The development of brain metastases in patients with different therapeutic strategies for metastatic renal cell cancer.

A diagnosis of brain metastasis (BM) significantly affects quality of life in patients with metastatic renal cell cancer (mRCC). Although systemic treatments have shown efficacy in mRCC, active surveillance (AS) is still commonly used in clinical practice. In this single-center cohort study, we assessed the impact of different initial treatment strategies for metastatic RCC (mRCC) on the development of BM. All consecutive patients diagnosed with mRCC between 2011 and 2022 were included at the Erasmus MC Cancer Institute, the Netherlands, and a subgroup of patients with BM was selected. In total, 381 patients with mRCC (ECM, BM, or both) were identified. Forty-six patients had BM of whom 39 had metachronous BM (diagnosed ≥1 month after ECM). Twenty-five (64.1%) of these 39 patients with metachronous BM had received prior systemic treatment for ECM and 14 (35.9%) patients were treatment naive at BM diagnosis. The median BM-free survival since ECM diagnosis was significantly longer (p = .02) in previously treated patients (29.0 [IQR 12.6-57.0] months) compared to treatment naive patients (6.8 [IQR 1.0-7.0] months). In conclusion, patients with mRCC who received systemic treatment for ECM prior to BM diagnosis had a longer BM-free survival as compared to treatment naïve patients. These results emphasize the need for careful evaluation of treatment strategies, and especially AS, for patients with mRCC.

Diffuse infiltrating tumour with the molecular profile of an atypical teratoid rhabdoid tumour (AT/RT SHH-1B) in an adult patient.

We describe a 46-year-old patient with an IDH-wildtype diffusely infiltrating atypical teratoid/rhabdoid tumour (AT/RT), SHH-1B molecular subtype. The unusual histology and subsequent diagnosis in an adult patient will be discussed.

Patient-Specific Vascular Flow Phantom for MRI- and Doppler Ultrasound Imaging.

OBJECTIVE: Intraoperative Doppler ultrasound imaging of human brain vasculature is an emerging neuro-imaging modality that offers vascular brain mapping with unprecedented spatiotemporal resolution. At present, however, access to the human brain using Doppler Ultrasound is only possible in this intraoperative context, posing a significant challenge for validation of imaging techniques. This challenge necessitates the development of realistic flow phantoms outside of the neurosurgical operating room as external platforms for testing hardware and software. An ideal ultrasound flow phantom should provide reference-like values in standardized topologies such as a slanted pipe, and allow for measurements in structures closely resembling vascular morphology of actual patients. Additionally, the phantom should be compatible with other clinical cerebrovascular imaging modalities. To meet these criteria, we developed and validated a versatile, multimodal MRI- and ultrasound Doppler phantom. METHODS: Our approach incorporates the latest advancements in phantom research using tissue-mimicking material and 3D-printing with water-soluble resin to create wall-less patient-specific lumens, compatible for ultrasound and MRI. RESULTS: We successfully produced three distinct phantoms: a slanted pipe, a y-shape phantom representing a bifurcating vessel and an arteriovenous malformation (AVM) derived from clinical Digital Subtraction Angiography (DSA)-data of the brain. We present 3D ultrafast power Doppler imaging results from these phantoms, demonstrating their ability to mimic complex flow patterns as observed in the human brain. Furthermore, we showcase the compatibility of our phantom with Magnetic Resonance Imaging (MRI). CONCLUSION: We developed an MRI- and Doppler Ultrasound-compatible flow-phantom using customizable, water-soluble resin prints ranging from geometrical forms to patient-specific vasculature.

Evaluating the Predictive Value of Glioma Growth Models for Low-Grade Glioma After Tumor Resection.

Tumor growth models have the potential to model and predict the spatiotemporal evolution of glioma in individual patients. Infiltration of glioma cells is known to be faster along the white matter tracts, and therefore structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) can be used to inform the model. However, applying and evaluating growth models in real patient data is challenging. In this work, we propose to formulate the problem of tumor growth as a ranking problem, as opposed to a segmentation problem, and use the average precision (AP) as a performance metric. This enables an evaluation of the spatial pattern that does not require a volume cut-off value. Using the AP metric, we evaluate diffusion-proliferation models informed by structural MRI and DTI, after tumor resection. We applied the models to a unique longitudinal dataset of 14 patients with low-grade glioma (LGG), who received no treatment after surgical resection, to predict the recurrent tumor shape after tumor resection. The diffusion models informed by structural MRI and DTI showed a small but significant increase in predictive performance with respect to homogeneous isotropic diffusion, and the DTI-informed model reached the best predictive performance. We conclude there is a significant improvement in the prediction of the recurrent tumor shape when using a DTI-informed anisotropic diffusion model with respect to istropic diffusion, and that the AP is a suitable metric to evaluate these models. All code and data used in this publication are made publicly available.

Preoperative assessment of eloquence in neurosurgery: a systematic review.

BACKGROUND AND OBJECTIVES: Tumor location and eloquence are two crucial preoperative factors when deciding on the optimal treatment choice in glioma management. Consensus is currently lacking regarding the preoperative assessment and definition of eloquent areas. This systematic review aims to evaluate the existing definitions and assessment methods of eloquent areas that are used in current clinical practice. METHODS: A computer-aided search of Embase, Medline (OvidSP), and Google Scholar was performed to identify relevant studies. This review includes articles describing preoperative definitions of eloquence in the study's Methods section. These definitions were compared and categorized by anatomical structure. Additionally, various techniques to preoperatively assess tumor eloquence were extracted, along with their benefits, drawbacks and ease of use. RESULTS: This review covers 98 articles including 12,714 participants. Evaluation of these studies indicated considerable variability in defining eloquence. Categorization of these definitions yielded a list of 32 brain regions that were considered eloquent. The most commonly used methods to preoperatively determine tumor eloquence were anatomical classification systems and structural MRI, followed by DTI-FT, functional MRI and nTMS. CONCLUSIONS: There were major differences in the definitions and assessment methods of eloquence, and none of them proved to be satisfactory to express eloquence as an objective, quantifiable, preoperative factor to use in glioma decision making. Therefore, we propose the development of a novel, objective, reliable, preoperative classification system to assess eloquence. This should in the future aid neurosurgeons in their preoperative decision making to facilitate personalized treatment paradigms and to improve surgical outcomes.

Outcomes Associated With Intracranial Aneurysm Treatments Reported as Safe, Effective, or Durable: A Systematic Review and Meta-Analysis.

Importance: Testing new medical devices or procedures in terms of safety, effectiveness, and durability should follow the strictest methodological rigor before implementation. Objectives: To review and analyze studies investigating devices and procedures used in intracranial aneurysm (IA) treatment for methods and completeness of reporting and to compare the results of studies with positive, uncertain, and negative conclusions. Data Sources: Embase, MEDLINE, Web of Science, and The Cochrane Central Register of Clinical Trials were searched for studies on IA treatment published between January 1, 1995, and the October 1, 2022. Grey literature was retrieved from Google Scholar. Study Selection: All studies making any kind of claims of safety, effectiveness, or durability in the field of IA treatment were included. Data Extraction and Synthesis: Using a predefined data dictionary and analysis plan, variables ranging from patient and aneurysm characteristics to the results of treatment were extracted, as were details pertaining to study methods and completeness of reporting. Extraction was performed by 10 independent reviewers. A blinded academic neuro-linguist without involvement in IA research evaluated the conclusion of each study as either positive, uncertain, or negative. The study followed Preferring Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Main Outcomes and Measures: The incidence of domain-specific outcomes between studies with positive, uncertain, or negative conclusions regarding safety, effectiveness, or durability were compared. The number of studies that provided a definition of safety, effectiveness, or durability and the incidence of incomplete reporting of domain-specific outcomes were evaluated. Results: Overall, 12 954 studies were screened, and 1356 studies were included, comprising a total of 410 993 treated patients. There was no difference in the proportion of patients with poor outcome or in-hospital mortality between studies claiming a technique was safe, uncertain, or not safe. Similarly, there was no difference in the proportion of IAs completely occluded at last follow-up between studies claiming a technique was effective, uncertain, or noneffective. Less than 2% of studies provided any definition of safety, effectiveness, or durability, and only 1 of the 1356 studies provided a threshold under which the technique would be considered unsafe. Incomplete reporting was found in 546 reports (40%). Conclusions and Relevance: In this systematic review and meta-analysis of IA treatment literature, studies claiming safety, effectiveness, or durability of IA treatment had methodological flaws and incomplete reporting of relevant outcomes supporting these claims.

Impact of Novel Treatments in Patients with Melanoma Brain Metastasis: Real-World Data.

BACKGROUND: Melanoma brain metastasis (MBM) is associated with poor outcome, but targeted therapies (TTs) and immune checkpoint inhibitors (ICIs) have revolutionized treatment over the past decade. We assessed the impact of these treatments in a real-world setting. METHODS: A single-center cohort study was performed at a large, tertiary referral center for melanoma (Erasmus MC, Rotterdam, the Netherlands). Overall survival (OS) was assessed before and after 2015, after which TTs and ICIs were increasingly prescribed. RESULTS: There were 430 patients with MBM included; 152 pre-2015 and 278 post-2015. Median OS improved from 4.4 to 6.9 months (HR 0.67, p < 0.001) after 2015. TTs and ICIs prior to MBM diagnosis were associated with poorer median OS as compared to no prior systemic treatment (TTs: 2.0 vs. 10.9 and ICIs: 4.2 vs. 7.9 months, p < 0.001). ICIs directly after MBM diagnosis were associated with improved median OS as compared to no direct ICIs (21.5 vs. 4.2 months, p < 0.001). Stereotactic radiotherapy (SRT; HR 0.49, p = 0.013) and ICIs (HR 0.32, p < 0.001) were independently associated with improved OS. CONCLUSION: After 2015, OS significantly improved for patients with MBM, especially with SRT and ICIs. Demonstrating a large survival benefit, ICIs should be considered first after MBM diagnosis, if clinically feasible.

Impact of maximal extent of resection on postoperative deficits, patient functioning, and survival within clinically important glioblastoma subgroups.

BACKGROUND: The impact of extent of resection (EOR), residual tumor volume (RTV), and gross-total resection (GTR) in glioblastoma subgroups is currently unknown. This study aimed to analyze their impact on patient subgroups in relation to neurological and functional outcomes. METHODS: Patients with tumor resection for eloquent glioblastoma between 2010 and 2020 at 4 tertiary centers were recruited from a cohort of 3919 patients. RESULTS: One thousand and forty-seven (1047) patients were included. Higher EOR and lower RTV were significantly associated with improved overall survival (OS) and progression-free survival (PFS) across all subgroups, but RTV was a stronger prognostic factor. GTR based on RTV improved median OS in the overall cohort (19.0 months, P < .0001), and in the subgroups with IDH wildtype tumors (18.5 months, P = .00055), MGMT methylated tumors (35.0 months, P < .0001), aged <70 (20.0 months, P < .0001), NIHSS 0-1 (19.0 months, P = .0038), KPS 90-100 (19.5 months, P = .0012), and KPS ≤80 (17.0 months, P = .036). GTR was significantly associated with improved OS in the overall cohort (HR 0.58, P = .0070) and improved PFS in the NIHSS 0-1 subgroup (HR 0.47, P = .012). GTR combined with preservation of neurological function (OFO 1 grade) yielded the longest survival times (median OS 22.0 months, P < .0001), which was significantly more frequently achieved in the awake mapping group (50.0%) than in the asleep group (21.8%) (P < .0001). CONCLUSIONS: Maximum resection was especially beneficial in the subgroups aged <70, NIHSS 0-1, and KPS 90-100 without increasing the risk of postoperative NIHSS or KPS worsening. These findings may assist surgical decision making in individual glioblastoma patients.

Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning.

BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineation of the tumor is also desirable in the initial decision stages but is time-consuming. Previously, deep learning methods have been developed that can either non-invasively predict the genetic or histological features of glioma, or that can automatically delineate the tumor, but not both tasks at the same time. Here, we present our method that can predict the molecular subtype and grade, while simultaneously providing a delineation of the tumor. METHODS: We developed a single multi-task convolutional neural network that uses the full 3D, structural, preoperative MRI scans to predict the IDH mutation status, the 1p/19q co-deletion status, and the grade of a tumor, while simultaneously segmenting the tumor. We trained our method using a patient cohort containing 1508 glioma patients from 16 institutes. We tested our method on an independent dataset of 240 patients from 13 different institutes. RESULTS: In the independent test set, we achieved an IDH-AUC of 0.90, an 1p/19q co-deletion AUC of 0.85, and a grade AUC of 0.81 (grade II/III/IV). For the tumor delineation, we achieved a mean whole tumor Dice score of 0.84. CONCLUSIONS: We developed a method that non-invasively predicts multiple, clinically relevant features of glioma. Evaluation in an independent dataset shows that the method achieves a high performance and that it generalizes well to the broader clinical population. This first-of-its-kind method opens the door to more generalizable, instead of hyper-specialized, AI methods.

MRI-Based Assessment of Brain Tumor Hypoxia: Correlation with Histology.

Cerebral hypoxia significantly impacts the progression of brain tumors and their resistance to radiotherapy. This study employed streamlined quantitative blood-oxygen-level-dependent (sqBOLD) MRI to assess the oxygen extraction fraction (OEF)-a measure of how much oxygen is being extracted from vessels, with higher OEF values indicating hypoxia. Simultaneously, we utilized vessel size imaging (VSI) to evaluate microvascular dimensions and blood volume. A cohort of ten patients, divided between those with glioma and those with brain metastases, underwent a 3 Tesla MRI scan. We generated OEF, cerebral blood volume (CBV), and vessel size maps, which guided 3-4 targeted biopsies per patient. Subsequent histological analyses of these biopsies used hypoxia-inducible factor 1-alpha (HIF-1α) for hypoxia and CD31 for microvasculature assessment, followed by a correlation analysis between MRI and histological data. The results showed that while the sqBOLD model was generally applicable to brain tumors, it demonstrated discrepancies in some metastatic tumors, highlighting the need for model adjustments in these cases. The OEF, CBV, and vessel size maps provided insights into the tumor's hypoxic condition, showing intertumoral and intratumoral heterogeneity. A significant relationship between MRI-derived measurements and histological data was only evident in the vessel size measurements (r = 0.68, p < 0.001).

Impact of dedicated neuro-anesthesia management on clinical outcomes in glioblastoma patients: A single-institution cohort study.

BACKGROUND: Glioblastomas are mostly resected under general anesthesia under the supervision of a general anesthesiologist. Currently, it is largely unkown if clinical outcomes of GBM patients can be improved by appointing a neuro-anesthesiologist for their cases. We aimed to evaluate whether the assignment of dedicated neuro-anesthesiologists improves the outcomes of these patients. We also investigated the value of dedicated neuro-oncological surgical teams as an independent variable in both groups. METHODS: A cohort consisting of 401 GBM patients who had undergone resection was retrospectively investigated. Primary outcomes were postoperative neurological complications, fluid balance, length-of-stay and overall survival. Secondary outcomes were blood loss, anesthesia modality, extent of resection, total admission costs, and duration of surgery. RESULTS: 320 versus 81 patients were operated under the anesthesiological supervision of a general anesthesiologist and a dedicated neuro-anesthesiologist, respectively. Dedicated neuro-anesthesiologists yielded significant superior outcomes in 1) postoperative neurological complications (early: p = 0.002, OR = 2.54; late: p = 0.003, OR = 2.24); 2) fluid balance (p<0.0001); 3) length-of-stay (p = 0.0006) and 4) total admission costs (p = 0.0006). In a subanalysis of the GBM resections performed by an oncological neurosurgeon (n = 231), the assignment of a dedicated neuro-anesthesiologist independently improved postoperative neurological complications (early minor: p = 0.0162; early major: p = 0.00780; late minor: p = 0.00250; late major: p = 0.0364). The assignment of a dedicated neuro-oncological team improved extent of resection additionally (p = 0.0416). CONCLUSION: GBM resections with anesthesiological supervision of a dedicated neuro-anesthesiologists are associated with improved patient outcomes. Prospective evidence is needed to further investigate the usefulness of the dedicated neuro-anesthesiologist in different settings.

High-resolution micro-Doppler imaging during neurosurgical resection of an arteriovenous malformation: illustrative case.

OBJECTIVE: Given the high-risk nature of arteriovenous malformation (AVM) resections, accurate pre- and intraoperative imaging of the vascular morphology is a crucial component that may contribute to successful surgical results. Surprisingly, current gold standard imaging techniques for surgical guidance of AVM resections are mostly preoperative, lacking the necessary flexibility to cater to intraoperative changes. Micro-Doppler imaging is a unique high-resolution technique relying on high frame rate ultrasound and subsequent Doppler processing of microvascular hemodynamics. In this paper the authors report the first application of intraoperative, coregistered magnetic resonance/computed tomograpy, micro-Doppler imaging during the neurosurgical resection of an AVM in the parietal lobe. OBSERVATIONS: The authors applied intraoperative two-dimensional and three-dimensional (3D) micro-Doppler imaging during resection and were able to identify key anatomical features including draining veins, supplying arteries and microvasculature in the nidus itself. Compared to the corresponding preoperative 3D-digital subtraction angiography (DSA) image, the micro-Doppler images could delineate vascular structures and visualize hemodynamics with higher, submillimeter scale detail, even at significant depths (>5 cm). Additionally, micro-Doppler imaging revealed unique microvascular morphology of surrounding healthy vasculature. LESSONS: The authors conclude that micro-Doppler imaging in its current form has clear potential as an intraoperative counterpart to preoperative contrast-dependent DSA, and the microvascular details it provides could build new ground to further study cerebrovascular pathophysiology.

Effect of awake craniotomy in glioblastoma in eloquent areas (GLIOMAP): a propensity score-matched analysis of an international, multicentre, cohort study.

BACKGROUND: Awake mapping has been associated with decreased neurological deficits and increased extent of resection in eloquent glioma resections. However, its effect within clinically relevant glioblastoma subgroups remains poorly understood. We aimed to assess the benefit of this technique in subgroups of patients with glioblastomas based on age, preoperative neurological morbidity, and Karnofsky Performance Score (KPS). METHODS: In this propensity score-matched analysis of an international, multicentre, cohort study (GLIOMAP), patients were recruited at four tertiary centres in Europe (Erasmus MC, Rotterdam and Haaglanden MC, The Hague, Netherlands, and UZ Leuven, Leuven, Belgium) and the USA (Brigham and Women's Hospital, Boston, MA). Patients were eligible if they were aged 18-90 years, undergoing resection, had a histopathological diagnosis of primary glioblastoma, their tumour was in an eloquent or near-eloquent location, and they had a unifocal enhancing lesion. Patients either underwent awake mapping during craniotomy, or asleep resection, as per treating physician or multidisciplinary tumour board decision. We used propensity-score matching (1:3) to match patients in the awake group with those in the asleep group to create a matched cohort, and to match patients from subgroups stratified by age (<70 years vs ≥70 years), preoperative National Institute of Health Stroke Scale (NIHSS) score (score of 0-1 vs ≥2), and preoperative KPS (90-100 vs ≤80). We used Cox proportional hazard regressions to analyse the effect of awake mapping on the primary outcomes including postoperative neurological deficits (measured by deterioration in NIHSS score at 6 week, 3 months, and 6 months postoperatively), overall survival, and progression-free survival. We used logistic regression to analyse the predictive value of awake mapping and other perioperative factors on postoperative outcomes. FINDINGS: Between Jan 1, 2010, and Oct 31, 2020, 3919 patients were recruited, of whom 1047 with tumour resection for primary eloquent glioblastoma were included in analyses as the overall unmatched cohort. After propensity-score matching, the overall matched cohort comprised 536 patients, of whom 134 had awake craniotomies and 402 had asleep resection. In the overall matched cohort, awake craniotomy versus asleep resection resulted in fewer neurological deficits at 3 months (26 [22%] of 120 vs 107 [33%] of 323; p=0·019) and 6 months (30 [26%] of 115 vs 125 [41%] of 305; p=0·0048) postoperatively, longer overall survival (median 17·0 months [95% CI 15·0-24·0] vs 14·0 months [13·0-16·0]; p=0·00054), and longer progression-free survival (median 9·0 months [8·0-11·0] vs 7·3 months [6·0-8·8]; p=0·0060). In subgroup analyses, fewer postoperative neurological deficits occurred at 3 months and at 6 months with awake craniotomy versus asleep resection in patients younger than 70 years (3 months: 22 [21%] of 103 vs 93 [34%] of 272; p=0·016; 6 months: 24 [24%] of 101 vs 108 [42%] of 258; p=0·0014), those with an NIHSS score of 0-1 (3 months: 22 [23%] of 96 vs 97 [38%] of 254; p=0·0071; 6 months: 27 [28%] of 95 vs 115 [48%] of 239; p=0·0010), and those with a KPS of 90-100 (3 months: 17 [19%] of 88 vs 74 [35%] of 237; p=0·034; 6 months: 24 [28%] of 87 vs 101 [45%] of 223, p=0·0043). Additionally, fewer postoperative neurological deficits were seen in the awake group versus the asleep group at 3 months in patients aged 70 years and older (two [13%] of 16 vs 15 [43%] of 35; p=0·033; no difference seen at 6 months), with a NIHSS score of 2 or higher (3 months: three [13%] of 23 vs 21 [36%] of 58; p=0·040) and at 6 months in those with a KPS of 80 or lower (five [18%] of 28 vs 34 [39%] of 88; p=0·043; no difference seen at 3 months). Median overall survival was longer for the awake group than the asleep group in the subgroups younger than 70 years (19·5 months [95% CI 16·0-31·0] vs 15·0 months [13·0-17·0]; p<0·0001), an NIHSS score of 0-1 (18·0 months [16·0-31·0] vs 14·0 months [13·0-16·5]; p=0·00047), and KPS of 90-100 (19·0 months [16·0-31·0] vs 14·5 months [13·0-16·5]; p=0·00058). Median progression-free survival was also longer in the awake group than in the asleep group in patients younger than 70 years (9·3 months [95% CI 8·0-12·0] vs 7·5 months [6·5-9·0]; p=0·0061), in those with an NIHSS score of 0-1 (9·5 months [9·0-12·0] vs 8·0 months [6·5-9·0]; p=0·0035), and in those with a KPS of 90-100 (10·0 months [9·0-13·0] vs 8·0 months [7·0-9·0]; p=0·0010). No difference was seen in overall survival or progression-free survival between the awake group and the asleep group for those aged 70 years and older, with NIHSS scores of 2 or higher, or with a KPS of 80 or lower. INTERPRETATION: These data might aid neurosurgeons with the assessment of their surgical strategy in individual glioblastoma patients. These findings will be validated and further explored in the SAFE trial (NCT03861299) and the PROGRAM study (NCT04708171). FUNDING: None.

Mapping tumour heterogeneity with pulsed 3D CEST MRI in non-enhancing glioma at 3 T.

OBJECTIVE: Amide proton transfer (APT) weighted chemical exchange saturation transfer (CEST) imaging is increasingly used to investigate high-grade, enhancing brain tumours. Non-enhancing glioma is currently less studied, but shows heterogeneous pathophysiology with subtypes having equally poor prognosis as enhancing glioma. Here, we investigate the use of CEST MRI to best differentiate non-enhancing glioma from healthy tissue and image tumour heterogeneity. MATERIALS & METHODS: A 3D pulsed CEST sequence was applied at 3 Tesla with whole tumour coverage and 31 off-resonance frequencies (+6 to -6 ppm) in 18 patients with non-enhancing glioma. Magnetisation transfer ratio asymmetry (MTRasym) and Lorentzian difference (LD) maps at 3.5 ppm were compared for differentiation of tumour versus normal appearing white matter. Heterogeneity was mapped by calculating volume percentages of the tumour showing hyperintense APT-weighted signal. RESULTS: LDamide gave greater effect sizes than MTRasym to differentiate non-enhancing glioma from normal appearing white matter. On average, 17.9 % ± 13.3 % (min-max: 2.4 %-54.5 %) of the tumour volume showed hyperintense LDamide in non-enhancing glioma. CONCLUSION: This works illustrates the need for whole tumour coverage to investigate heterogeneity in increased APT-weighted CEST signal in non-enhancing glioma. Future work should investigate whether targeting hyperintense LDamide regions for biopsies improves diagnosis of non-enhancing glioma.

Intraoperative B-Mode Ultrasound Guided Surgery and the Extent of Glioblastoma Resection: A Randomized Controlled Trial.

BACKGROUND: Intraoperative MRI and 5-aminolaevulinic acid guided surgery are useful to maximize the extent of glioblastoma resection. Intraoperative ultrasound is used as a time-and cost-effective alternative, but its value has never been assessed in a trial. The goal of this randomized controlled trial was to assess the value of intraoperative B-mode ultrasound guided surgery on the extent of glioblastoma resection. MATERIALS AND METHODS: In this randomized controlled trial, patients of 18 years or older with a newly diagnosed presumed glioblastoma, deemed totally resectable, presenting at the Erasmus MC (Rotterdam, The Netherlands) were enrolled and randomized (1:1) into intraoperative B-mode ultrasound guided surgery or resection under standard neuronavigation. The primary outcome of this study was complete contrast-enhancing tumor resection, assessed quantitatively by a blinded neuroradiologist on pre- and post-operative MRI scans. This trial was registered with ClinicalTrials.gov (NCT03531333). RESULTS: We enrolled 50 patients between November 1, 2016 and October 30, 2019. Analysis was done in 23 of 25 (92%) patients in the intraoperative B-mode ultrasound group and 24 of 25 (96%) patients in the standard surgery group. Eight (35%) of 23 patients in the intraoperative B-mode ultrasound group and two (8%) of 24 patients in the standard surgery group underwent complete resection (p=0.036). Baseline characteristics, neurological outcome, functional performance, quality of life, complication rates, overall survival and progression-free survival did not differ between treatment groups (p>0.05). CONCLUSIONS: Intraoperative B-mode ultrasound enables complete resection more often than standard surgery without harming patients and can be considered to maximize the extent of glioblastoma resection during surgery.

The Erasmus Glioma Database (EGD): Structural MRI scans, WHO 2016 subtypes, and segmentations of 774 patients with glioma.

The Erasmus Glioma Database (EGD) contains structural magnetic resonance imaging (MRI) scans, genetic and histological features (specifying the WHO 2016 subtype), and whole tumor segmentations of patients with glioma. Pre-operative MRI data of 774 patients with glioma (281 female, 492 male, 1 unknown, age range 19-86 years) treated at the Erasmus MC between 2008 and 2018 is available. For all patients a pre-contrast T1-weighted, post-contrast T1-weighted, T2-weighted, and T2-weighted FLAIR scan are available, made on a variety of scanners from four different vendors. All scans are registered to a common atlas and defaced. Genetic and histological data consists of the IDH mutation status (available for 467 patients), 1p/19q co-deletion status (available for 259 patients), and grade (available for 716 patients). The full WHO 2016 subtype is available for 415 patients. Manual segmentations are available for 374 patients and automatically generated segmentations are available for 400 patients. The dataset can be used to relate the visual appearance of the tumor on the scan with the genetic and histological features, and to develop automatic segmentation methods.

Unruptured Arteriovenous Malformations: Do We Have an Answer After the Final Follow-Up of ARUBA? A Bayesian Viewpoint.

Brain arteriovenous malformations (bAVMs) are vascular lesions that carry significant morbidity and mortality risk upon rupture. bAVM rupture causes either intracerebral or intraventricular hemorrhage, or both. In 2014, the first results of the ARUBA trial (A Randomized Trial of Unruptured Brain Arteriovenous Malformations) were published in The Lancet, causing a paradigm shift in clinical practice and suggesting the superiority of medical treatment in terms of mortality or stroke compared with any intervention designed to obliterate the AVM. In 2020, the final results of the ARUBA trial were published. In this Viewpoint, we critically review the clinical equipoise behind the trial, highlight issues regarding external validity, and place the results of the trial in the context of other results in scientific literature of bAVMs using Bayesian inference. ARUBA is a trial of decision-making, and only proper knowledge of the nuances of its interpretation within the broader context of bAVM research can lead to proper decision-making when confronted with patients with unruptured bAVMs.

Can Young Vascular Neurosurgeons Become Proficient in Microsurgical Clip Reconstruction in the Endovascular Era? A Rotterdam Cohort Spanning 2 Decades with Propensity Score Matching for Complexity.

BACKGROUND: Little is known about the results of young vascular neurosurgeons who perform only microsurgical clip reconstruction in the era since the International Subarachnoid Aneurysm Trial (ISAT) or about the training and caseload required to equivocate the results of senior, more experienced colleagues. The aim of this study was to compare clinical outcomes of patients treated by young and senior vascular neurosurgeons at Erasmus MC University Medical Center Rotterdam, adjusting for case mix. METHODS: A partially prospective and partially retrospective database was used. Hierarchical mixed models with a random intercept for surgeon were used for confounder adjustment, and propensity score matching for complexity was used to create comparable groups. RESULTS: The study included 609 patients harboring 767 aneurysms. Most (86%) of the aneurysms had at least 1 complexity characteristic, with the majority having 3 characteristics. The most often encountered complexity characteristics were the presence of a broad neck and the presence of branches emerging from the aneurysm. Use of temporary clipping and skull base approaches was significantly higher in the young vascular neurosurgeons group (P < 0.0001). The complexity score differed significantly between senior and young vascular neurosurgeons (P < 0.001). After propensity score matching for complexity, multivariable logistic regression showed young vascular neurosurgeons to be significantly associated with better outcomes for ruptured aneurysms (propensity score weighted odds ratio 0.55 [95% confidence interval 0.35-0.88], P = 0.01). CONCLUSIONS: In a high-volume neurovascular center where both endovascular and microsurgical treatment options are available, young vascular neurosurgeons can be trained to achieve at least the same results as their senior colleagues despite increased complexity.

Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm.

PURPOSE: Patients with 1p/19q codeleted low-grade glioma (LGG) have longer overall survival and better treatment response than patients with 1p/19q intact tumors. Therefore, it is relevant to know the 1p/19q status. To investigate whether the 1p/19q status can be assessed prior to tumor resection, we developed a machine learning algorithm to predict the 1p/19q status of presumed LGG based on preoperative MRI. EXPERIMENTAL DESIGN: Preoperative brain MR images from 284 patients who had undergone biopsy or resection of presumed LGG were used to train a support vector machine algorithm. The algorithm was trained on the basis of features extracted from post-contrast T1-weighted and T2-weighted MR images and on patients' age and sex. The performance of the algorithm compared with tissue diagnosis was assessed on an external validation dataset of MR images from 129 patients with LGG from The Cancer Imaging Archive (TCIA). Four clinical experts also predicted the 1p/19q status of the TCIA MR images. RESULTS: The algorithm achieved an AUC of 0.72 in the external validation dataset. The algorithm had a higher predictive performance than the average of the neurosurgeons (AUC 0.52) but lower than that of the neuroradiologists (AUC of 0.81). There was a wide variability between clinical experts (AUC 0.45-0.83). CONCLUSIONS: Our results suggest that our algorithm can noninvasively predict the 1p/19q status of presumed LGG with a performance that on average outperformed the oncological neurosurgeons. Evaluation on an independent dataset indicates that our algorithm is robust and generalizable.