITT in patients with newly diagnosed glioblastoma. The low quality of evidence shows the need for a well-designed prospective multicenter randomized controlled trial. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) technologies are being used for patient education. For glioma, a personalized 3D model can show the patient specific tumor and eloquent areas. We aim to compare the amount of information that is understood and can be recalled after a pre-operative consult using a 3D model (physically printed or in Augmented Reality (AR)) versus two-dimensional (2D) MR images. In this explorative study, healthy individuals were eligible to participate. Sixty-one participants were enrolled and assigned to either the 2D (MRI/fMRI), 3D (physical 3D model) or AR groups. After undergoing a mock pre-operative consultation for low-grade glioma surgery, participants completed two assessments (one week apart) testing information recall using a standardized questionnaire. The 3D group obtained the highest recall scores on both assessments (Cohen's d = 1.76 and Cohen's d = 0.94, respectively, compared to 2D), followed by AR and 2D, respectively. Thus, real-size 3D models appear to improve information recall as compared to MR images in a pre-operative consultation for glioma cases. Future clinical studies should measure the efficacy of using real-size 3D models in actual neurosurgery patients. [ABSTRACT FROM AUTHOR]

Many biology-based precision drugs are available that neutralize aberrant molecular pathways in cancer. Molecular heterogeneity and the lack of reliable companion diagnostic biomarkers for many drugs makes targeted treatment of cancer inaccurate for many individuals. Identifying actionable hyperactive biological pathways in individual cancers may improve this situation. To achieve this we applied a novel targeted RNA next generation sequencing (t/RNA-NGS) technique to surgically obtained glioma tissues. The test combines mutation detection with analysis of biological pathway activities that are involved in tumour behavior in many cancer types (e.g. tyrosine kinase signaling, angiogenesis signaling, immune response, metabolism), via quantitative measurement of transcript levels and splice variants of hundreds of genes. We here present proof of concept that the technique, which uses molecular inversion probes, generates a histology-independent molecular diagnosis and identifies classifiers that are strongly associated with conventional histopathology diagnoses and even with patient prognosis. The test not only confirmed known glioma-associated molecular aberrations but also identified aberrant expression levels of actionable genes and mutations that have so far been considered not to be associated with glioma, opening up the possibility of drug repurposing for individual patients. Its cost-effectiveness makes t/RNA-NGS to an attractive instrument to aid oncologists in therapy decision making. [ABSTRACT FROM AUTHOR]

Background Patients with cancer need high-quality information about disease stage, treatment options, and side effects. High-quality information can also improve health literacy, shared decision making, and satisfaction. We created patient-specific three-dimensional (3D) models of tumors including surrounding functional areas and assessed what patients with glioma value (or fear) about the models when they are used to educate them about the relationship between their tumor and specific brain parts, the surgical procedure, and risks. Methods This exploratory study included adult patients with glioma who underwent functional magnetic resonance imaging and diffusion tensor imaging as part of preoperative work-up. All participants received an actual-size 3D model printed based on functional magnetic resonance imaging and diffusion tensor imaging. Semistructured interviews were conducted to identify facilitators and barriers for using the model and perceived effects. Results Models were successfully created for all 11 participants. There were 18 facilitators and 8 barriers identified. The model improved patients' understanding about their situation; patients reported that it was easier to ask their neurosurgeon questions based on their model and that it supported their decision about preferred treatment. A perceived barrier for using the 3D model was that it could be emotionally confronting, particularly in an early phase of the disease. Positive effects were related to psychological domains, including coping, learning effects, and communication. Conclusions Patient-specific 3D models are promising and simple tools that could help patients with glioma better understand their situation, treatment options, and risks. These models have the potential to improve shared decision making. [ABSTRACT FROM AUTHOR]