Multi-center study finds postoperative residual non-enhancing component of glioblastoma as a new determinant of patient outcome

Radio-pathomic estimates of cellular growth kinetics predict survival in recurrent glioblastoma

Aim: A radio-pathomic machine learning (ML) model has been developed to estimate tumor cell density, cytoplasm density (Cyt) and extracellular fluid density (ECF) from multimodal MR images and autopsy pathology. In this multicenter study, we implemented this model to test its ability to predict survival in patients with recurrent glioblastoma (rGBM) treated with chemotherapy.Methods: Pre- and post-contrast T1-weighted, FLAIR and ADC images were used to generate radio-pathomic maps for 51 patients with longitudinal pre- and post-treatment scans. Univariate and multivariate Cox regression analyses were used to test the influence of contrast-enhancing tumor volume, total cellularity, mean Cyt and mean ECF at baseline, immediately post-treatment and the pre- and post-treatment rate of change in volume and cellularity on overall survival (OS).Results: Smaller Cyt and larger ECF after treatment were significant predictors of OS, independent of tumor volume and other clinical prognostic factors (HR = 3.23 × 10-6, p < 0.001 and HR = 2.39 × 105, p < 0.001, respectively). Both post-treatment volumetric growth rate and the rate of change in cellularity were significantly correlated with OS (HR = 1.17, p = 0.003 and HR = 1.14, p = 0.01, respectively).Conclusion: Changes in histological characteristics estimated from a radio-pathomic ML model are a promising tool for evaluating treatment response and predicting outcome in rGBM.

Do clinical outcomes in individuals with malignant gliomas differ between sexes?

Introduction

Sex-related differences in the epidemiology of malignant gliomas are acknowledged; however, information regarding their clinical characteristics and outcomes after surgery is limited.

Research question

To identify sex-specific differences of all patients with high-grade glioma at our institution and assessed clinical outcomes and prognostic factors.

Material and methods

This single-center study included those who underwent surgery for malignant gliomas between 2010 and 2020. Categorical, normally distributed, and skewed continuous variables were compared between men and women using the chi-square test, independent samples t-test, and Mann-Whitney U test, respectively. Survival was calculated using the log-rank and Kaplan-Meier methods.

Results

In total, 621 patients with WHO grade IV gliomas were identified (370 (59.58%) male). Men were significantly younger, underwent surgery faster after imaging diagnosis, and had a slightly higher surgical complications incidence than women. Women reported a worse preoperative performance status. Multivariate analysis showed that sex did not affect survival, surgical complications, nicotine or alcohol abuse, or preoperative tumor volume. Age, Karnofsky performance status, neurosurgical resection, and adjuvant radiotherapy with temozolomide showed a survival advantage.

Discussion and conclusions

Men are diagnosed with malignant glioma at a younger age than women; however, no advantage in clinical outcomes was observed. No sex-related differences were observed.

Magnetic resonance imaging (MRI)-based intratumoral and peritumoral radiomics for prognosis prediction in glioma patients

AIM

The purpose of this study was to identify robust radiological features from intratumoral and peritumoral regions, evaluate MRI protocols, and machine learning methods for overall survival stratification of glioma patients, and explore the relationship between radiological features and the tumour microenvironment.

MATERIAL AND METHODS

A retrospective analysis was conducted on 163 glioma patients, divided into a training set (n=113) and a testing set (n=50). For each patient, 2135 features were extracted from clinical MRI. Feature selection was performed using the Minimum Redundancy Maximum Relevance method and the Random Forest (RF) algorithm. Prognostic factors were assessed using the Cox proportional hazards model. Four machine learning models (RF, Logistic Regression, Support Vector Machine, and XGBoost) were trained on clinical and radiological features from tumour and peritumoral regions. Model evaluations on the testing set used receiver operating characteristic curves.

RESULTS

Among the 163 patients, 96 had an overall survival (OS) of less than three years postsurgery, while 67 had an OS of more than three years. Univariate Cox regression in the validation set indicated that age (p=0.003) and tumour grade (p<0.001) were positively associated with the risk of death within three years postsurgery. The final predictive model incorporated 13 radiological and 7 clinical features. The RF model, combining intratumor and peritumor radiomics, achieved the best predictive performance (AUC = 0.91; ACC = 0.86), outperforming single-region models.

CONCLUSION

Combined intratumoral and peritumoral radiomics can improve survival prediction and have potential as a practical imaging biomarker to guide clinical decision-making.

Advanced magnetic resonance imaging for glioblastoma: Oncology-radiology integration

Background

Aggressive brain tumors like glioblastoma multiforme (GBM) pose a poor prognosis. While magnetic resonance imaging (MRI) is crucial for GBM management, distinguishing it from other lesions using conventional methods can be difficult. This study explores advanced MRI techniques better to understand GBM properties and their link to patient outcomes.

Methods

We studied MRI scans of 157 GBM surgery patients from January 2020 to March 2024 to extract radiomic features and analyze the impact of fluid-attenuated inversion recovery (FLAIR) resection on survival using statistical methods, proportional hazards regression, and Kaplan-Meier survival analysis.

Results

Predictive models achieved high accuracy (area under the curve of 0.902) for glioma-grade prediction. FLAIR abnormality resection significantly improved survival, while diffusion-weighted image best-depicted tumor infiltration. Glioblastoma infiltration was best seen with advanced MRI compared to metastasis. Glioblastomas showed distinct features, including irregular shape, margins, and enhancement compared to metastases, which were oval or round, with clear edges and even contrast, and extensive peritumoral changes.

Conclusion

Advanced radiomic and machine learning analysis of MRI can provide noninvasive glioma grading and characterization of tumor properties with clinical relevance. Combining advanced neuroimaging with histopathology may better integrate oncology and radiology for optimized glioblastoma management. However, further studies are needed to validate these findings with larger datasets and assess additional MRI sequences and radiomic features.

Prediction of nuclide accumulation spread based on the volume of enhancing magnetic resonance imaging lesion in glioblastoma patients

BACKGROUND

11C-methionine-PET (MET) and Thallium-201 chloride-SPECT (TL) are useful for predictive proliferation ability and tumor invasion range identification in glioma patients, however they are not always possible in any hospital or country. Our study aimed to assess whether the range of MET and Tl accumulation could be predicted from the contrast-enhanced lesions in Gadolinium (Gd)-T1 weighted magnetic resonance image in glioblastoma multiforme (GBM) patients.

METHODS

In 25 cases, the MET-area, TL-area, O-area where MET and TL overlap, and all accumulation area (AA-area) were measured in the same axial cross section as the Gd enhanced maximum area (Gd-area). This tracing operation was repeated with all axial fusion slices, and each volume was also measured (Gd-V, MET-V, TL-V, O-V, AA-V).

RESULTS

The maximum accumulation distance of MET and TL beyond the Gd-area was limited to within 30 mm, 35 mm, respectively. Significant positive correlations were showed in all combinations with Gd-area: MET-area (r=0.851, P<0.0001), TL-area (r=0.955, P<0.0001), O-area (r=0.935, P<0.0001) and AA-area (r=0.893, P<0.0001), respectively. All combinations with Gd-V showed significant positive correlation: MET-V (r=0.867, P<0.0001), TL-V (r=0.952, P<0.0001), O-V (r=0.935, P<0.0001) and AA-V (r=0.897, P<0.0001), respectively.

CONCLUSIONS

Approximate tumor volume Gd-V can be calculated using the formula A * B * C / 2, where A, B, and C represent the dimensions of Gd-enhanced lesion in 3 axes perpendicular to each other. The nuclide accumulation predictive table created using the obtained linear approximation functions can be used to predict the average tumor invasion range from the Gd-V without preoperative nuclear examinations.

The surgical management of diffuse gliomas: Current state of neurosurgical management and future directions

After recent updates to the World Health Organization pathological criteria for diagnosing and grading diffuse gliomas, all major North American and European neuro-oncology societies recommend a maximal safe resection as the initial management of a diffuse glioma. For neurosurgeons to achieve this goal, the surgical plan for both low- and high-grade gliomas should be to perform a supramaximal resection when feasible based on preoperative imaging and the patient's performance status, utilizing every intraoperative adjunct to minimize postoperative neurological deficits. While the surgical approach and technique can vary, every effort must be taken to identify and preserve functional cortical and subcortical regions. In this summary statement on the current state of the field, we describe the tools and technologies that facilitate the safe removal of diffuse gliomas and highlight intraoperative and postoperative management strategies to minimize complications for these patients. Moreover, we discuss how surgical resections can go beyond cytoreduction by facilitating biological discoveries and improving the local delivery of adjuvant chemo- and radiotherapies.

Association of pre-radiotherapy tumour burden and overall survival in newly diagnosed glioblastoma adjusted for MGMT promoter methylation status

PURPOSE

We retrospectively evaluated the association between postoperative pre-radiotherapy tumour burden and overall survival (OS) adjusted for the prognostic value of O6-methylguanine DNA methyltransferase (MGMT) promoter methylation in patients with newly diagnosed glioblastoma treated with radio-/chemotherapy with temozolomide.

MATERIALS AND METHODS

Patients were included from the CENTRIC (EORTC 26071-22072) and CORE trials if postoperative magnetic resonance imaging scans were available within a timeframe of up to 4weeks before radiotherapy, including both pre- and post-contrast T1w images and at least one T2w sequence (T2w or T2w-FLAIR). Postoperative (residual) pre-radiotherapy contrast-enhanced tumour (CET) volumes and non-enhanced T2w abnormalities (NT2A) tissue volumes were obtained by three-dimensional segmentation. Cox proportional hazard models and Kaplan Meier estimates were used to assess the association of pre-radiotherapy CET/NT2A volume with OS adjusted for known prognostic factors (age, performance status, MGMT status).

RESULTS

408 tumour (of which 270 MGMT methylated) segmentations were included. Median OS in patients with MGMT methylated tumours was 117 weeks versus 61weeks in MGMT unmethylated tumours (p < 0.001). When stratified for MGMT methylation status, higher CET volume (HR 1.020; 95% confidence interval CI [1.013-1.027]; p < 0.001) and older age (HR 1.664; 95% CI [1.214-2.281]; p = 0.002) were significantly associated with shorter OS while NT2A volume and performance status were not.

CONCLUSION

Pre-radiotherapy CET volume was strongly associated with OS in patients receiving radio-/chemotherapy for newly diagnosed glioblastoma stratified by MGMT promoter methylation status.

Surgical management of Glioma Grade 4: technical update from the neuro-oncology section of the Italian Society of Neurosurgery (SINch®): a systematic review

PURPOSE

The extent of resection (EOR) is an independent prognostic factor for overall survival (OS) in adult patients with Glioma Grade 4 (GG4). The aim of the neuro-oncology section of the Italian Society of Neurosurgery (SINch®) was to provide a general overview of the current trends and technical tools to reach this goal.

METHODS

A systematic review was performed. The results were divided and ordered, by an expert team of surgeons, to assess the Class of Evidence (CE) and Strength of Recommendation (SR) of perioperative drugs management, imaging, surgery, intraoperative imaging, estimation of EOR, surgery at tumor progression and surgery in elderly patients.

RESULTS

A total of 352 studies were identified, including 299 retrospective studies and 53 reviews/meta-analysis. The use of Dexamethasone and the avoidance of prophylaxis with anti-seizure medications reached a CE I and SR A. A preoperative imaging standard protocol was defined with CE II and SR B and usefulness of an early postoperative MRI, with CE II and SR B. The EOR was defined the strongest independent risk factor for both OS and tumor recurrence with CE II and SR B. For intraoperative imaging only the use of 5-ALA reached a CE II and SR B. The estimation of EOR was established to be fundamental in planning postoperative adjuvant treatments with CE II and SR B and the stereotactic image-guided brain biopsy to be the procedure of choice when an extensive surgical resection is not feasible (CE II and SR B).

CONCLUSIONS

A growing number of evidences evidence support the role of maximal safe resection as primary OS predictor in GG4 patients. The ongoing development of intraoperative techniques for a precise real-time identification of peritumoral functional pathways enables surgeons to maximize EOR minimizing the post-operative morbidity.

Maximal Safe Resection in Glioblastoma Surgery: A Systematic Review of Advanced Intraoperative Image-Guided Techniques

Glioblastoma multiforme (GBM) represents the most common and aggressive central nervous system tumor associated with a poor prognosis. The aim of this study was to depict the role of intraoperative imaging techniques in GBM surgery and how they can ensure the maximal extent of resection (EOR) while preserving the functional outcome. The authors conducted a systematic review following PRISMA guidelines on the PubMed/Medline and Scopus databases. A total of 1747 articles were identified for screening. Studies focusing on GBM-affected patients, and evaluations of EOR and functional outcomes with the aid of advanced image-guided techniques were included. The resulting studies were assessed for methodological quality using the Risk of Bias in Systematic Review tool. Open Science Framework registration DOI 10.17605/OSF.IO/3FDP9. Eighteen studies were eligible for this systematic review. Among the selected studies, eight analyzed Sodium Fluorescein, three analyzed 5-aminolevulinic acid, two evaluated IoMRI imaging, two evaluated IoUS, and three evaluated multiple intraoperative imaging techniques. A total of 1312 patients were assessed. Gross Total Resection was achieved in the 78.6% of the cases. Follow-up time ranged from 1 to 52 months. All studies assessed the functional outcome based on the Karnofsky Performance Status scale, while one used the Neurologic Assessment in Neuro-Oncology score. In 77.7% of the cases, the functional outcome improved or was stable over the pre-operative assessment. Combining multiple intraoperative imaging techniques could provide better results in GBM surgery than a single technique. However, despite good surgical outcomes, patients often present a neurocognitive decline leading to a marked deterioration of the quality of life. Advanced intraoperative image-guided techniques can allow a better understanding of the anatomo-functional relationships between the tumor and the surrounding brain, thus maximizing the EOR while preserving functional outcomes.

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma

Background

Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT).

Methods

Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased.

Results

Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT (P < 0.05). A decrease of TGR (P = 0.009), smaller baseline tumor volume (P = 0.02), O6-methylguanine-DNA methyltransferase promoter methylation (P = 0.048) and fewer number of recurrences (P = 0.048) were significantly associated with longer OS after controlling for age, sex and concomitant RT.

Conclusion

A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

The Extent of Resection in Gliomas-Evidence-Based Recommendations on Methodological Aspects of Research Design

OBJECTIVE

Modern neurosurgery has established maximal safe resection as a cornerstone in the management of diffuse gliomas. Evaluation of the extent of resection (EOR), and its association with certain outcomes or interventions, heavily depends on an adequate methodology to draw strong conclusions. We aim to identify weaknesses and limitations that may threaten the internal validity and generalizability of studies involving the EOR in patients with glioma and to suggest methodological recommendations that may help mitigate these threats.

METHODS

A systematic search was performed by querying PubMed, Web of Science, and Scopus since inception to April 30, 2021 using PICOS/PRISMA guidelines. Articles were then screened to identify high-impact studies evaluating the EOR in patients diagnosed with diffuse gliomas in accordance with predefined criteria. We identify common weakness and limitations during the evaluation of the EOR in the selected studies and then delineate potential methodological recommendations for future endeavors dealing with the EOR.

RESULTS

We identified 31 high-impact studies and found several research design issues including inconsistencies regarding EOR terminology, measurement, data collection, analysis, and reporting. Although some of these issues were related to now outdated reporting standards, many were still present in recent publications and deserve attention in contemporary and future research.

CONCLUSIONS

There is a current need to focus more attention to the methodological aspects of glioma research. Methodological inconsistencies may introduce weaknesses into the internal validity of the studies and hamper comparative analysis of cohorts from different institutions. We hope our recommendations will eventually help develop stronger methodological designs in future research endeavors.

FLAIRectomy: Resecting beyond the Contrast Margin for Glioblastoma

The standard of care for isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) is maximal resection followed by chemotherapy and radiation. Studies investigating the resection of GBM have primarily focused on the contrast enhancing portion of the tumor on magnetic resonance imaging. Histopathological studies, however, have demonstrated tumor infiltration within peri-tumoral fluid-attenuated inversion recovery (FLAIR) abnormalities, which is often not resected. The histopathology of FLAIR and local recurrence patterns of GBM have prompted interest in the resection of peri-tumoral FLAIR, or FLAIRectomy. To this point, recent studies have suggested a significant survival benefit associated with safe peri-tumoral FLAIR resection. In this review, we discuss the evidence surrounding the composition of peri-tumoral FLAIR, outcomes associated with FLAIRectomy, future directions of the field, and potential implications for patients.

Contrast enhancing pattern on pre-treatment MRI predicts response to anti-angiogenic treatment in recurrent glioblastoma: comparison of bevacizumab and temozolomide treatment

OBJECTIVE

To evaluate the value of the contrast enhancing pattern on pre-treatment MRI for predicting the response to anti-angiogenic treatment in patients with IDH-wild type recurrent glioblastoma.

METHODS

This retrospective study enrolled 65 patients with IDH wild-type recurrent glioblastoma who received standard therapy and then received either bevacizumab (46 patients) or temozolomide (19 patients) as a secondary treatment. The contrast enhancing pattern on pre-treatment MRI was visually analyzed and dichotomized into contrast enhancing lesion (CEL) dominant and non-enhancing lesion (NEL) dominant types. Quantitative volumetric analysis was used to support the dichotomization. The Kaplan-Meier method and Cox proportional hazards regression analysis were used to stratify progression free survival (PFS) according to the treatment in the entire patients, CEL dominant group, and NEL dominant group.

RESULTS

In all patients, the PFS of those treated with bevacizumab was not significantly different from those treated with temozolomide (log-rank test, P = 0.96). When the contrast enhancing pattern was considered, bevacizumab was associated with longer PFS in the CEL dominant group (P = 0.031), whereas temozolomide showed longer PFS in the NEL dominant group (P = 0.022). Quantitative analysis revealed mean values for the proportion of solid-enhancing tumor of 13.7% for the CEL dominant group and 4.3% for the NEL dominant group.

CONCLUSION

Patients with the CEL dominant type showed a better treatment response to bevacizumab, whereas NEL dominant types showed a better response to temozolomide. The contrast enhancing pattern on pre-treatment MRI can be used to stratify patients with IDH wild-type recurrent glioblastoma according to the effect of anti-angiogenic treatment.

Prediction of Glioma Grade Using Intratumoral and Peritumoral Radiomic Features From Multiparametric MRI Images

The accurate prediction of glioma grade before surgery is essential for treatment planning and prognosis. Since the gold standard (i.e., biopsy)for grading gliomas is both highly invasive and expensive, and there is a need for a noninvasive and accurate method. In this study, we proposed a novel radiomics-based pipeline by incorporating the intratumoral and peritumoral features extracted from preoperative mpMRI scans to accurately and noninvasively predict glioma grade. To address the unclear peritumoral boundary, we designed an algorithm to capture the peritumoral region with a specified radius. The mpMRI scans of 285 patients derived from a multi-institutional study were adopted. A total of 2153 radiomic features were calculated separately from intratumoral volumes (ITVs)and peritumoral volumes (PTVs)on mpMRI scans, and then refined using LASSO and mRMR feature ranking methods. The top-ranking radiomic features were entered into the classifiers to build radiomic signatures for predicting glioma grade. The prediction performance was evaluated with five-fold cross-validation on a patient-level split. The radiomic signatures utilizing the features of ITV and PTV both show a high accuracy in predicting glioma grade, with AUCs reaching 0.968. By incorporating the features of ITV and PTV, the AUC of IPTV radiomic signature can be increased to 0.975, which outperforms the state-of-the-art methods. Additionally, our proposed method was further demonstrated to have strong generalization performance in an external validation dataset with 65 patients. The source code of our implementation is made publicly available at https://github.com/chengjianhong/glioma_grading.git.

A Super-selective Wada Test Successfully Detected an Artery That Supplied Broca's Area in a Case of Left Frontal Lobe Glioblastoma: Technical Case Report

In cases of malignant gliomas located at language eloquent area, it is often difficult to preoperatively detect those area with functional MRI. Awake surgery is often used to spare the language eloquent area during surgery for such tumors; it is not available for a patient whose intracranial pressure is elevated due to the malignant tumor. The Wada test involves infusing anesthetic agents into the internal carotid artery to determine language dominancy before surgery for epilepsy or brain tumor. The super-selective Wada test is a technique to detect more detailed functional localization by infusing anesthetics into far distal middle cerebral artery branches. We present a 37-year-old man suffering from a left frontal lobe glioblastoma, in whom detection of an artery supplying Broca's area was attempted by a super-selective Wada test. The super-selective Wada test successfully detected the branch of middle cerebral artery supplying Broca's area. Total resection of the contrast-enhancing area was achieved without damaging the artery supplying Broca's area without any neurological sequelae. This is the first report describing the usefulness of the super-selective Wada test in glioblastoma treatment. Our findings suggest that the super-selective Wada test is a powerful and useful means to distinguish the artery that supplies the language area from the tumor feeding artery in cases of tumors in the language eloquent area.

Enhancing T Cell Chemotaxis and Infiltration in Glioblastoma

Glioblastoma is an immunologically 'cold' tumor, which are characterized by absent or minimal numbers of tumor-infiltrating lymphocytes (TILs). For those tumors that have been invaded by lymphocytes, they are profoundly exhausted and ineffective. While many immunotherapy approaches seek to reinvigorate immune cells at the tumor, this requires TILs to be present. Therefore, to unleash the full potential of immunotherapy in glioblastoma, the trafficking of lymphocytes to the tumor is highly desirable. However, the process of T cell recruitment into the central nervous system (CNS) is tightly regulated. Naïve T cells may undergo an initial licensing process to enter the migratory phenotype necessary to enter the CNS. T cells then must express appropriate integrins and selectin ligands to interact with transmembrane proteins at the blood-brain barrier (BBB). Finally, they must interact with antigen-presenting cells and undergo further licensing to enter the parenchyma. These T cells must then navigate the tumor microenvironment, which is rich in immunosuppressive factors. Altered tumoral metabolism also interferes with T cell motility. In this review, we will describe these processes and their mediators, along with potential therapeutic approaches to enhance trafficking. We also discuss safety considerations for such approaches as well as potential counteragents.

Multimodal Disentangled Variational Autoencoder with Game Theoretic Interpretability for Glioma grading

Effective fusion of multimodal magnetic resonance imaging (MRI) is of great significance to boost the accuracy of glioma grading thanks to the complementary information provided by different imaging modalities. However, how to extract the common and distinctive information from MRI to achieve complementarity is still an open problem in information fusion research. In this study, we propose a deep neural network model termed as multimodal disentangled variational autoencoder (MMD-VAE) for glioma grading based on radiomics features extracted from preoperative multimodal MRI images. Specifically, the radiomics features are quantized and extracted from the region of interest for each modality. Then, the latent representations of variational autoencoder for these features are disentangled into common and distinctive representations to obtain the shared and complementary data among modalities. Afterward, cross-modality reconstruction loss and common-distinctive loss are designed to ensure the effectiveness of the disentangled representations. Finally, the disentangled common and distinctive representations are fused to predict the glioma grades, and SHapley Additive exPlanations (SHAP) is adopted to quantitatively interpret and analyze the contribution of the important features to grading. Experimental results on two benchmark datasets demonstrate that the proposed MMD-VAE model achieves encouraging predictive performance (AUC:0.9939) on a public dataset, and good generalization performance (AUC:0.9611) on a cross-institutional private dataset. These quantitative results and interpretations may help radiologists understand gliomas better and make better treatment decisions for improving clinical outcomes.

Glioblastoma radiomics to predict survival: Diffusion characteristics of surrounding nonenhancing tissue to select patients for extensive resection

BACKGROUND AND PURPOSE

Glioblastoma (GBM) is an aggressive primary CNS neoplasm with poor overall survival (OS) despite standard of care. On MRI, GBM is usually characterized by an enhancing portion (CET) (surgery target) and a nonenhancing surrounding (NET). Extent of resection is a long debated issue in GBM, with recent evidence suggesting that both CET and NET should be resected in <65 years old patients, regardless of other risk factors (i.e., molecular biomarkers). Our aim was to test a radiomic model for patient survival stratification in <65 years old patients, by analyzing MRI features of NET, to aid tumor resection.

METHODS

Sixty-eight <65 years old GBM patients, with extensive CET resection, were selected. Resection was evaluated by manually segmenting CET on volumetric T1-weighted MRI pre and postsurgery (within 72 h). All patients underwent the same treatment protocol including chemoradiation. NET radiomic features were extracted with a custom version of Pyradiomics. Feature selection was performed with principal component analysis (PCA) and its effect on survival tested with Cox regression model. Twelve months OS discrimination was tested by t-test followed by logistic regression. Statistical significance was set at p<0.05. The most relevant features were identified from the component matrix.

RESULTS

Five PCA components (PC1-5) explained 90% of the variance. PC5 resulted significant in the Cox model (p = 0.002; exp(B) = 0.686), at t-test (p = 0.002) and logistic regression analysis (p = 0.006). Apparent diffusion coefficient (ADC)-based features were the most significant for patient survival stratification.

CONCLUSIONS

ADC radiomic features on NET predict survival after standard therapy and could be used to improve patient selection for more extensive surgery.

Refinement of response assessment in neuro-oncology (RANO) using non-enhancing lesion type and contrast enhancement evolution pattern in IDH wild-type glioblastomas

Background

Updated response assessment in neuro-oncology (RANO) does not consider peritumoral non-enhancing lesion (NEL) and baseline (residual) contrast enhancement (CE) volume. The objective of this study is to explore helpful imaging characteristics to refine RANO for assessing early treatment response (pseudoprogression and time-to-progression [TTP]) in patients with IDH wild-type glioblastoma.

Methods

This retrospective study enrolled 86 patients with IDH wild-type glioblastoma who underwent consecutive MRI examinations before and after concurrent chemoradiotherapy (CCRT). NEL was classified as edema- or tumor-dominant type on pre-CCRT MRI. CE evolution was categorized into 4 patterns based on post-operative residual CE (measurable vs. non-measurable) and CE volume change (same criteria with RANO) during CCRT. Multivariable logistic regression, including clinical parameters, NEL type, and CE evolution pattern, was used to analyze pseudoprogression rate. TTP and OS according to NEL type and CE evolution pattern was analyzed by the Kaplan–Meier method.

Results

Pseudoprogression rate was significantly lower (chi-square test, P = .047) and TTP was significantly shorter (hazard ratio [HR] = 2.03, P = .005) for tumor-dominant type than edema-dominant type of NEL. NEL type was the only predictive marker of pseudoprogression on multivariate analysis (odds ratio = 0.26, P = .046). Among CE evolution patterns, TTP and OS was shortest in patients with residual CE compared with those exhibiting new CE (HR = 4.33, P < 0.001 and HR = 3.71, P = .009, respectively). In edema-dominant NEL type, both TTP and OS was stratified by CE evolution pattern (log-rank, P = .001), whereas it was not in tumor-dominant NEL.

Conclusions

NEL type improves prediction of pseudoprogression and, together with CE evolution pattern, further stratifies TTP and OS in patients with IDH wild-type glioblastoma and may become a helpful biomarker for refining RANO.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08414-2.

Evidence-based recommendations on categories for extent of resection in diffuse glioma

Surgical resection represents the standard of care in diffuse glioma, and more extensive tumour resection appears to be associated with favourable outcome. Up to now, terminology to describe extent of resection has been inconsistently applied across clinical trials which hampers comparative analysis of cohorts between different studies. Based on a comprehensive literature review, we developed evidence-based expert recommendations on categories for extent of resection. Recommendations are formulated for the categories 'biopsy', 'partial resection', 'subtotal resection', 'near total resection', 'complete resection' and 'supramaximal resection'. Definitions rest on reduction of contrast- and non-contrast-enhancing tumour in glioblastoma, and on reduction of T2/FLAIR-hyperintense tumour in gliomas WHO grade 2 or 3. Both relative reduction of tumour volume (in percentage) as a measurement of surgical efficacy and absolute residual tumour volume (in cm³) as a measurement of remaining tumour burden are incorporated into the categories for extent of resection. Class of evidence for the proposed categories ranges from class IIB to IV. Limitations of the suggested categories are discussed. The proposed categories on extent of resection offer a framework to standardize nomenclature based on previous studies, and will need to be evaluated in prospective, molecularly well-defined cohorts. Our categories may eventually help as a stratification factor for future clinical trials.

Current Limitations of Intraoperative Ultrasound in Brain Tumor Surgery

While benefits of intraoperative ultrasound (IOUS) have been frequently described, data on IOUS limitations are relatively sparse. Suboptimal ultrasound imaging of some pathologies, various types of ultrasound artifacts, challenging patient positioning during some IOUS-guided surgeries, and absence of an optimal IOUS probe depicting the entire sellar region during transsphenoidal pituitary surgery are some of the most important pitfalls. This review aims to summarize prominent limitations of current IOUS systems, and to present possibilities to reduce them by using ultrasound technology suitable for a specific procedure and by proper scanning techniques. In addition, future trends of IOUS imaging optimization are described in this article.

MGMT Promoter Methylation Status in Initial and Recurrent Glioblastoma: Correlation Study with DWI and DSC PWI Features

BACKGROUND AND PURPOSE

O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in primary and recurrent glioblastoma may change during treatment. The purpose of this study was to correlate MGMT promoter methylation status changes with DWI and DSC PWI features in patients with recurrent glioblastoma after standard treatment.

MATERIALS AND METHODS

Between January 2008 and November 2016, forty patients with histologically confirmed recurrent glioblastoma were enrolled. Patients were divided into 3 groups according to the MGMT promoter methylation status for the initial and recurrent tumors: 2 groups whose MGMT promoter methylation status remained, group methylated (n = 13) or group unmethylated (n = 18), and 1 group whose MGMT promoter methylation status changed from methylated to unmethylated (n = 9). Normalized ADC and normalized relative CBV values were obtained from both the enhancing and nonenhancing regions, from which histogram parameters were calculated. The ANOVA and the Kruskal-Wallis test followed by post hoc tests were performed to compare histogram parameters among the 3 groups. The t test and Mann-Whitney U test were used to compare parameters between group methylated and group methylated to unmethylated. Receiver operating characteristic curve analysis was used to measure the predictive performance of the normalized relative CBV values between the 2 groups.

RESULTS

Group methylated to unmethylated showed significantly higher means and 90th and 95th percentiles of the cumulative normalized relative CBV values of the nonenhancing region of the initial tumor than group methylated and group unmethylated (all P < .05). The mean normalized relative CBV value of the nonenhancing region of the initial tumor was the best predictor of methylation status change (P < .001), with a sensitivity of 77.78% and specificity of 92.31% at a cutoff value of 2.594.

CONCLUSIONS

MGMT promoter methylation status might change in recurrent glioblastoma after standard treatment. The normalized relative CBV values of the nonenhancing region at the first preoperative MR imaging were higher in the MGMT promoter methylation change group from methylation to unmethylation in recurrent glioblastoma.

Advancing Imaging to Enhance Surgery: From Image to Information Guidance

Conventional magnetic resonance imaging (cMRI) has an established role as a crucial disease parameter in the multidisciplinary management of glioblastoma, guiding diagnosis, treatment planning, assessment, and follow-up. Yet, cMRI cannot provide adequate information regarding tissue heterogeneity and the infiltrative extent beyond the contrast enhancement. Advanced magnetic resonance imaging and PET and newer analytical methods are transforming images into data (radiomics) and providing noninvasive biomarkers of molecular features (radiogenomics), conveying enhanced information for improving decision making in surgery. This review analyzes the shift from image guidance to information guidance that is relevant for the surgical treatment of glioblastoma.

Effects of supra-total resection in neurocognitive and oncological outcome of high-grade gliomas comparing asleep and awake surgery

PURPOSE

Awake surgery is an established technique for resection of low-grade gliomas, while its possible benefit for resection of high-grade gliomas (HGGs) needs further confirmations. This retrospective study aims to compare overall survival, extent of resection (EOR) and cognitive outcome in two groups of HGGs patients submitted to asleep or awake surgery.

METHODS

Thirty-three patients submitted to Gross Total Resection of contrast-enhancing area of HGGs were divided in two homogeneous groups: awake (AWg; N = 16) and asleep surgery (ASg; N = 17). All patients underwent to an extensive neuropsychological assessment before surgery (time_1), 1-week (time_2) and 4-months (time_3) after surgery. We performed analyses to assess differences in cognitive performances between groups, cognitive outcomes in each group and EOR. A comparison of overall survival (OS) between the two groups was conducted.

RESULTS

Statistical analyses showed no differences between groups at time_2 and time_3 in each cognitive domain, excluding selective attention that resulted higher in the AWg before surgery. Regarding cognitive outcomes, we found a reversible worsening of memory and constructional praxis, and a significant recovery at time_3, similar for both groups. Assessment of time_3 in respect to time_1 never showed differences (all ps > .074). Moreover we found a significant lower level of tumor infiltration after surgery for AWg (p < .05), with an influence on OS (p < .05). Indeed, patients of AWg showed a significant longer OS in comparison to those in the ASg (p < .01). This result was confirmed even considering only wildtype Glioblastoma (p < .05).

CONCLUSION

These results indicate that awake surgery, and in general a supra-total resection of enhancing area, can improve OS in HGGs patients, preserving neuro-cognitive profile and quality of life.

Validation of magnetic resonance imaging-based automatic high-grade glioma segmentation accuracy via 11C-methionine positron emission tomography

Brain Tumor Image Analysis (BraTumIA) is a fully automated segmentation tool dedicated to detecting brain tumors imaged by magnetic resonance imaging (MRI). BraTumIA has recently been applied to several clinical investigations; however, the validity of this novel method has not yet been fully examined. The present study was conducted to validate the quality of tumor segmentation with BraTumIA in comparison with results from ¹¹C-methionine positron emission tomography (MET-PET). A total of 45 consecutive newly diagnosed high-grade gliomas imaged by MRI and MET-PET were analyzed. Automatic tumor segmentation was conducted by BraTumIA and the resulting segmentation images were registered to MET-PET. Three-dimensional conformal association between these two modalities was calculated, considering MET-PET as the gold standard. High underestimation and overestimation errors were observed in tumor segmentation calculated by BraTumIA compared with MET-PET. Furthermore, when the tumor/normal ratio threshold was set at 1.3 from MET-PET, the BraTumIA false-positive fraction was ~0.4 and the false-negative fraction was 0.9. By tightening this threshold to 2.0, the BraTumIA false-positive fraction was 0.6 and the false-negative fraction was 0.6. Following comparison of segmentation performance with BraTumIA with regard to glioblastoma (GBM) and World Health Organization (WHO) grade III glioma, GBM exhibited better segmentation compared with WHO grade III glioma. Although BraTumIA may be able to detect enhanced tumors, non-enhancing tumors and necrosis, the spatial concordance rate with MET-PET was relatively low. Careful interpretation is therefore required when using this technique.

Non-Contrast-Enhancing Tumor: A New Frontier in Glioblastoma Research

There is a growing understanding of the prognostic importance of non-contrast-enhancing tumor in glioblastoma, and recent attempts at more aggressive management of this component using neurosurgical resection and radiosurgery have been shown to prolong survival. Optimizing these therapeutic strategies requires an understanding of the features that can distinguish non-contrast-enhancing tumor from other processes, in particular vasogenic edema; however, the limited and heterogeneous manner in which it has been defined in the literature limits clinical translation. This review covers pertinent literature on our growing understanding of non-contrast-enhancing tumor and focuses on key conventional MR imaging features for improving its delineation. Such features include subtle differences in the degree of FLAIR hyperintensity, gray matter involvement, and focal mass effect. Improved delineation of tumor from edema will facilitate more aggressive management of this component and potentially realize associated survival benefits.