Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks.

Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of residual tumor from post-operative MR images is essential. The current standard method for estimating it is subject to high inter- and intra-rater variability, and an automated method for segmentation of residual tumor in early post-operative MRI could lead to a more accurate estimation of extent of resection. In this study, two state-of-the-art neural network architectures for pre-operative segmentation were trained for the task. The models were extensively validated on a multicenter dataset with nearly 1000 patients, from 12 hospitals in Europe and the United States. The best performance achieved was a 61% Dice score, and the best classification performance was about 80% balanced accuracy, with a demonstrated ability to generalize across hospitals. In addition, the segmentation performance of the best models was on par with human expert raters. The predicted segmentations can be used to accurately classify the patients into those with residual tumor, and those with gross total resection.

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVIDIA-net (nv-Net) were trained and tested using manual segmentations from preoperative MRI of glioblastoma (GBM) and low-grade gliomas (LGG) from the BraTS 2021 dataset (1251 in total), in addition to 275 GBM and 205 LGG acquired clinically across 12 hospitals worldwide. Data was split into 80% training, 5% validation, and 15% internal test data. An additional external test-set of 158 GBM and 69 LGG was used to assess generalisability to other hospitals' data. All models' median Dice similarity coefficient (DSC) for both test sets were within, or higher than, previously reported human inter-rater agreement (range of 0.74-0.85). For both test sets, nn-Unet achieved the highest DSC (internal = 0.86, external = 0.93) and the lowest Hausdorff distances (10.07, 13.87 mm, respectively) for all tumor classes (p < 0.001). By applying Sparsified training, missing MRI sequences did not statistically affect the performance. nn-Unet achieves accurate segmentations in clinical settings even in the presence of incomplete MRI datasets. This facilitates future clinical adoption of automated glioma segmentation, which could help inform treatment planning and glioma monitoring.

Work-related experiences and unmet needs of patients with a malignant glioma and relevant professionals: the BrainWork study.

PURPOSE: Many patients with a malignant (i.e., grade II-IV) glioma are of working age, yet they are rarely included in "cancer and work" studies. Here, we explored (1) the work-related experiences and unmet needs of patients with a malignant glioma and (2) the experiences and needs of relevant healthcare and occupational (health) professionals ("professionals") in providing work-related support to this patient group. METHODS: Individual semi-structured interviews were held with patients with a malignant glioma who were of working age and had an employment contract at diagnosis, and relevant professionals. Interviews were transcribed verbatim and analysed thematically. RESULTS: Patients (n = 22) were on average 46 ± 13 years of age (64% male) and diagnosed with a grade II (n = 12), III (n = 4), or IV glioma (n = 6). Professionals (n = 16) had on average 15 ± 9 years of relevant work experience with the patient group. Four themes emerged from the data: (1) having a malignant glioma: experienced consequences on work ability, (2) communicating about the consequences of a malignant glioma at work, (3) distilling the right approach: generic or tailored work-related support, and (4) accessibility of work-related support. CONCLUSIONS: Glioma-specific consequences on patients' work ability necessitate better communication between, and tailored guidance for, patients, relevant professionals, and the workplace. Suggestions for improvement, e.g., the periodic use of comprehensive neuropsychological assessments, are provided in the article. IMPLICATIONS FOR CANCER SURVIVORS: Patients with a malignant glioma would benefit from tailored and proactive outreach about work-related issues bv relevant professionals.

Preoperative Brain Tumor Imaging: Models and Software for Segmentation and Standardized Reporting.

For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports.

Between-hospital variation in time to glioblastoma surgery: a report from the Quality Registry Neuro Surgery in the Netherlands.

OBJECTIVE: Patients with glioblastoma are often scheduled for urgent elective surgery. Currently, the impact of the waiting period until glioblastoma surgery is undetermined. In this national quality registry study, the authors determined the wait times until surgery for patients with glioblastoma, the risk factors associated with wait times, and the risk-standardized variation in time to surgery between Dutch hospitals. The associations between time to surgery and patient outcomes were also explored. METHODS: Data from all 4589 patients who underwent first-time glioblastoma surgery between 2014 and 2019 in the Netherlands were collected by 13 hospitals in the Quality Registry Neuro Surgery. Time to surgery comprised 1) the time from first MR scan to surgery (MTS), and 2) the time from first neurosurgical consultation to surgery (CTS). Long MTS was defined as more than 21 days and long CTS as more than 14 days. Potential risk factors were analyzed in multivariable logistic regression models. The standardized rate of long time to surgery was analyzed using funnel plots. Patient outcomes including Karnofsky Performance Scale (KPS) score change, complications, and survival were analyzed by multivariable logistic regression and proportional hazards models. RESULTS: The median overall MTS and CTS were 18 and 9 days, respectively. Overall, 2576 patients (56%) had an MTS within 3 weeks and 3069 (67%) had a CTS within 2 weeks. Long MTS was significantly associated with older age, higher preoperative KPS score, higher American Society of Anesthesiologists comorbidity class, season, lower hospital case volume, university affiliation, and resection. Long CTS was significantly associated with higher baseline KPS score, university affiliation, resection, more recent year of treatment, and season. In funnel plots, considerable practice variation was observed between hospitals in patients with long times to surgery. Fewer patients with KPS score improvement were observed after a long time until resection. Long CTS was associated with longer survival. Complications and KPS score decline were not associated with time to surgery. CONCLUSIONS: Considerable between-hospital variation among Dutch hospitals was observed in the time to glioblastoma surgery. A long time to resection impeded KPS score improvement, and therefore, patients who may improve should be identified for more urgent resection. Longer survival was observed in patients selected for longer time until surgery after neurosurgical consultation (CTS).

On the cutting edge of glioblastoma surgery: where neurosurgeons agree and disagree on surgical decisions.

OBJECTIVE: The aim of glioblastoma surgery is to maximize the extent of resection while preserving functional integrity. Standards are lacking for surgical decision-making, and previous studies indicate treatment variations. These shortcomings reflect the need to evaluate larger populations from different care teams. In this study, the authors used probability maps to quantify and compare surgical decision-making throughout the brain by 12 neurosurgical teams for patients with glioblastoma. METHODS: The study included all adult patients who underwent first-time glioblastoma surgery in 2012-2013 and were treated by 1 of the 12 participating neurosurgical teams. Voxel-wise probability maps of tumor location, biopsy, and resection were constructed for each team to identify and compare patient treatment variations. Brain regions with different biopsy and resection results between teams were identified and analyzed for patient functional outcome and survival. RESULTS: The study cohort consisted of 1087 patients, of whom 363 underwent a biopsy and 724 a resection. Biopsy and resection decisions were generally comparable between teams, providing benchmarks for probability maps of resections and biopsies for glioblastoma. Differences in biopsy rates were identified for the right superior frontal gyrus and indicated variation in biopsy decisions. Differences in resection rates were identified for the left superior parietal lobule, indicating variations in resection decisions. CONCLUSIONS: Probability maps of glioblastoma surgery enabled capture of clinical practice decisions and indicated that teams generally agreed on which region to biopsy or to resect. However, treatment variations reflecting clinical dilemmas were observed and pinpointed by using the probability maps, which could therefore be useful for quality-of-care discussions between surgical teams for patients with glioblastoma.

Glioblastoma Surgery Imaging-Reporting and Data System: Validation and Performance of the Automated Segmentation Task.

For patients with presumed glioblastoma, essential tumor characteristics are determined from preoperative MR images to optimize the treatment strategy. This procedure is time-consuming and subjective, if performed by crude eyeballing or manually. The standardized GSI-RADS aims to provide neurosurgeons with automatic tumor segmentations to extract tumor features rapidly and objectively. In this study, we improved automatic tumor segmentation and compared the agreement with manual raters, describe the technical details of the different components of GSI-RADS, and determined their speed. Two recent neural network architectures were considered for the segmentation task: nnU-Net and AGU-Net. Two preprocessing schemes were introduced to investigate the tradeoff between performance and processing speed. A summarized description of the tumor feature extraction and standardized reporting process is included. The trained architectures for automatic segmentation and the code for computing the standardized report are distributed as open-source and as open-access software. Validation studies were performed on a dataset of 1594 gadolinium-enhanced T1-weighted MRI volumes from 13 hospitals and 293 T1-weighted MRI volumes from the BraTS challenge. The glioblastoma tumor core segmentation reached a Dice score slightly below 90%, a patientwise F1-score close to 99%, and a 95th percentile Hausdorff distance slightly below 4.0 mm on average with either architecture and the heavy preprocessing scheme. A patient MRI volume can be segmented in less than one minute, and a standardized report can be generated in up to five minutes. The proposed GSI-RADS software showed robust performance on a large collection of MRI volumes from various hospitals and generated results within a reasonable runtime.

Glioblastoma Surgery Imaging-Reporting and Data System: Standardized Reporting of Tumor Volume, Location, and Resectability Based on Automated Segmentations.

Treatment decisions for patients with presumed glioblastoma are based on tumor characteristics available from a preoperative MR scan. Tumor characteristics, including volume, location, and resectability, are often estimated or manually delineated. This process is time consuming and subjective. Hence, comparison across cohorts, trials, or registries are subject to assessment bias. In this study, we propose a standardized Glioblastoma Surgery Imaging Reporting and Data System (GSI-RADS) based on an automated method of tumor segmentation that provides standard reports on tumor features that are potentially relevant for glioblastoma surgery. As clinical validation, we determine the agreement in extracted tumor features between the automated method and the current standard of manual segmentations from routine clinical MR scans before treatment. In an observational consecutive cohort of 1596 adult patients with a first time surgery of a glioblastoma from 13 institutions, we segmented gadolinium-enhanced tumor parts both by a human rater and by an automated algorithm. Tumor features were extracted from segmentations of both methods and compared to assess differences, concordance, and equivalence. The laterality, contralateral infiltration, and the laterality indices were in excellent agreement. The native and normalized tumor volumes had excellent agreement, consistency, and equivalence. Multifocality, but not the number of foci, had good agreement and equivalence. The location profiles of cortical and subcortical structures were in excellent agreement. The expected residual tumor volumes and resectability indices had excellent agreement, consistency, and equivalence. Tumor probability maps were in good agreement. In conclusion, automated segmentations are in excellent agreement with manual segmentations and practically equivalent regarding tumor features that are potentially relevant for neurosurgical purposes. Standard GSI-RADS reports can be generated by open access software.

Timing of glioblastoma surgery and patient outcomes: a multicenter cohort study.

BACKGROUND: The impact of time-to-surgery on clinical outcome for patients with glioblastoma has not been determined. Any delay in treatment is perceived as detrimental, but guidelines do not specify acceptable timings. In this study, we relate the time to glioblastoma surgery with the extent of resection and residual tumor volume, performance change, and survival, and we explore the identification of patients for urgent surgery. METHODS: Adults with first-time surgery in 2012-2013 treated by 12 neuro-oncological teams were included in this study. We defined time-to-surgery as the number of days between the diagnostic MR scan and surgery. The relation between time-to-surgery and patient and tumor characteristics was explored in time-to-event analysis and proportional hazard models. Outcome according to time-to-surgery was analyzed by volumetric measurements, changes in performance status, and survival analysis with patient and tumor characteristics as modifiers. RESULTS: Included were 1033 patients of whom 729 had a resection and 304 a biopsy. The overall median time-to-surgery was 13 days. Surgery was within 3 days for 235 (23%) patients, and within a month for 889 (86%). The median volumetric doubling time was 22 days. Lower performance status (hazard ratio [HR] 0.942, 95% confidence interval [CI] 0.893-0.994) and larger tumor volume (HR 1.012, 95% CI 1.010-1.014) were independently associated with a shorter time-to-surgery. Extent of resection, residual tumor volume, postoperative performance change, and overall survival were not associated with time-to-surgery. CONCLUSIONS: With current decision-making for urgent surgery in selected patients with glioblastoma and surgery typically within 1 month, we found equal extent of resection, residual tumor volume, performance status, and survival after longer times-to-surgery.

Between-hospital variation in rates of complications and decline of patient performance after glioblastoma surgery in the dutch Quality Registry Neuro Surgery.

INTRODUCTION: For decisions on glioblastoma surgery, the risk of complications and decline in performance is decisive. In this study, we determine the rate of complications and performance decline after resections and biopsies in a national quality registry, their risk factors and the risk-standardized variation between institutions. METHODS: Data from all 3288 adults with first-time glioblastoma surgery at 13 hospitals were obtained from a prospective population-based Quality Registry Neuro Surgery in the Netherlands between 2013 and 2017. Patients were stratified by biopsies and resections. Complications were categorized as Clavien-Dindo grades II and higher. Performance decline was considered a deterioration of more than 10 Karnofsky points at 6 weeks. Risk factors were evaluated in multivariable logistic regression analysis. Patient-specific expected and observed complications and performance declines were summarized for institutions and analyzed in funnel plots. RESULTS: For 2271 resections, the overall complication rate was 20 % and 16 % declined in performance. For 1017 biopsies, the overall complication rate was 11 % and 30 % declined in performance. Patient-related characteristics were significant risk factors for complications and performance decline, i.e. higher age, lower baseline Karnofsky, higher ASA classification, and the surgical procedure. Hospital characteristics, i.e. case volume, university affiliation and biopsy percentage, were not. In three institutes the observed complication rate was significantly less than expected. In one institute significantly more performance declines were observed than expected, and in one institute significantly less. CONCLUSIONS: Patient characteristics, but not case volume, were risk factors for complications and performance decline after glioblastoma surgery. After risk-standardization, hospitals varied in complications and performance declines.

Stereotactic cyst aspiration directly followed by Gamma Knife radiosurgery for large cystic brain metastases.

BACKGROUND: Gamma Knife radiosurgery (GKRS) has been proven to be a successful primary treatment for metastatic brain tumors (BM). BM can come in cystic lesions and are often too large for GKRS. An alternative approach to treat cystic BM is stereotactic cyst aspiration (SCA) for volume reduction, making it suitable for GKRS afterwards. OBJECTIVE: Our objective is evaluation of volumetric reduction after SCA, tumor control, and complications after SCA directly followed by GKRS. METHODS: We performed a retrospective analysis of all patients who underwent SCA directly followed by GKRS at the Gamma Knife Center of the Elisabeth-Tweesteden Hospital in Tilburg between 2002 and 2015. In total, 54 patients had undergone this combined approach. Two patients were excluded because of prior intracranial treatment. The other 52 patients were included for analysis. RESULTS: SCA resulted in a mean volumetric reduction of 56.5% (range 5.50-87.00%). In 83.6% of the tumors (46 tumors), SCA led to sufficient volumetric reduction making GKRS possible. The overall local tumor control (OLTC) of the aspirated lesions post-GKRS was 60.9% (28 out of 46 tumors). Median progression-free survival (PFS) and overall survival (OS) for all patients were 3 (range 5 days-14 months) and 12 months (range 5 days-58 months), respectively. Leptomeningeal disease was reported in 5 (9.6%) cases. CONCLUSION: SCA directly followed by GKRS is an effective and time-efficient treatment for large cystic BM in selected patients in which surgery is contraindicated and those with deeply located lesions.

Quantifying eloquent locations for glioblastoma surgery using resection probability maps.

OBJECTIVE: Decisions in glioblastoma surgery are often guided by presumed eloquence of the tumor location. The authors introduce the "expected residual tumor volume" (eRV) and the "expected resectability index" (eRI) based on previous decisions aggregated in resection probability maps. The diagnostic accuracy of eRV and eRI to predict biopsy decisions, resectability, functional outcome, and survival was determined. METHODS: Consecutive patients with first-time glioblastoma surgery in 2012-2013 were included from 12 hospitals. The eRV was calculated from the preoperative MR images of each patient using a resection probability map, and the eRI was derived from the tumor volume. As reference, Sawaya's tumor location eloquence grades (EGs) were classified. Resectability was measured as observed extent of resection (EOR) and residual volume, and functional outcome as change in Karnofsky Performance Scale score. Receiver operating characteristic curves and multivariable logistic regression were applied. RESULTS: Of 915 patients, 674 (74%) underwent a resection with a median EOR of 97%, functional improvement in 71 (8%), functional decline in 78 (9%), and median survival of 12.8 months. The eRI and eRV identified biopsies and EORs of at least 80%, 90%, or 98% better than EG. The eRV and eRI predicted observed residual volumes under 10, 5, and 1 ml better than EG. The eRV, eRI, and EG had low diagnostic accuracy for functional outcome changes. Higher eRV and lower eRI were strongly associated with shorter survival, independent of known prognostic factors. CONCLUSIONS: The eRV and eRI predict biopsy decisions, resectability, and survival better than eloquence grading and may be useful preoperative indices to support surgical decisions.

Between-hospital variation in mortality and survival after glioblastoma surgery in the Dutch Quality Registry for Neuro Surgery.

PURPOSE: Standards for surgical decisions are unavailable, hence treatment decisions can be personalized, but also introduce variation in treatment and outcome. National registrations seek to monitor healthcare quality. The goal of the study is to measure between-hospital variation in risk-standardized survival outcome after glioblastoma surgery and to explore the association between survival and hospital characteristics in conjunction with patient-related risk factors. METHODS: Data of 2,409 adults with first-time glioblastoma surgery at 14 hospitals were obtained from a comprehensive, prospective population-based Quality Registry Neuro Surgery in The Netherlands between 2011 and 2014. We compared the observed survival with patient-specific risk-standardized expected early (30-day) mortality and late (2-year) survival, based on age, performance, and treatment year. We analyzed funnel plots, logistic regression and proportional hazards models. RESULTS: Overall 30-day mortality was 5.2% and overall 2-year survival was 13.5%. Median survival varied between 4.8 and 14.9 months among hospitals, and biopsy percentages ranged between 16 and 73%. One hospital had lower than expected early mortality, and four hospitals had lower than expected late survival. Higher case volume was related with lower early mortality (P = 0.031). Patient-related risk factors (lower age; better performance; more recent years of treatment) were significantly associated with longer overall survival. Of the hospital characteristics, longer overall survival was associated with lower biopsy percentage (HR 2.09, 1.34-3.26, P = 0.001), and not with academic setting, nor with case volume. CONCLUSIONS: Hospitals vary more in late survival than early mortality after glioblastoma surgery. Widely varying biopsy percentages indicate treatment variation. Patient-related factors have a stronger association with overall survival than hospital-related factors.

Comparative Effectiveness of Surgery for Traumatic Acute Subdural Hematoma in an Aging Population.

There is uncertainty as to the optimal initial management of patients with traumatic acute subdural hematoma, leading to regional variation in surgical policy. This can be exploited to compare the effect of various management strategies and determine best practices. This article reports such a comparative effectiveness analysis of a retrospective observational cohort of traumatic acute subdural hematoma patients in two geographically distinct neurosurgical departments chosen for their - a-priori defined - diverging treatment preferences. Region A favored a strategy focused on surgical hematoma evacuation, whereas region B employed a more conservative approach, performing primary surgery less often. Region was used as a proxy for preferred treatment strategy to compare outcomes between groups, adjusted for potential confounders using multivariable logistic regression with imputation of missing data. In total, 190 patients were included: 108 from region A and 82 from region B. There were 104 males (54.7%). Matching current epidemiological developments, the median age was relatively high at 68 years (interquartile range [IQR], 54-76). Baseline characteristics were comparable between regions. Primary evacuation was performed in 84% of patients in region A and in 65% of patients in region B (p < 0.01). Mortality was lower in region A (37% vs. 45%, p = 0.29), as was unfavorable outcome (53% vs. 62%, p = 0.23). The strategy favoring surgical evacuation was associated with significantly lower odds of mortality (odds ratio [OR]: 0.43; 95% confidence interval [CI]: 0.21-0.88) and unfavorable outcome (OR: 0.53; 95% CI: 0.27-1.02) 3-9 months post-injury. Therefore, in the aging population of patients with acute subdural hematoma, a treatment strategy favoring emergency hematoma evacuation might be associated with lower odds of mortality and unfavorable outcome.

Gamma knife radiosurgery for recurrent gliomas.

OBJECTIVE: In recent years, gamma knife radiosurgery (GKRS) has become increasingly more popular as a salvage treatment modality for patients diagnosed with recurrent gliomas. The goal of GKRS for recurrent glioma patients is to improve survival rates with minimal burden for these patients. The emphasis of this report is on local tumor control (TC), clinical outcome and survival analysis. METHODS: We performed a retrospective analysis of prospectively collected data of all patients who underwent GKRS for gliomas at the Gamma Knife Center Tilburg between 23-09-2002 and 21-05-2015. In total, 94 patients with glioma were treated with GKRS. Two patients were excluded because GKRS was used as a first stage treatment. The other 92 patients were included for analysis. RESULTS: TC was 37% for all tumors (TC was 50% in LGGs and 27% in HGGs). Local progression (LP) was 46% for all tumors (LP was 31% in LGGs and 58% in HGGs). New distant lesions were seen in 18% of all patients (in 5% of LGG patients and 31% of HGG patients). Median progression-free and overall survival (PFS and OS) for all patients were 10.5 and 34.4 months, respectively. Median PFS was 50.1 and 5.7 months for low and high grade tumors, respectively. Median OS was 86.6 and 12.8 months for low and high grade tumors, respectively. No serious adverse events were noted post-GKRS. CONCLUSION: GKRS can safely be used as salvage treatment for recurrent glioma and seems to improve survival rates in (high grade) glioma patients with minimal burden.

Aquaporin-4 in glioma and metastatic tissues harboring 5-aminolevulinic acid-induced porphyrin fluorescence.

INTRODUCTION: Aquaporin channels (AQPs) are a group of integral membrane proteins that regulate the transport of water through cell membranes. Previous studies have shown that up-regulation of AQP1 and AQP4, two of the predominant AQPs in the human brain, in high grade glial tumors contribute to cerebral edema. Others link AQPs to the regulation of human glioma cell migration and invasion. The aim of this study was to determine AQPs expression in tumor tissue harboring 5-aminolevulinic acid (ALA)-induced porphyrin fluorescence with flow cytometry and compare it to the expression in normal brain tissue. METHODS: Tissue samples were obtained from fluorescing brain tumors of 26 patients treated with ALA prior to surgery (20 mg/kg b.w.). Expression levels of aquaporin channels were measured in primary tissue cultures using a FACS CANTO I flow cytometer. A control group consisted of four non-fluorescing tissue samples, the C6 and the U87 cell line. RESULTS: Nineteen gliomas (14 high grade, 5 low grade) and 7 metastases were analyzed. On the 4th post-operative day, expression levels of AQP4 channels, but not of AQP1 channels, were significantly increased in samples from fluorescing tissue compared to non-fluorescing tissue. In addition we could see how ALA induces fluorescence in metastases. CONCLUSION: Flow cytometry appears to be an auspicious method for the analysis of porphyrins and AQPs in primary brain cell tumor cultures. ALA fluorescing tissue showed higher AQP4 expression compared to normal brain tissue. The demonstrated expression in a context with ALA could open a targeted therapeutic spectrum, for example to selectively target AQP4.

Stratification according to HGG-IMMUNO RPA model predicts outcome in a large group of patients with relapsed malignant glioma treated by adjuvant postoperative dendritic cell vaccination.

PURPOSE: Adult patients with relapsed high-grade glioma are a very heterogenous group with, however, an invariably dismal prognosis. We stratified patients with relapsed high-grade glioma treated with re-operation and postoperative dendritic cell (DC) vaccination according to a simple recursive partitioning analysis (RPA) model to predict outcome. PATIENTS AND METHODS: Based on age, pathology, Karnofsky performance score, and mental status, 117 adult patients with relapsed malignant glioma, undergoing re-operation, and postoperative adjuvant dendritic cell (DC) vaccination were stratified into 4 classes. Kaplan-Meier survival estimates were generated for each class of this HGG-IMMUNO RPA model. Extent of resection was documented but not included in the prognostic model. RESULTS: Kaplan-Meier overall survival estimates revealed significant (p < 0.0001) differences among the 4 HGG-IMMUNO RPA classes. Long-term survivors, surviving more than 24 months after the re-operation and vaccination, are seen in 54.5, 26.7, 11.5, and 0 % for the classes I, II, III, and IV respectively. CONCLUSION: This HGG-IMMUNO RPA classification is able to predict overall survival in a large group of adult patients with a relapsed malignant glioma, treated with re-operation and postoperative adjuvant DC vaccination in the HGG-IMMUNO-2003 cohort comparison trial. The model appears useful for prognostic patient counseling for patients participating in DC vaccination trials. A substantial number of long-term survivors after relapse are seen in class I to III, but not in class IV patients.

Integration of autologous dendritic cell-based immunotherapy in the standard of care treatment for patients with newly diagnosed glioblastoma: results of the HGG-2006 phase I/II trial.

PURPOSE: Dendritic cell (DC)-based tumor vaccination has rendered promising results in relapsed high-grade glioma patients. In the HGG-2006 trial (EudraCT 2006-002881-20), feasibility, toxicity, and clinical efficacy of the full integration of DC-based tumor vaccination into standard postoperative radiochemotherapy are studied in 77 patients with newly diagnosed glioblastoma. PATIENTS AND METHODS: Autologous DC are generated after leukapheresis, which is performed before the start of radiochemotherapy. Four weekly induction vaccines are administered after the 6-week course of concomitant radiochemotherapy. During maintenance chemotherapy, 4 boost vaccines are given. Feasibility and progression-free survival (PFS) at 6 months (6mo-PFS) are the primary end points. Overall survival (OS) and immune profiling, rather than monitoring, as assessed in patients' blood samples, are the secondary end points. Analysis has been done on intent-to-treat basis. RESULTS: The treatment was feasible without major toxicity. The 6mo-PFS was 70.1 % from inclusion. Median OS was 18.3 months. Outcome improved significantly with lower EORTC RPA classification. Median OS was 39.7, 18.3, and 10.7 months for RPA classes III, IV, and V, respectively. Patients with a methylated MGMT promoter had significantly better PFS (p = 0.0027) and OS (p = 0.0082) as compared to patients with an unmethylated status. Exploratory "immunological profiles" were built to compare to clinical outcome, but no statistical significant evidence was found for these profiles to predict clinical outcome. CONCLUSION: Full integration of autologous DC-based tumor vaccination into standard postoperative radiochemotherapy for newly diagnosed glioblastoma seems safe and possibly beneficial. These results were used to power the currently running phase IIb randomized clinical trial.

Paraganglioma of the cauda equina region: A report of three cases.

BACKGROUND: Cauda equina paragangliomas (CEP) are rare tumors. Low back pain and sciatica are the main presenting symptoms. Magnetic resonance imaging (MRI) is the study of choice and treatment consists of total excision when feasible. Definitive diagnosis can only be made after immunohistochemical investigation. CEP is classified as grade I WHO and after total removal the prognosis is excellent. Nonetheless, after subtotal removal, tumor recurrence can occur. CASE DESCRIPTION: We present 3 cases of CEP, preoperatively diagnosed as an intradural mass on MRI and suspected to be ependymoma. All 3 patients presented with low back pain and variable sciatic pain. Total resection of the tumor was performed after which all patients fully recovered. There is no recurrence after 13, 11, and 5 years, respectively. CONCLUSION: CEP is a rare tumor. We diagnosed 3 paragangliomas out of a series of 105 intradural extramedullary tumors in adults (1994-2005). No recurrence was seen after total resection. In retrospect, both the intraoperative appearance and the MR image were not completely typical for schwannoma or ependymoma, but final diagnosis can only be made histologically.

Integration of autologous dendritic cell-based immunotherapy in the primary treatment for patients with newly diagnosed glioblastoma multiforme: a pilot study.

Despite resection, radiochemotherapy, and maintenance temozolomide chemotherapy (TMZm), the prognosis of patients with glioblastoma multiforme (GBM) remains poor. We integrated immunotherapy in the primary standard treatment for eight pilot adult patients (median age 50 years) with GBM, to assess clinical and immunological feasibility and toxicity in preparation of a phase I/II protocol HGG-2006. After maximum, safe resection, leukapheresis was performed before radiochemotherapy, and four weekly vaccinations with autologous GBM lysate-loaded monocyte-derived dendritic cells were given after radiochemotherapy. Boost vaccines with lysates were given during TMZm. During the course of vaccination, immunophenotyping showed a relative increase in CD8+CD25+ cells in six of the seven patients, complying with the prerequisites for implementation of immunotherapy in addition to postoperative radiochemotherapy. In five patients, a more than twofold increase in tumor antigen-reacting IFN-gamma-producing T cells on Elispot was seen at the fourth vaccination compared with before vaccination. In three of these five patients this more than twofold increase persisted after three cycles of TMZm. Quality of life during vaccination remained excellent. Progression-free survival at six months was 75%. Median overall survival for all patients was 24 months (range: 13-44 months). The only serious adverse event was an ischemic stroke eight months postoperatively. We conclude that tumor vaccination, fully integrated within the standard primary postoperative treatment for patients with newly diagnosed GBM, is feasible and well tolerated. The survival data were used to power a currently running phase I/II trial.