EANO guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics

OBJECTIVES

To evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM).

MATERIALS AND METHODS

In this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison.

RESULTS

The validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar.

CONCLUSION

The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM.

CLINICAL RELEVANCE STATEMENT

The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity.

KEY POINTS

• The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis. • Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors. • The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma and supratentorial glioblastoma

Objective

To develop a machine learning-based nomogram for distinguishing between supratentorial extraventricular ependymoma (STEE) and supratentorial glioblastoma (GBM).

Methods

We conducted a retrospective analysis on MRI datasets obtained from 140 patients who were diagnosed with STEE (n=48) and GBM (n=92) from two institutions. Initially, we compared seven different machine learning algorithms to determine the most suitable signature (rad-score). Subsequently, univariate and multivariate logistic regression analyses were performed to identify significant clinical predictors that can differentiate between STEE and GBM. Finally, we developed a nomogram by visualizing the rad-score and clinical features for clinical evaluation.

Results

The TreeBagger (TB) outperformed the other six algorithms, yielding the best diagnostic efficacy in differentiating STEE from GBM, with area under the curve (AUC) values of 0.735 (95% CI: 0.625-0.845) and 0.796 (95% CI: 0.644-0.949) in the training set and test set. Furthermore, the nomogram incorporating both the rad-score and clinical variables demonstrated a robust predictive performance with an accuracy of 0.787 in the training set and 0.832 in the test set.

Conclusion

The nomogram could serve as a valuable tool for non-invasively discriminating between STEE and GBM.

Differentiation of glioblastoma from solitary brain metastasis using deep ensembles: Empirical estimation of uncertainty for clinical reliability

BACKGROUND AND OBJECTIVES

To develop a clinically reliable deep learning model to differentiate glioblastoma (GBM) from solitary brain metastasis (SBM) by providing predictive uncertainty estimates and interpretability.

METHODS

A total of 469 patients (300 GBM, 169 SBM) were enrolled in the institutional training set. Deep ensembles based on DenseNet121 were trained on multiparametric MRI. The model performance was validated in the external test set consisting of 143 patients (101 GBM, 42 SBM). Entropy values for each input were evaluated for uncertainty measurement; based on entropy values, the datasets were split to high- and low-uncertainty groups. In addition, entropy values of out-of-distribution (OOD) data from unknown class (257 patients with meningioma) were compared to assess uncertainty estimates of the model. The model interpretability was further evaluated by localization accuracy of the model.

RESULTS

On external test set, the area under the curve (AUC), accuracy, sensitivity and specificity of the deep ensembles were 0.83 (95 % confidence interval [CI] 0.76-0.90), 76.2 %, 54.8 % and 85.2 %, respectively. The performance was higher in the low-uncertainty group than in the high-uncertainty group, with AUCs of 0.91 (95 % CI 0.83-0.98) and 0.58 (95 % CI 0.44-0.71), indicating that assessment of uncertainty with entropy values ascertained reliable prediction in the low-uncertainty group. Further, deep ensembles classified a high proportion (90.7 %) of predictions on OOD data to be uncertain, showing robustness in dataset shift. Interpretability evaluated by localization accuracy provided further reliability in the "low-uncertainty and high-localization accuracy" subgroup, with an AUC of 0.98 (95 % CI 0.95-1.00).

CONCLUSIONS

Empirical assessment of uncertainty and interpretability in deep ensembles provides evidence for the robustness of prediction, offering a clinically reliable model in differentiating GBM from SBM.

National Trends and Factors Associated with Voluntary Refusal of Glioblastoma Treatment: A Retrospective Review of the National Cancer Database

OBJECTIVE

Adherence to combinatorial treatments are important predictors of improved long-term outcomes for patients with glioblastoma (GB); however, factors associated with refusal of surgery, chemotherapy, or radiotherapy (RT) by patients with GB have not been studied.

METHODS

The National Cancer Database was queried from 2004 to 2018 to identify patients with a primary diagnosis of GB who underwent surgical resection alone or followed by either RT or chemotherapy. Adult patients who voluntarily rejected a physician's recommendations for 1 or more treatment were selected. Multivariable regression was used to identify factors associated with rejection of surgical resection, chemotherapy, and RT. Patients receiving treatment were 3:1 propensity score matched to those rejecting treatment and median overall survival (OS) was compared.

RESULTS

58,788 patients were included in the analysis. Factors associated with voluntary refusal of GB treatment included: old age, nonprivate insurance, female sex, Black race, comorbidities, treatment at a nonacademic facility, and living 55+ miles away from a treatment facility (P < 0.05). On propensity matched analysis, refusal of surgery conferred a 4 month decrease in OS (P < 0.001), RT an 8 month decrease in OS (P < 0.001), and chemotherapy a 7 month decrease in OS (P < 0.001).

CONCLUSIONS

In patients with GB, age, sex, race, nonprivate insurance, medical comorbidities, distance from treatment facility, and geographic location were associated with refusal of surgery, postsurgical RT, and chemotherapy. In addition, treatment refusal had a significant impact on OS length.

Gene Expression Profile Identifies LncRNA AL355974.3 As a Potential Glioma Biomarker

OBJECTIVE

Glioma is a central nervous system tumor arising from glial cells. Despite significant advances in diagnosis and treatment, most patients with high-grade gliomas have a poor prognosis. Many studies have shown that long noncoding RNAs (lncRNAs) may play important roles in the development, progression and treatment of many tumors, including gliomas. Molecularly targeted therapy may be a new direction for the adjuvant treatment of glioma. Therefore, we hope that by studying differentially expressed lncRNAs (DElncRNAs) in glioma, we can discover lncRNAs that can serve as biomarkers for glioma and provide better therapeutic modalities for glioma patients.

METHODS

First, the expression of lncRNAs in 5 normal brain (NB) tissues and 10 glioma tissues was examined by RNA sequencing (RNA-seq). Next, we performed Kaplan-Meier analysis of data from The Cancer Genome Atlas (TCGA) database to assess the prognostic value of these variables. Finally, functional analysis of the DElncRNAs was performed by means of Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis.

RESULTS

RNA sequencing analysis revealed 85 upregulated miRNAs and 71 downregulated lncRNAs in low-grade glioma (LGG) and 50 upregulated lncRNAs and 70 downregulated lncRNAs in glioblastoma (GBM). Among them, AL355974.3 was the most upregulated lncRNA. LINC00632 was the most downregulated lncRNA. Second, LGG patients with higher AL355974.3 expression had worse overall survival according to Kaplan-Meier analysis of the TCGA database. Finally, bioinformatics analysis revealed that the target genes of these DElncRNAs were enriched in various biological processes and signaling pathways, such as cell metabolic and developmental processes.

CONCLUSION

Our findings provide evidence that AL355974.3 may be a new biomarker for glioma.

Assessing the prognostic role of panimmune inflammation in high-grade gliomas

OBJECTIVE

High-grade gliomas are aggressive brain tumors with poor prognoses. Understanding the factors that influence their progression is crucial for improving treatment outcomes. This study investigates the prognostic significance of panimmune inflammation in patients diagnosed with high-grade gliomas.

MATERIALS-METHODS

Data from 89 high-grade glioma patients were analysed retrospectively. The Panimmune inflammation Value (PIV) of each patient meeting the eligibility criteria was calculated on the basis of platelet, monocyte, neutrophil, and lymphocyte counts obtained from peripheral blood samples taken on the first day of treatment. PIV is calculated using the following formula: PIV = T × M × N ÷ L. A receiver operating characteristic (ROC) analysis was employed to identify the optimal cut-off value for PIV about progression-free survival (PFS) and overall survival (OS) outcomes. The primary and secondary endpoints were the differences in OS and PFS between the PIV groups. The Kaplan‒Meier method was used for survival analyses.

RESULTS

The ROC analysis indicated that the optimal PIV threshold was 545.5, which exhibited a significant interaction with PFS and OS outcomes. Patients were subsequently divided into two groups based on their PIV levels: a low PIV (L-PIV) group comprising 45 patients and a high PIV (H-PIV) group comprising 44 patients. A comparative analysis of survival rates indicated that patients with elevated PIV had a shorter median PFS of 4.0 months compared to 8.0 months in the low PIV group (P = 0.797), as well as a reduced median OS of 19.0 months versus not available (NA) in the low PIV group (P = 0.215).

CONCLUSION

Our study results did not reveal a statistically significant association between H-PIV measurements and reduced PFS or OS. However, PIV effectively stratified newly diagnosed high-grade glioma patients into two distinct groups with significantly different PFS and OS outcomes.

"Doctor, What Would You do if You Were Me?" - A Survey of Physician Perspectives Toward Glioblastoma Resection

OBJECTIVE

How maximal safe resection of glioblastoma (GBM) is implemented in the clinical setting remains understudied. Here, we utilized a survey-based approach to understand physician perspectives on this matter.

METHODS

Scenarios involving GBMs were presented to physicians who were asked to select from planned subtotal resection, gross total resection (GTR), medical therapy only, or palliative care. Demographic, experience, and Likert scales of value assessment were collected.

RESULTS

In the scenario involving a corpus callosum GBM, 2.33% opted for GTR. For a right frontal GBM, 91.7% opted for GTR. In contrast, only 30.8% chose GTR of a right motor strip GBM (P < 0.001). When presented with a left motor strip GBM, fewer respondents (12.7%, P < 0.001) opted for GTR. Physicians who placed a high value on preserving physical independence were more likely to forgo GTR for right motor GBMs (hazard ratio = 0.068, 95% confidence interval: 0.47-0.97, P = 0.035), and physicians who placed a high value on their faith were more likely to opt for surgical treatments that differ from the general consensus, for instance opting for GTR of the corpus callosum GBM (hazard ratio = 4.18, 95% confidence interval: 1.63-10.74, P = 0.003). No other associations were found between the choice for GTR and other variables collected.

CONCLUSIONS

Our results suggest that while maximal safe resection remains a guiding principle for GBM resection, physician preference in terms of the extent of resection varies significantly as a function of tumor location and personal values.

Novel Collagen Membrane Formulations with Irinotecan or Minocycline for Potential Application in Brain Cancer

Our study explores the development of collagen membranes with integrated minocycline or irinotecan, targeting applications in tissue engineering and drug delivery systems. Type I collagen, extracted from bovine skin using advanced fibril-forming technology, was crosslinked with glutaraldehyde to create membranes. These membranes incorporated minocycline, an antibiotic, or irinotecan, a chemotherapeutic agent, in various concentrations. The membranes, varying in drug concentration, were studied by water absorption and enzymatic degradation tests, demonstrating a degree of permeability. We emphasize the advantages of local drug delivery for treating high-grade gliomas, highlighting the targeted approach's efficacy in reducing systemic adverse effects and enhancing drug bioavailability at the tumor site. The utilization of collagen membranes is proposed as a viable method for local drug delivery. Irinotecan's mechanism, a topoisomerase I inhibitor, and minocycline's broad antibacterial spectrum and inhibition of glial cell-induced membrane degradation are discussed. We critically examine the challenges posed by the systemic administration of chemotherapeutic agents, mainly due to the blood-brain barrier's restrictive nature, advocating for local delivery methods as a more effective alternative for glioblastoma treatment. These local delivery strategies, including collagen membranes, are posited as significant advancements in enhancing therapeutic outcomes for glioblastoma patients.

DA, K. KK. Diagnostic Utility of Integration of Dynamic Contrast-Enhanced and Dynamic Susceptibility Contrast MR Perfusion Employing Split Bolus Technique in Differentiating High-Grade Glioma

Background : Despite documented correlation between glioma grades and dynamic contrast-enhanced (DCE) magnetic resonance (MR) perfusion-derived parameters, and its inherent advantages over dynamic susceptibility contrast (DSC) perfusion, the former remains underutilized in clinical practice. Given the inherent spatial heterogeneity in high-grade diffuse glioma (HGG) and assessment of different perfusion parameters by DCE (extravascular extracellular space volume [Ve] and volume transfer constant in unit time [k-trans]) and DSC (rCBV), integration of the two into a protocol could provide a holistic assessment. Considering therapeutic and prognostic implications of differentiating WHO grade 3 from 4, we analyzed the two grades based on a combined DCE and DSC perfusion. Methods : Perfusion sequences were performed on 3-T MR. Cumulative dose of 0.1 mmol/kg of gadodiamide, split into two equal boluses, was administered with an interval of 6 minutes between the DCE and DSC sequences. DCE data were analyzed utilizing commercially available GenIQ software. Results : Of the 41 cases of diffuse gliomas analyzed, 24 were WHO grade III and 17 grade IV gliomas (2016 WHO classification). To differentiate grade III and IV gliomas, Ve cut-off value of 0.178 provided the best combination of sensitivity (88.24%) and specificity (87.50%; AUC: 0.920; p  < 0.001). A relative cerebral blood volume (rCBV) of value 3.64 yielded a sensitivity of 70.59% and specificity of 62.50% ( p  = 0.018). The k-trans value, although higher in grade III than in grade IV gliomas, did not reach statistical significance ( p  = 0.108). Conclusion : Uniqueness of employed combined perfusion technique, treatment naïve patients at imaging, user-friendly postprocessing software utilization, and ability of Ve and rCBV to differentiate between grade III and IV gliomas ( p  < 0.05) are the strengths of the present study, contributing to the existing literature and moving a step closer to achieving accurate MR perfusion-based glioma grading.

A fast transition: A case study of patients' experiences during the diagnostic and surgical treatment phase of an accelerated brain cancer pathway

BACKGROUND

Patients receiving a brain cancer diagnosis may face cognitive decline and a poor prognosis. In addition, they suffer from a high symptom burden in a complex cancer pathway. The aim of this study was to investigate the early hospital experiences of brain tumour patients during the diagnostic and surgical treatment phase.

METHODS

A descriptive longitudinal single-case study design was used, and data were analysed via systematic text condensation.

RESULTS

The patients' experiences of being diagnosed with and treated for brain cancer were interpreted in terms of the central theme: a fast transition into an unknown journey. This theme consisted of the following subthemes: emotionally overwhelmed, putting life on hold and an unfamiliar dependency.

CONCLUSIONS

Patients diagnosed with brain cancer struggle with overwhelming emotions due to this sudden life-threatening diagnosis, their fear of brain surgery and their progressing dependence. Patients did not voice their feelings, fears or needs, so these may easily be overlooked and unmet. A proactive and continuous care approach throughout the diagnostic phase is needed to support these patients.

Fluorescein-stained confocal laser endomicroscopy versus conventional frozen section for intraoperative histopathological assessment of intracranial tumors

BACKGROUND

The aim of this clinical trial was to compare Fluorescein-stained intraoperative confocal laser endomicroscopy (CLE) of intracranial lesions and evaluation by a neuropathologist with routine intraoperative frozen section (FS) assessment by neuropathology.

METHODS

In this phase II noninferiority, prospective, multicenter, nonrandomized, off-label clinical trial (EudraCT: 2019-004512-58), patients above the age of 18 years with any intracranial lesion scheduled for elective resection were included. The diagnostic accuracies of both CLE and FS referenced with the final histopathological diagnosis were statistically compared in a noninferiority analysis, representing the primary endpoint. Secondary endpoints included the safety of the technique and time expedited for CLE and FS.

RESULTS

A total of 210 patients were included by 3 participating sites between November 2020 and June 2022. Most common entities were high-grade gliomas (37.9%), metastases (24.1%), and meningiomas (22.7%). A total of 6 serious adverse events in 4 (2%) patients were recorded. For the primary endpoint, the diagnostic accuracy for CLE was inferior with 0.87 versus 0.91 for FS, resulting in a difference of 0.04 (95% confidence interval -0.10; 0.02; P = .367). The median time expedited until intraoperative diagnosis was 3 minutes for CLE and 27 minutes for FS, with a mean difference of 27.5 minutes (standard deviation 14.5; P < .001).

CONCLUSIONS

CLE allowed for a safe and time-effective intraoperative histological diagnosis with a diagnostic accuracy of 87% across all intracranial entities included. The technique achieved histological assessments in real time with a 10-fold reduction of processing time compared to FS, which may invariably impact surgical strategy on the fly.

Columbianadin suppresses glioblastoma progression by inhibiting the PI3K-Akt signaling pathway

Glioblastoma (GBM) is the most common malignant glioma among brain tumors with low survival rate and high recurrence rate. Columbianadin (CBN) has pharmacological properties such as anti-inflammatory, analgesic, thrombogenesis-inhibiting and anti-tumor effects. However, it remains unknown that the effect of CBN on GBM cells and its underlying molecular mechanisms. In the present study, we found that CBN inhibited the growth and proliferation of GBM cells in a dose-dependent manner. Subsequently, we found that CBN arrested the cell cycle in G0/G1 phase and induced the apoptosis of GBM cells. In addition, CBN also inhibited the migration and invasion of GBM cells. Mechanistically, we chose network pharmacology approach by screening intersecting genes through targets of CBN in anti-GBM, performing PPI network construction followed by GO analysis and KEGG analysis to screen potential candidate signaling pathway, and found that phosphatidylinositol 3-kinase/Protein Kinase-B (PI3K/Akt) signaling pathway was a potential target signaling pathway of CBN in anti-GBM. As expected, CBN treatment indeed inhibited the PI3K/Akt signaling pathway in GBM cells. Furthermore, YS-49, an agonist of PI3K/Akt signaling, partially restored the anti-GBM effect of CBN. Finally, we found that CBN inhibited GBM growth in an orthotopic mouse model of GBM through inhibiting PI3K/Akt signaling pathway. Together, these results suggest that CBN has an anti-GBM effect by suppressing PI3K/Akt signaling pathway, and is a promising drug for treating GBM effectively.

Amide proton transfer-weighted imaging and derived radiomics in the classification of adult-type diffuse gliomas

OBJECTIVES

To evaluate the utility of amide proton transfer-weighted (APTw) MRI imaging and its derived radiomics in classifying adult-type diffuse glioma.

MATERIALS AND METHODS

In this prospective study, APTw imaging was performed on 129 patients with adult-type diffuse gliomas. The mean APTw-related metrics (chemical exchange saturation transfer ratio (CESTR), CESTR normalized with the reference value (CESTRnr), and relaxation-compensated inverse magnetization transfer ratio (MTRRex)) and radiomic features within 3D tumor masks were extracted. APTw-radiomics models were developed using a support vector machine (SVM) classifier. Sensitivity analysis with tumor area of interest, different histogram cutoff values, and other classifiers were conducted.

RESULTS

CESTR, CESTRnr, and MTRRex in glioblastomas were all significantly higher (p < 0.0003) than those of oligodendrogliomas and astrocytomas, with no significant difference between oligodendrogliomas and astrocytomas. The APTw-related metrics for IDH-wildtype and high-grade gliomas were significantly higher (p < 0.001) than those for the IDH-mutant and low-grade gliomas, with area under the curve (AUCs) of 0.88 for CESTR. The CESTR-radiomics models demonstrated accuracies of 84% (AUC 0.87), 83% (AUC 0.83), 90% (AUC 0.95), and 84% (AUC 0.86) in predicting the IDH mutation status, differentiating glioblastomas from astrocytomas, distinguishing glioblastomas from oligodendrogliomas, and determining high/low grade prediction, respectively, but showed poor performance in distinguishing oligodendrogliomas from astrocytomas (accuracy 63%, AUC 0.63). The sensitivity analysis affirmed the robustness of the APTw signal and APTw-derived radiomics prediction models.

CONCLUSION

APTw imaging, along with its derived radiomics, presents a promising quantitative approach for prediction IDH mutation and grading adult-type diffuse glioma.

CLINICAL RELEVANCE STATEMENT

Amide proton transfer-weighted imaging, a quantitative imaging biomarker, coupled with its derived radiomics, offers a promising non-invasive approach for predicting IDH mutation status and grading adult-type diffuse gliomas, thereby informing individualized clinical diagnostics and treatment strategies.

KEY POINTS

• This study evaluates the differences of different amide proton transfer-weighted metrics across three molecular subtypes and their efficacy in classifying adult-type diffuse glioma. • Chemical exchange saturation transfer ratio normalized with the reference value and relaxation-compensated inverse magnetization transfer ratio effectively predicts IDH mutation/grading, notably the first one. • Amide proton transfer-weighted imaging and its derived radiomics holds potential to be used as a diagnostic tool in routine clinical characterizing adult-type diffuse glioma.

The Potential of the Fibronectin Inhibitor Arg-Gly-Asp-Ser in the Development of Therapies for Glioblastoma

Glioblastoma (GBM) is the most lethal and common malignant primary brain tumor in adults. An important feature that supports GBM aggressiveness is the unique composition of its extracellular matrix (ECM). Particularly, fibronectin plays an important role in cancer cell adhesion, differentiation, proliferation, and chemoresistance. Thus, herein, a hydrogel with mechanical properties compatible with the brain and the ability to disrupt the dynamic and reciprocal interaction between fibronectin and tumor cells was produced. High-molecular-weight hyaluronic acid (HMW-HA) functionalized with the inhibitory fibronectin peptide Arg-Gly-Asp-Ser (RGDS) was used to produce the polymeric matrix. Liposomes encapsulating doxorubicin (DOX) were also included in the hydrogel to kill GBM cells. The resulting hydrogel containing liposomes with therapeutic DOX concentrations presented rheological properties like a healthy brain. In vitro assays demonstrated that unmodified HMW-HA hydrogels only caused GBM cell killing after DOX incorporation. Conversely, RGDS-functionalized hydrogels displayed per se cytotoxicity. As GBM cells produce several proteolytic enzymes capable of disrupting the peptide-HA bond, we selected MMP-2 to illustrate this phenomenon. Therefore, RGDS internalization can induce GBM cell apoptosis. Importantly, RGDS-functionalized hydrogel incorporating DOX efficiently damaged GBM cells without affecting astrocyte viability, proving its safety. Overall, the results demonstrate the potential of the RGDS-functionalized hydrogel to develop safe and effective GBM treatments.

Engineered exosomes with enhanced stability and delivery efficiency for glioblastoma therapy

Due to the blood-brain barrier (BBB), the application of chemical drugs for glioblastoma treatment is severely limited. Recently, exosomes have been widely applied for drug delivery to the brain. However, the differences in brain targeting efficiency among exosomes derived from different cell sources, as well as the premature drug leakage during circulation, still limit the therapeutic efficacy. Here, we designed a functional oligopeptide-modified exosome loaded with doxorubicin (Pep2-Exos-DOX) for glioblastoma treatment. BV2 mouse microglial cell line was selected as the exosome source due to the favorable BBB penetration. To avoid drug release in the circulation, a redox-response oligopeptide was designed for incorporation into the membranes of exosomes to lock the drug during circulation. The enrichment of the drug in glioblastoma was confirmed. Pharmacodynamic evaluation showed Pep2-Exos-DOX possessed significant anti-cancer activity against glioblastoma as well as relative biosafety. This exosome-based drug delivery system modified with redox-response oligopeptides provides us a novel strategy for brain diseases treatment.

Repeat surgery of recurrent glioma for molecularly informed treatment in the age of precision oncology: A risk-benefit analysis

PURPOSE

Surgery for recurrent glioma provides cytoreduction and tissue for molecularly informed treatment. With mostly heavily pretreated patients involved, it is unclear whether the benefits of repeat surgery outweigh its potential risks.

METHODS

Patients receiving surgery for recurrent glioma WHO grade 2-4 with the goal of tissue sampling for targeted therapies were analyzed retrospectively. Complication rates (surgical, neurological) were compared to our institutional glioma surgery cohort. Tissue molecular diagnostic yield, targeted therapies and post-surgical survival rates were analyzed.

RESULTS

Between 2017 and 2022, tumor board recommendation for targeted therapy through molecular diagnostics was made for 180 patients. Of these, 70 patients (38%) underwent repeat surgery. IDH-wildtype glioblastoma was diagnosed in 48 patients (69%), followed by IDH-mutant astrocytoma (n = 13; 19%) and oligodendroglioma (n = 9; 13%). Gross total resection (GTR) was achieved in 50 patients (71%). Tissue was processed for next-generation sequencing in 64 cases (91%), and for DNA methylation analysis in 58 cases (83%), while immunohistochemistry for mTOR phosphorylation was performed in 24 cases (34%). Targeted therapy was recommended in 35 (50%) and commenced in 21 (30%) cases. Postoperatively, 7 patients (11%) required revision surgery, compared to 7% (p = 0.519) and 6% (p = 0.359) of our reference cohorts of patients undergoing first and second craniotomy, respectively. Non-resolving neurological deterioration was documented in 6 cases (10% vs. 8%, p = 0.612, after first and 4%, p = 0.519, after second craniotomy). Median survival after repeat surgery was 399 days in all patients and 348 days in GBM patients after repeat GTR.

CONCLUSION

Surgery for recurrent glioma provides relevant molecular diagnostic information with a direct consequence for targeted therapy under a reasonable risk of postoperative complications. With satisfactory postoperative survival it can therefore complement a multi-modal glioma therapy approach.

Apigenin and Temozolomide Synergistically Inhibit Glioma Growth Through the PI3K/AKT Pathway

Background: Glioma is a devastating disease with the worst prognosis among human malignant tumors. Although temozolomide (TMZ) improves the overall survival of glioma patients, there are still many glioma patients who are resistant to TMZ. In this study, we focused on the effect of apigenin (API) and TMZ on glioma cells in vitro and in vivo, and we studied the underlying molecular mechanisms. Materials and Methods: To investigate the effect of API on glioblastoma cell proliferation, cell viability was assessed after glioma cells were incubated with various concentrations of API with or without TMZ using MTT assays. Then, we explored the synergistic effect of API and TMZ on glioma cell cycle, apoptosis, and migration. To investigate the molecular mechanism behind the synergism of API and TMZ, we examined the related genes of the major signaling pathways involved in glioma pathogenesis by Western blotting. Results: In this study, we found that API significantly suppressed the proliferation of glioma cells in a dose- and time-dependent manner. Combining API and TMZ significantly induced glioma cells arrest at the G2 phase and inhibited glioma cells proliferation compared with API or TMZ alone. In addition, API promoted the ability of TMZ to induce glioma cells apoptosis and inhibit glioma cells invasion. Furthermore, compared with treatment with individual agents, the combination of API and TMZ significantly inhibited the growth of subcutaneous tumors in mice. These results implied that API could synergistically suppress the growth of glioma cells when combined with TMZ. Combining API and TMZ significantly inhibited the protein expression of p-AKT, cyclin D1, Bcl-2, Matrix Metallopeptidase 2, and Matrix Metallopeptidase 9. Conclusion: API and TMZ synergistically inhibited glioma growth through the PI3K/AKT pathway.

Analysis of Histomorphologic/Molecular Association and Immune Checkpoint Regulators in Epithelioid Glioblastoma and Pleomorphic Xanthoastrocytoma: Are These Tumors Potential Candidates for Immune Checkpoint Blockade?

Accurate diagnosis of Epithelioid glioblastoma (eGB) and pleomorphic xanthoastrocytoma (PXA) is sometimes challenging owing to overlapping histologic and genetic features. There are limited reports on the immune profile of these tumors. In this study, we assessed 21 PXA [15 PXA Grade 2 (PXAG2); 6 PXA Grade 3 (PXAG3)] and 14 eGB for their histopathological and molecular association. Further, their immune profile was compared with GB, IDH1 wild-type (wt) (n-18). Morphologically, PXAG2 mostly differed from eGB; however, it was occasionally difficult to differentiate PXAG3 from eGB due to their epithelioid pattern and less obvious degenerative features. PXAG2 showed predominantly diffuse, whereas variable positivity for epithelial and glial markers was seen in PXAG3 and eGB. All cases showed retained nuclear ATRX and INI-1 . H3K27M or IDH1 mutation was seen in none. P53 mutation was more common in eGB, followed by PXAG3, and least common in PXAG2. BRAF V600E mutation was observed in 66.67% PXAG2, 33.33% PXAG3, and 50% eGB, with 100% concordance between immunohistochemistry (IHC) and sequencing. Thirty-six percent eGB, 33% PXAG3, and 61% PXAG2 harbored CDKN2A homozygous deletion. EGFR amplification was observed in 14% eGB and 66% of GB, IDH wt. PDL1 and CTLA-4 expression was higher in eGB (71.4% and 57.1%), PXAG3 (66.6% and100%), and PXAG2 (60% & 66.7%) as compared with GB, IDH wt (38.8% and 16.7%). Tumor-infiltrating lymphocytes were also observed in a majority of eGB and PXA (90% to 100%) in contrast to GB, IDH wt (66%). This analysis highlights the homogenous molecular and immune profile of eGB and PXA, suggesting the possibility that histologically and molecularly, these two entities represent 2 ends of a continuous spectrum with PXAG3 lying in between. Higher upregulation of PDL1, CTLA-4, and increased tumor infiltrating lymphocytes in these tumors as compared with GB, IDH wt suggests potential candidature for immunotherapy.

Glioblastoma vaccines: past, present, and opportunities

Glioblastoma (GBM) is one of the most lethal central nervous systems (CNS) tumours in adults. As supplements to standard of care (SOC), various immunotherapies improve the therapeutic effect in other cancers. Among them, tumour vaccines can serve as complementary monotherapy or boost the clinical efficacy with other immunotherapies, such as immune checkpoint blockade (ICB) and chimeric antigen receptor T cells (CAR-T) therapy. Previous studies in GBM therapeutic vaccines have suggested that few neoantigens could be targeted in GBM due to low mutation burden, and single-peptide therapeutic vaccination had limited efficacy in tumour control as monotherapy. Combining diverse antigens, including neoantigens, tumour-associated antigens (TAAs), and pathogen-derived antigens, and optimizing vaccine design or vaccination strategy may help with clinical efficacy improvement. In this review, we discussed current GBM therapeutic vaccine platforms, evaluated and potential antigenic targets, current challenges, and perspective opportunities for efficacy improvement.

Exosomal long non-coding RNAs in glioblastoma

Glioblastoma multiforme (GBM) is the most prevalent primary tumor found in the central nervous system, accounting for 70% of all adult brain tumors. The median overall survival rate is one year post-diagnosis with treatment, and only four months without treatment. Current GBM diagnostic methods, such as magnetic resonance imaging (MRI), surgery, and brain biopsies, have limitations. These include difficulty distinguishing between tumor recurrence and post-surgical necrotic regions, and operative risks associated with obtaining histological samples through direct surgery or biopsies. Consequently, there is a need for rapid, inexpensive, and minimally invasive techniques for early diagnosis and improved subsequent treatment. Research has shown that tumor-derived exosomes containing various long non-coding RNAs (lncRNAs) play critical regulatory roles in immunomodulation, cancer metastasis, cancer development, and drug resistance in GBM. They regulate genes that enhance cancer growth and progression and alter the expression of several key signaling pathways. Due to the specificity and sensitivity of exosomal lncRNAs, they have the potential to be used as biomarkers for early diagnosis and prognosis, as well as to monitor a patient's response to chemotherapy for GBM. In this review, we discuss the role of exosomal lncRNAs in the pathogenesis of GBM and their potential clinical applications for early diagnosis.

Carcinoembryonic antigen-expressing oncolytic measles virus derivative in recurrent glioblastoma: a phase 1 trial

Measles virus (MV) vaccine strains have shown significant preclinical antitumor activity against glioblastoma (GBM), the most lethal glioma histology. In this first in human trial (NCT00390299), a carcinoembryonic antigen-expressing oncolytic measles virus derivative (MV-CEA), was administered in recurrent GBM patients either at the resection cavity (Group A), or, intratumorally on day 1, followed by a second dose administered in the resection cavity after tumor resection on day 5 (Group B). A total of 22 patients received study treatment, 9 in Group A and 13 in Group B. Primary endpoint was safety and toxicity: treatment was well tolerated with no dose-limiting toxicity being observed up to the maximum feasible dose (2×107 TCID50). Median OS, a secondary endpoint, was 11.6 mo and one year survival was 45.5% comparing favorably with contemporary controls. Other secondary endpoints included assessment of viremia, MV replication and shedding, humoral and cellular immune response to the injected virus. A 22 interferon stimulated gene (ISG) diagonal linear discriminate analysis (DLDA) classification algorithm in a post-hoc analysis was found to be inversely (R = -0.6, p = 0.04) correlated with viral replication and tumor microenvironment remodeling including proinflammatory changes and CD8 + T cell infiltration in post treatment samples. This data supports that oncolytic MV derivatives warrant further clinical investigation and that an ISG-based DLDA algorithm can provide the basis for treatment personalization.

Differential Expression of SRY-Related HMG-Box Transcription Factor 2, Oligodendrocyte Lineage Transcription Factor 2, and Zinc Finger E-Box Binding Homeobox 1 in Serum-Derived Extracellular Vesicles: Implications for Mithramycin Sensitivity and Targeted Therapy in High-Grade Glioma

Glioblastoma multiforme (GBM) is the most aggressive type of glioma and is often resistant to traditional therapies. Evidence suggests that glioma stem cells (GSCs) contribute to this resistance. Mithramycin (Mit-A) targets GSCs and exhibits antitumor activity in GBM by affecting transcriptional targets such as SRY-related HMG-box transcription factor 2 (SOX2), oligodendrocyte lineage transcription factor 2 (OLIG2), and zinc finger E-box binding homeobox 1 (ZEB1). However, its clinical use has been limited by toxicity. This study explored the diagnostic potential of serum extracellular vesicles (EVs) to identify Mit-A responders. Serum EVs were isolated from 70 glioma patients, and targeted gene expression was analyzed using qRT-PCR. Using chemosensitivity assay, we identified 8 Mit-A responders and 17 nonresponders among 25 glioma patients. The M-score showed a significant correlation (p = 0.045) with isocitrate dehydrogenase 1 mutation but not other clinical variables. The genes SOX2 (p = 0.005), OLIG2 (p = 0.003), and ZEB1 (p = 0.0281) were found to be upregulated in the responder EVs. SOX2 had the highest diagnostic potential (AUC = 0.875), followed by OLIG2 (AUC = 0.772) and ZEB1 (AUC = 0.632).The combined gene panel showed significant diagnostic efficacy (AUC = 0.956) through logistic regression analysis. The gene panel was further validated in the serum EVs of 45 glioma patients. These findings highlight the potential of Mit-A as a targeted therapy for high-grade glioma based on differential gene expression in serum EVs. The gene panel could serve as a diagnostic tool to predict Mit-A sensitivity, offering a promising approach for personalized treatment strategies and emphasizing the role of GSCs in therapeutic resistance.

Advancements in Glioma Care: Focus on Emerging Neurosurgical Techniques

BACKGROUND

Despite significant advances in understanding the molecular pathways of glioma, translating this knowledge into effective long-term solutions remains a challenge. Indeed, gliomas pose a significant challenge to neurosurgical oncology because of their diverse histopathological features, genetic heterogeneity, and clinical manifestations. Relevant sections: This study focuses on glioma complexity by reviewing recent advances in their management, also considering new classification systems and emerging neurosurgical techniques. To bridge the gap between new neurosurgical approaches and standards of care, the importance of molecular diagnosis and the use of techniques such as laser interstitial thermal therapy (LITT) and focused ultrasound (FUS) are emphasized, exploring how the integration of molecular knowledge with emerging neurosurgical approaches can personalize and improve the treatment of gliomas.

CONCLUSIONS

The choice between LITT and FUS should be tailored to each case, considering factors such as tumor characteristics and patient health. LITT is favored for larger, complex tumors, while FUS is standard for smaller, deep-seated ones. Both techniques are equally effective for small and superficial tumors. Our study provides clear guidance for treating pediatric low-grade gliomas and highlights the crucial roles of LITT and FUS in managing high-grade gliomas in adults. This research sets the stage for improved patient care and future developments in the field of neurosurgery.

Radiomic texture analysis based on neurite orientation dispersion and density imaging to differentiate glioblastoma from solitary brain metastasis

BACKGROUND

We created discriminative models of different regions of interest (ROIs) using radiomic texture features of neurite orientation dispersion and density imaging (NODDI) and evaluated the feasibility of each model in differentiating glioblastoma multiforme (GBM) from solitary brain metastasis (SBM).

METHODS

We conducted a retrospective study of 204 patients with GBM (n = 146) or SBM (n = 58). Radiomic texture features were extracted from five ROIs based on three metric maps (intracellular volume fraction, orientation dispersion index, and isotropic volume fraction of NODDI), including necrosis, solid tumors, peritumoral edema, tumor bulk volume (TBV), and abnormal bulk volume. Four feature selection methods and eight classifiers were used for the radiomic texture feature selection and model construction. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the models. Routine magnetic resonance imaging (MRI) radiomic texture feature models generated in the same manner were used for the horizontal comparison.

RESULTS

NODDI-radiomic texture analysis based on TBV subregions exhibited the highest accuracy (although nonsignificant) in differentiating GBM from SBM, with area under the ROC curve (AUC) values of 0.918 and 0.882 in the training and test datasets, respectively, compared to necrosis (AUCtraining:0.845, AUCtest:0.714), solid tumor (AUCtraining:0.852, AUCtest:0.821), peritumoral edema (AUCtraining:0.817, AUCtest:0.762), and ABV (AUCtraining:0.834, AUCtest:0.779). The performance of the five ROI radiomic texture models in routine MRI was inferior to that of the NODDI-radiomic texture model.

CONCLUSION

Preoperative NODDI-radiomic texture analysis based on TBV subregions shows great potential for distinguishing GBM from SBM.

Synergistic effect of cryptotanshinone and temozolomide treatment against human glioblastoma cells

Glioblastoma multiforme (GBM) is a complex disease to treat owing to its profound chemoresistance. Therefore, we evaluated the combined effect and therapeutic efficacy of temozolomide (TMZ), a potent alkylating agent and the current gold standard therapy for GBM, and cryptotanshinone (CTS), which inhibits glioma cell proliferation in GBM cells. Using LN229 and U87-MG human GBM cells in a short-term stimulation in vitro model, the cytotoxic and anti-proliferative effects of single and combined treatment with 4 μM CTS and 200 μM TMZ were investigated. Furthermore, cell viability, DNA damage, apoptosis rate, and signal transducer and activator of transcription 3 (STAT3) protein were measured using cytotoxic assay, comet assay, flow cytometry, and western blotting analysis, respectively. The two drugs' synergistic interaction was validated using the synergy score. We found that the anti-proliferative effects of combination therapy using the two drugs were greater than that of each agent used alone (CTS or TMZ). Western blot analysis indicated that treatment of GBM cells with CTS combined with TMZ more significantly decreased the expression of MGMT and STAT3, than that with TMZ alone. Combined treatment with CTS and TMZ might be an effective option to overcome the chemoresistance of GBM cells in a long-term treatment strategy.

Chemotherapy in pediatric brain tumor and the challenge of the blood-brain barrier

BACKGROUND

Pediatric brain tumors (PBT) stand as the leading cause of cancer-related deaths in children. Chemoradiation protocols have improved survival rates, even for non-resectable tumors. Nonetheless, radiation therapy carries the risk of numerous adverse effects that can have long-lasting, detrimental effects on the quality of life for survivors. The pursuit of chemotherapeutics that could obviate the need for radiotherapy remains ongoing. Several anti-tumor agents, including sunitinib, valproic acid, carboplatin, and panobinostat, have shown effectiveness in various malignancies but have not proven effective in treating PBT. The presence of the blood-brain barrier (BBB) plays a pivotal role in maintaining suboptimal concentrations of anti-cancer drugs in the central nervous system (CNS). Ongoing research aims to modulate the integrity of the BBB to attain clinically effective drug concentrations in the CNS. However, current findings on the interaction of exogenous chemical agents with the BBB remain limited and do not provide a comprehensive explanation for the ineffectiveness of established anti-cancer drugs in PBT.

METHODS

We conducted our search for chemotherapeutic agents associated with the blood-brain barrier (BBB) using the following keywords: Chemotherapy in Cancer, Chemotherapy in Brain Cancer, Chemotherapy in PBT, BBB Inhibition of Drugs into CNS, Suboptimal Concentration of CNS Drugs, PBT Drugs and BBB, and Potential PBT Drugs. We reviewed each relevant article before compiling the information in our manuscript. For the generation of figures, we utilized BioRender software.

FOCUS

We focused our article search on chemical agents for PBT and subsequently investigated the role of the BBB in this context. Our search criteria included clinical trials, both randomized and non-randomized studies, preclinical research, review articles, and research papers.

FINDING

Our research suggests that, despite the availability of potent chemotherapeutic agents for several types of cancer, the effectiveness of these chemical agents in treating PBT has not been comprehensively explored. Additionally, there is a scarcity of studies examining the role of the BBB in the suboptimal outcomes of PBT treatment, despite the effectiveness of these drugs for other types of tumors.

Identification of immune-related hub genes and construction of an immune-related gene prognostic index for low-grade glioma

Low-grade glioma (LGG) poses significant management challenges and has a dismal prognosis. While immunotherapy has shown significant promise in cancer treatment, its progress in glioma has confronted with challenges. In our study, we aimed to develop an immune-related gene prognostic index (IRGPI) which could be used to evaluate the response and efficacy of LGG patients with immunotherapy. We included a total of 529 LGG samples from TCGA database and 1152 normal brain tissue samples from the GTEx database. Immune-related differentially expressed genes (DEGs) were screened. Then, we used weighted gene co-expression network analysis (WGCNA) to identify immune-related hub genes in LGG patients and performed Cox regression analysis to construct an IRGPI. The median IRGPI was used as the cut-off value to categorize LGG patients into IRGPI-high and low subgroups, and the molecular and immune mechanism in IRGPI-defined subgroups were analysed. Finally, we explored the relationship between IRGPI-defined subgroups and immunotherapy related indicators in patients after immunotherapy. Three genes (RHOA, NFKBIA and CCL3) were selected to construct the IRGPI. In a survival analysis using TCGA cohort as a training set, patients in the IRGPI-low subgroup had a better OS than those in IRGPI-high subgroup, consistent with the results in CGGA cohort. The comprehensive results showed that IRGPI-low subgroup had a more abundant activated immune cell population and lower TIDE score, higher MSI, higher TMB score, lower T cell dysfunction score, more likely benefit from ICIs therapy. IRGPI is a promising biomarker in the field of LGG ICIs therapy to distinguish the prognosis, the molecular and immunological characteristics of patients.

Protumorigenic role of the atypical cadherin FAT1 by the suppression of PDCD10 via RelA/miR221-3p/222-3p axis in glioblastoma

The atypical cadherin FAT1 function either as a pro or antitumorigenic in tumors of different tissue origins. Our group previously demonstrated the protumorigenic nature of FAT1 signaling in glioblastoma (GBM). In this study, we investigated how FAT1 influences the expression of clustered oncomiRs (miR-221-3p/miR-222-3p) and their downstream effects in GBM. Through several experiments involving the measurement of specific gene/microRNA expression, gene knockdowns, protein and cellular assays, we have demonstrated a novel oncogenic signaling pathway mediated by FAT1 in glioma. These results have been verified using antimiRs and miR-mimic assays. Initially, in glioma-derived cell lines (U87MG and LN229), we observed FAT1 as a novel up-regulator of the transcription factor NFκB-RelA. RelA then promotes the expression of the clustered-oncomiRs, miR-221-3p/miR-222-3p, which in turn suppresses the expression of the tumor suppressor gene (TSG), PDCD10 (Programmed cell death protein10). The suppression of PDCD10, and other known TSG targets (PTEN/PUMA), by miR-221-3p/miR-222-3p, leads to increased clonogenicity, migration, and invasion of glioma cells. Consistent with our in-vitro findings, we observed a positive expression correlation of FAT1 and miR-221-3p, and an inverse correlation of FAT1 and the miR-targets (PDCD10/PTEN/PUMA), in GBM tissue-samples. These findings were also supported by publicly available GBM databases (The Cancer Genome Atlas [TCGA] and The Repository of Molecular Brain Neoplasia Data [Rembrandt]). Patients with tumors displaying high levels of FAT1 and miR-221-3p expression (50% and 65% respectively) experienced shorter overall survival. Similar results were observed in the TCGA-GBM database. Thus, our findings show a novel FAT1/RelA/miR-221/miR-222 oncogenic-effector pathway that downregulates the TSG, PDCD10, in GBM, which could be targeted therapeutically in a specific manner.

European Cancer Organisation Essential Requirements for Quality Cancer Care: Adult glioma

European Cancer Organisation Essential Requirements for Quality Cancer Care (ERQCCs) are explanations of the organisation and actions necessary to provide high-quality care to patients with a specific cancer type. They are compiled by a working group of European experts representing disciplines involved in cancer care, and provide oncology teams, patients, policymakers and managers with an overview of the essential requirements in any healthcare system. The focus here is on adult glioma. Gliomas make up approximately 80% of all primary malignant brain tumours. They are highly diverse and patients can face a unique cognitive, physical and psychosocial burden, so personalised treatments and support are essential. However, management of gliomas is currently very heterogeneous across Europe and there are only few formally-designated comprehensive cancer centres with brain tumour programmes. To address this, the ERQCC glioma expert group proposes frameworks and recommendations for high quality care, from diagnosis to treatment and survivorship. Wherever possible, glioma patients should be treated from diagnosis onwards in high volume neurosurgical or neuro-oncology centres. Multidisciplinary team working and collaboration is essential if patients' length and quality of life are to be optimised.

Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas

Objective

This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2-4) from 3 different centers.

Methods

To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space.

Results

The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively.

Conclusion

The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.

The STEMRI trial: Magnetic resonance spectroscopy imaging can define tumor areas enriched in glioblastoma stem-like cells

Despite maximally safe resection of the magnetic resonance imaging (MRI)-defined contrast-enhanced (CE) central tumor area and chemoradiotherapy, most patients with glioblastoma (GBM) relapse within a year in peritumoral FLAIR regions. Magnetic resonance spectroscopy imaging (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (choline/N-acetyl-aspartate index >2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSCs), CNI+ areas might be GSC enriched. In this prospective trial, 16 patients with GBM underwent MRSI/MRI before surgery/chemoradiotherapy to investigate GSC content in CNI-/+ biopsies from CE/FLAIR. Biopsy and derived-GSC characterization revealed a FLAIR/CNI+ sample enrichment in GSC and in gene signatures related to stemness, DNA repair, adhesion/migration, and mitochondrial bioenergetics. FLAIR/CNI+ samples generate GSC-enriched neurospheres faster than FLAIR/CNI-. Parameters assessing biopsy GSC content and time-to-neurosphere formation in FLAIR/CNI+ were associated with worse patient outcome. Preoperative MRI/MRSI would certainly allow better resection and targeting of FLAIR/CNI+ areas, as their GSC enrichment can predict worse outcomes.

The impact of short-course hypofractionated radiotherapy on multimodality treatment utilisation, compliance, and outcome in glioblastoma patients: a Danish patterns of care study

BACKGROUND

The aim of this retrospective registry-based Danish patterns of care study was (1) to evaluate the real-world utilisation of short-course hypofractionated radiotherapy (HFRT) in glioblastoma (GBM) patients over time, and (2) to evaluate the impact of short-course HFRT by assessing trends in multimodality treatment utilisation, compliance, and outcome.

MATERIAL AND METHODS

Data of all adults with newly diagnosed pathology-confirmed GBM between 2011 and 2019 were extracted from the nationwide Danish Neuro-Oncology Registry. Short-course HFRT was defined as a fraction size of > 2 Gy to a planned dose of > 30 Gy. Patterns of care were assessed. To analyse trends in the assignment to short-course HFRT, and in radiotherapy (RT) compliance, multivariable logistic regression was applied. To analyse trends in survival, multivariable Cox regression was used.

RESULTS

In this cohort of 2416 GBM patients, the utilisation of short-course HFRT significantly increased from ca. 10% in 2011 to 33% in recent years. This coincided with the discontinued use of palliative regimens and a decreased use of conventional fractionation. The proportion of patients proceeding to RT remained stable at ca. 85%. The proportion of patients assigned to chemoradiotherapy (CRT) remained stable at ca. 60%; the use of short-course hypofractionated CRT increased with ca. 10%, while the use of conventionally fractionated CRT decreased with ca. 10%. Compliance with conventionally fractionated and short-course HFRT was respective 92% and 93%, and significantly increasing in recent years. In the complete cohort, the median overall survival remained stable at ca. 11 months. Assignment to short-course HFRT was independently associated with shorter survival.

CONCLUSION

In Denmark, the use of short-course HFRT significantly increased in recent years. Nonetheless, the overall utilisation of RT and chemotherapy did not increase on a population level. Nor did survival change. In contrast, compliance with both conventionally fractionated RT and short-course HFRT increased.

Modern preoperative imaging and functional mapping in patients with intracranial glioma

Magnetic resonance imaging (MRI) in therapy-naïve intracranial glioma is paramount for neuro-oncological diagnostics, and it provides images that are helpful for surgery planning and intraoperative guidance during tumor resection, including assessment of the involvement of functionally eloquent brain structures. This study reviews emerging MRI techniques to depict structural information, diffusion characteristics, perfusion alterations, and metabolism changes for advanced neuro-oncological imaging. In addition, it reflects current methods to map brain function close to a tumor, including functional MRI and navigated transcranial magnetic stimulation with derived function-based tractography of subcortical white matter pathways. We conclude that modern preoperative MRI in neuro-oncology offers a multitude of possibilities tailored to clinical needs, and advancements in scanner technology (e. g., parallel imaging for acceleration of acquisitions) make multi-sequence protocols increasingly feasible. Specifically, advanced MRI using a multi-sequence protocol enables noninvasive, image-based tumor grading and phenotyping in patients with glioma. Furthermore, the add-on use of preoperatively acquired MRI data in combination with functional mapping and tractography facilitates risk stratification and helps to avoid perioperative functional decline by providing individual information about the spatial location of functionally eloquent tissue in relation to the tumor mass. KEY POINTS::   · Advanced preoperative MRI allows for image-based tumor grading and phenotyping in glioma.. · Multi-sequence MRI protocols nowadays make it possible to assess various tumor characteristics (incl. perfusion, diffusion, and metabolism).. · Presurgical MRI in glioma is increasingly combined with functional mapping to identify and enclose individual functional areas.. · Advancements in scanner technology (e. g., parallel imaging) facilitate increasing application of dedicated multi-sequence imaging protocols.. CITATION FORMAT: · Sollmann N, Zhang H, Kloth C et al. Modern preoperative imaging and functional mapping in patients with intracranial glioma. Fortschr Röntgenstr 2023; 195: 989 - 1000.

Nanoparticles Mediated the Diagnosis and Therapy of Glioblastoma: Bypass or Cross the Blood-Brain Barrier

Glioblastoma is one of the most aggressive central nervous system malignancies with high morbidity and mortality. Current clinical approaches, including surgical resection, radiotherapy, and chemotherapy, are limited by the difficulty of targeting brain lesions accurately, leading to disease recurrence and fatal outcomes. The lack of effective treatments has prompted researchers to continuously explore novel therapeutic strategies. In recent years, nanomedicine has made remarkable progress and expanded its application in brain drug delivery, providing a new treatment for brain tumors. Against this background, this article reviews the application and progress of nanomedicine delivery systems in brain tumors. In this paper, the mechanism of nanomaterials crossing the blood-brain barrier is summarized. Furthermore, the specific application of nanotechnology in glioblastoma is discussed in depth.

Rewiring of cortical glucose metabolism fuels human brain cancer growth

The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of 13 C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth.

Significance

This study is the first to directly measure biosynthetic flux in both glioma and cortical tissue in human brain cancer patients. Brain tumors rewire glucose carbon utilization away from oxidation and neurotransmitter production towards biosynthesis to fuel growth. Blocking these metabolic adaptations with dietary interventions slows brain cancer growth with minimal effects on cortical metabolism.

Prognostic nomogram for glioblastoma (GBM) patients presenting with distant extension: a seer-based study

BACKGROUND

Glioblastoma (GBM) with distant extension is rarely reported. We retrieved the data of GBM patients from the SEER database to identify the prognostic factors of GBM with distant extension and constructed a nomogram to predict the overall survival (OS) of these patients.

METHODS

The data of GBM patients between 2003 and 2018 were retrieved from the SEER Database. 181 GBM patients with distant extension were randomly divided into the training cohort (n = 129) and the validation cohort (n = 52) at a ratio of 7:3. The prognostic factors associated with the OS of the GBM patients were identified through univariate and multivariate cox analyses. A nomogram was constructed based on the training cohort to predict OS, and its clinical value was verified using the validation cohort data.

RESULTS

Kaplan-Meier curves showed that the prognosis was significantly worse for GBM patients with distant extension than GBM patients without distant extension. Stage (GBM patients with distant extension) was independent prognostic factor of survival. Multivariate Cox analyses demonstrated that age, surgery, radiotherapy and chemotherapy were independent risk factors for OS of GBM patients presenting with distant extension. The C-indexes of the nomogram for predicting OS were 0.755 (95% CI 0.713-0.797) and 0.757 (95% CI 0.703-0.811) for the training and validation cohorts, respectively. The calibration curves of both cohorts showed good consistency. The area under the curve (AUC) for predicting 0.25-year, 0.5-year and 1-year OS in the training cohort were 0.793, 0.864 and 0.867, respectively, and that in the validation cohort were 0.845, 0.828 and 0.803, respectively. The decision curve analysis (DCA) curves showed that the model to predict the 0.25-year, 0.5-year and 1-year OS probabilities was good.

CONCLUSION

Stage (GBM patients with distant extension) is independent prognostic factor for GBM patients. Age, surgery, radiotherapy and chemotherapy are independent prognostic factors for GBM patients presenting with distant extension, and the nomogram based on these factors can accurately predict the 0.25-year, 0.5-year and 1-year OS of these patients.

Dendritic cell vaccine of gliomas: challenges from bench to bed

Gliomas account for the majority of brain malignant tumors. As the most malignant subtype of glioma, glioblastoma (GBM) is barely effectively treated by traditional therapies (surgery combined with radiochemotherapy), resulting in poor prognosis. Meanwhile, due to its "cold tumor" phenotype, GBM fails to respond to multiple immunotherapies. As its capacity to prime T cell response, dendritic cells (DCs) are essential to anti-tumor immunity. In recent years, as a therapeutic method, dendritic cell vaccine (DCV) has been immensely developed. However, there have long been obstacles that limit the use of DCV yet to be tackled. As is shown in the following review, the role of DCs in anti-tumor immunity and the inhibitory effects of tumor microenvironment (TME) on DCs are described, the previous clinical trials of DCV in the treatment of GBM are summarized, and the challenges and possible development directions of DCV are analyzed.

Hypofractionated Stereotactic Re-irradiation and Anti-PDL1 Durvalumab Combination in Recurrent Glioblastoma: STERIMGLI Phase I Results

BACKGROUND

Hypofractionated stereotactic radiotherapy (hFSRT) is a salvage option for recurrent glioblastoma (GB) which may synergize anti-PDL1 treatment. This phase I study evaluated the safety and the recommended phase II dose of anti-PDL1 durvalumab combined with hFSRT in patients with recurrent GB.

METHODS

Patients were treated with 24 Gy, 8 Gy per fraction on days 1, 3, and 5 combined with the first 1500 mg Durvalumab dose on day 5, followed by infusions q4weeks until progression or for a maximum of 12 months. A standard 3 + 3 Durvalumab dose de-escalation design was used. Longitudinal lymphocytes count, cytokines analyses on plasma samples, and magnetic resonance imaging (MRI) were collected.

RESULTS

Six patients were included. One dose limiting toxicity, an immune-related grade 3 vestibular neuritis related to Durvalumab, was reported. Median progression-free interval (PFI) and overall survival (OS) were 2.3 and 16.7 months, respectively. Multi-modal deep 
learning-based analysis including MRI, cytokines, and lymphocytes/neutrophil ratio isolated the patients presenting pseudoprogression, the longest PFI and those with the longest OS, but statistical significance cannot be established considering phase I data only.

CONCLUSION

Combination of hFSRT and Durvalumab in recurrent GB was well tolerated in this phase I study. These encouraging results led to an ongoing randomized phase II. (ClinicalTrials.gov Identifier: NCT02866747).

Impact of timing of antiseizure medication withdrawal on seizure recurrence in glioma patients: a retrospective observational study

BACKGROUND

Withdrawal of antiseizure medication treatment (ASM) can be considered after completion of antitumour treatment in glioma patients who no longer suffer from seizures. We compared the risk for recurrent seizures after ASM withdrawal between patients with short-term, medium-term versus long-term seizure freedom after antitumour treatment.

METHODS

In this retrospective observational study, the primary outcome was time to recurrent seizure, from the starting date of no ASM treatment up to 36 months follow-up. Cox proportional hazards models were used to study the effect of risk factors on time to recurrent seizure. Stratification was done with information known at baseline. Short-term seizure freedom was defined as ≥ 3 months, but < 12 months; medium-term as 12-24 months; and long-term as ≥ 24 months seizure freedom from the date of last antitumour treatment.

RESULTS

This study comprised of 109 patients; 31% (34/109) were in the short-term, 29% (32/109) in the medium-term, and 39% (43/109) in the long-term group. A recurrent seizure was experienced by 47% (16/34) of the patients in the short-term, 31% (10/32) in the medium-term, and 44% (19/43) in the long-term group. Seizure recurrence risk was similar between patients in the short-term group as compared to the medium-term (cause-specific adjusted hazard ratio [aHR] = 0.65 [95%CI = 0.29-1.46]) and long-term group (cause-specific aHR = 1.04 [95%CI = 0.52-2.09]).

CONCLUSIONS

Seizure recurrence risk is relatively similar between patients with short-term, medium-term, and long-term seizure freedom after completion of antitumour treatment.

MR-guided LITT therapy in patients with primary irresectable glioblastoma: a prospective, controlled pilot study

PURPOSE

Laser interstitial thermal therapy (LITT) is increasingly being used in the treatment of brain tumors, whereas high-quality evidence of its effectiveness is lacking. This pilot examined the feasibility of conducting a randomized controlled trial (RCT) in patients with irresectable newly diagnosed glioblastoma (nGBM), and generated data on technical feasibility and safety.

METHODS

We included patients with irresectable nGBM with KPS ≥ 70 and feasible trajectories to ablate ≥ 70% of the tumor volume. Patients were initially randomized to receive either biopsy combined with LITT or biopsy alone, followed by chemoradiation (CRT). Randomization was stopped after 9 patients as the feasibility endpoint with respect to willingness to be randomized was met. Main endpoints were feasibility of performing an RCT, technical feasibility of LITT and safety. Follow-up was 3 months.

RESULTS

A total of 15 patients were included, of which 10 patients received a biopsy followed by LITT and 5 patients a biopsy. Most patients were able to complete the follow-up procedures (93% clinical, 86% questionnaires, 78% MRI). Patients were planned within 3 weeks after consultation (median 12 days, range 8-16) and no delay was observed in referring patients for CRT (median 37 days, range 28-61). Two CD ≥ 3 complications occurred in the LITT arm and none in the biopsy arm.

CONCLUSION

An RCT to study the effectiveness of LITT in patients with an irresectable nGBM seems feasible with acceptable initial safety data. The findings from this pilot study helped to further refine the design of a larger full-scale multicenter RCT in the Netherlands. Protocol and study identifier: The current study is registered at clinicaltrials.gov (EMITT pilot study, NTR: NCT04596930).

Diagnostic Approaches to Adult-Type Diffuse Glial Tumors: Comparative Literature and Clinical Practice Study

Gliomas are the most frequent intrinsic central nervous system tumors. The new 2021 WHO Classification of Central Nervous System Tumors brought significant changes into the classification of gliomas, that underline the role of molecular diagnostics, with the adult-type diffuse glial tumors now identified primarily by their biomarkers rather than histology. The status of the isocitrate dehydrogenase (IDH) 1 or 2 describes tumors at their molecular level and together with the presence or absence of 1p/19q codeletion are the most important biomarkers used for the classification of adult-type diffuse glial tumors. In recent years terminology has also changed. IDH-mutant, as previously known, is diagnostically used as astrocytoma and IDH-wildtype is used as glioblastoma. A comprehensive understanding of these tumors not only gives patients a more proper treatment and better prognosis but also highlights new difficulties. MR imaging is of the utmost importance for diagnosing and supervising the response to treatment. By monitoring the tumor on followup exams better results can be achieved. Correlations are seen between tumor diagnostic and clinical manifestation and surgical administration, followup care, oncologic treatment, and outcomes. Minimal resection site use of functional imaging (fMRI) and diffusion tensor imaging (DTI) have become indispensable tools in invasive treatment. Perfusion imaging provides insightful information about the vascularity of the tumor, spectroscopy shows metabolic activity, and nuclear medicine imaging displays tumor metabolism. To accommodate better treatment the differentiation of pseudoprogression, pseudoresponse, or radiation necrosis is needed. In this report, we present a literature review of diagnostics of gliomas, the differences in their imaging features, and our radiology's departments accumulated experience concerning gliomas.

Study protocol for a multicenter randomised controlled trial on the (cost)effectiveness of biopsy combined with same-session MR-guided LITT versus biopsy alone in patients with primary irresectable glioblastoma (EMITT trial)

BACKGROUND

Glioblastoma (GBM) is the most common primary, malignant brain tumour with a 5-year survival of 5%. If possible, a glioblastoma is resected and further treated with chemoradiation therapy (CRT), but resection is not feasible in about 30% of cases. Current standard of care in these cases is a biopsy followed by CRT. Magnetic resonance (MR) imaging-guided laser interstitial thermal therapy (LITT) has been suggested as a minimally invasive alternative when surgery is not feasible. However, high-quality evidence directly comparing LITT with standard of care is lacking, precluding any conclusions on (cost-)effectiveness. We therefore propose a multicenter randomized controlled study to assess the (cost-)effectiveness of MR-guided LITT as compared to current standard of care (EMITT trial).

METHODS AND ANALYSIS

The EMITT trial will be a multicenter pragmatic randomized controlled trial in the Netherlands. Seven Dutch hospitals will participate in this study. In total 238 patients will be randomized with 1:1 allocation to receive either biopsy combined with same-session MR-guided LITT therapy followed by CRT or the current standard of care being biopsy followed by CRT. The primary outcomes will be health-related quality of life (HR-QoL) (non-inferiority) using EORTC QLQ-C30 + BN20 scores at 5 months after randomization and overall survival (superiority). Secondary outcomes comprise cost-effectiveness (healthcare and societal perspective) and HR-QoL of life over an 18-month time horizon, progression free survival, tumour response, disease specific survival, longitudinal effects, effects on adjuvant treatment, ablation percentage and complication rates.

DISCUSSION

The EMITT trial will be the first RCT on the effectiveness of LITT in patients with glioblastoma as compared with current standard of care. Together with the Dutch Brain Tumour Patient association, we hypothesize that LITT may improve overall survival without substantially affecting patients' quality of life.

TRIAL REGISTRATION

This trial is registered at ClinicalTrials.gov (NCT05318612).

Label-Free Raman Spectromicroscopy Unravels the Relationship between MGMT Methylation and Intracellular Lipid Accumulation in Glioblastoma

Temozolomide (TMZ) is considered a first line chemotherapy drug for glioblastoma (GBM). Unfortunately, the GBM without methylation of O6-methylguanine-DNA methyltransferase (MGMT), accounting for about 70% of all GBM, shows an inherent resistance to TMZ treatment. Aberrant accumulation of neutral lipids, primarily triglycerides (TGs) and cholesteryl esters (CEs), in lipid droplets (LDs) has been recognized as metabolic vulnerability for GBM therapy. However, it is not known whether MGMT methylation affects lipid accumulation in GBM. Herein, we employed label-free Raman spectromicroscopy, which integrated stimulated Raman scattering (SRS) microscopy and confocal Raman spectroscopy, to quantitatively analyze both the amount and composition of intracellular LDs in intact GBM tissues obtained from patients who had undergone resection surgery. Our results showed significant reductions in both the LD amount and the CE percentage in MGMT unmethylated GBMs (MGMT methylation < 15%) compared to MGMT methylated ones (MGMT methylation ≥ 15%). Due to a big variation of lipid accumulation in the MGMT methylated GBMs, these patients were further divided into hypermethylated group (MGMT methylation ≥ 50%) and intermediate-methylated group (MGMT methylation 15∼50%), according to the significantly different median survival rates of these two groups. Remarkable differences in LD amount, CE percentage, and also lipid saturation degree were found between the hypermethylated group and the other two groups, but not between the unmethylated and intermediate-methylated groups. To elucidate the possible underlying mechanism, we analyzed the differential expression of lipid metabolism-related genes in GBM with different levels of MGMT methylation using The Cancer Genome Atlas Program (TCGA) dataset. It was shown that the genes related to lipid oxidation and lipid efflux were upregulated, and the genes related to lipid synthesis were downregulated in unmethylated group. These findings unravel the relationship between MGMT methylation and lipid accumulation in GBM, which may offer new opportunities for the diagnosis and treatment of TMZ-resistant GBM.

Targeting Wnt/β-catenin-mediated upregulation of oncogenic NLGN3 suppresses cancer stem cells in glioblastoma

Glioblastoma (GBM) is the most malignant tumor in brain and is highly resistant to therapy. Clinical evidence suggests increased number of cancer stem cells (CSCs) may contribute to the failure of conventional therapies, but the mechanisms associated with acquisition of CSC properties in GBM are not fully understood. We found that DAB2IP suppresses CSC properties by targeting the synaptic proteins neuroligin 3 (NLGN3) in GBM. Furthermore, we showed that GBM-derived NLGN3 has an oncogenic function by inducing CSC properties within GBM. Moreover, elevated NLGN3 transcription mediated by Wnt/β-catenin signaling pathway resulted in increased secretion of NLGN3 into the surrounding tumor microenvironment. Both condition media containing NLGN3 and recombinant NLGN3 transformed neighboring cells to CSCs, suggesting NLGN3 as a critical component inducing CSC properties. Furthermore, targeting NLGN3-bearing CSCs using upstream Wnt/β-catenin inhibitors synergistically enhances the efficacy of conventional treatment. Hence, we unveiled the series of regulatory mechanisms for acquisition of CSC properties in GBM progression by Wnt/β-catenin-mediated NLGN3. These results may provide a new targeting strategy to improve the therapeutic efficacy of GBM treatments.

The Impact of ioMRI on Glioblastoma Resection and Clinical Outcomes in a State-of-the-Art Neuro-Oncological Setup

Intraoperative magnetic resonance imaging (ioMRI) aims to improve gross total resection (GTR) in glioblastoma (GBM) patients. Despite some older randomized data on safety and feasibility, ioMRI's actual impact in a modern neurosurgical setting utilizing a larger armamentarium of techniques has not been sufficiently investigated to date. We therefore aimed to analyze its effects on residual tumor, patient outcome, and progression-free survival (PFS) in GBM patients in a modern high-volume center. Patients undergoing ioMRI for resection of supratentorial GBM were enrolled between March 2018 and June 2020. ioMRI was performed in all cases at the end of resection when surgeons expected complete macroscopic tumor removal. Extent of resection (EOR) was performed by volumetric analysis, with GTR defined as an EOR ≥ 95%, respectively. Progression-free survival (PFS) was analyzed through univariate and multivariate Cox proportional regression analyses. In total, we enrolled 172 patients. Mean EOR increased from 93.9% to 98.3% (p < 0.0001) due to ioMRI, equaling an increase in GTR rates from 78.5% to 93.0% (p = 0.0002). Residual tumor volume decreased from 1.3 ± 4.2 cm³ to 0.6 ± 2.5 cm³ (p = 0.0037). Logistic regression revealed recurrent GBM as a risk factor leading to subtotal resection (STR) (odds ratio (OR) = 3.047, 95% confidence interval (CI) 1.165-7.974, p = 0.023). Additional resection after ioMRI led to equally long PFS compared to patients with complete tumor removal before ioMRI (hazard ratio (HR) = 0.898, 95%-CI 0.543-1.483, p = 0.67). ioMRI considerably reduces residual tumor volume and helps to achieve comparable PFS, even in patients with unexpected residual tumor after initial resection before ioMRI.

Use Test of Automated Machine Learning in Cancer Diagnostics

Our aim is to investigate the added value of automated machine learning (AutoML) for potential future applications in cancer diagnostics. Using two important diagnostic questions, the non-invasive determination of IDH mutation status and ATRX status, we analyze whether it is possible to use AutoML to develop models that are comparable in performance to conventional machine learning models (ML) developed by experts. For this purpose, we develop AutoML models using different feature preselection methods and compare the results with previously developed conventional ML models. The cohort used for our study comprises T2-weighted MRI images of 124 patients with histologically confirmed gliomas. Using AutoML, we were able to develop sophisticated models in a very short time with only a few lines of computer code. In predicting IDH mutation status, we obtained a mean AUC of 0.7400 and a mean AUPRC of 0.8582. ATRX mutation status was predicted with very similar discriminatory power, with a mean AUC of 0.7810 and a mean AUPRC of 0.8511. In both cases, AutoML was even able to achieve a discriminatory power slightly above that of the respective conventionally developed models in a very short computing time, thus making such methods accessible to non-experts in the near future.

Deep-learning magnetic resonance imaging-based automatic segmentation for organs-at-risk in the brain: Accuracy and impact on dose distribution

Background and purpose

Normal tissue sparing in radiotherapy relies on proper delineation. While manual contouring is time consuming and subject to inter-observer variability, auto-contouring could optimize workflows and harmonize practice. We assessed the accuracy of a commercial, deep-learning, MRI-based tool for brain organs-at-risk delineation.

Materials and methods

Thirty adult brain tumor patients were retrospectively manually recontoured. Two additional structure sets were obtained: AI (artificial intelligence) and AIedit (manually corrected auto-contours). For 15 selected cases, identical plans were optimized for each structure set. We used Dice Similarity Coefficient (DSC) and mean surface-distance (MSD) for geometric comparison and gamma analysis and dose-volume-histogram comparison for dose metrics evaluation. Wilcoxon signed-ranks test was used for paired data, Spearman coefficient(ρ) for correlations and Bland-Altman plots to assess level of agreement.

Results

Auto-contouring was significantly faster than manual (1.1/20 min, p < 0.01). Median DSC and MSD were 0.7/0.9 mm for AI and 0.8/0.5 mm for AIedit. DSC was significantly correlated with structure size (ρ = 0.76, p < 0.01), with higher DSC for large structures. Median gamma pass rate was 74% (71-81%) for Plan_AI and 82% (75-86%) for Plan_AIedit, with no correlation with DSC or MSD. Differences between Dmean_AI and Dmean_Ref were ≤ 0.2 Gy (p < 0.05). The dose difference was moderately correlated with DSC. Bland Altman plot showed minimal discrepancy (0.1/0) between AI and reference Dmean/Dmax.

Conclusions

The AI-model showed good accuracy for large structures, but developments are required for smaller ones. Auto-segmentation was significantly faster, with minor differences in dose distribution caused by geometric variations.

Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas

This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00087-6.

VERY LONG-CHAIN ACYL-CoA SYNTHETASE-3 (ACSVL3) PROMOTES THE MALIGNANT GROWTH BEHAVIOR OF U87 GLIOMA CELLS VIA CHANGES IN CELL CYCLE WITHOUT AFFECTING APOPTOSIS

Decreasing the expression of very long-chain acyl-CoA synthetase 3 (ACSVL3) in U87MG glioblastoma cells by either RNA interference or genomic knockout (KO) significantly decreased their growth rate in culture, as well as their ability to form rapidly growing tumors in mice. U87-KO cells grew at a 9-fold slower rate than U87MG cells. When injected subcutaneously in nude mice, the tumor initiation frequency of U87-KO cells was 70% of that of U87MG cells, and the average growth rate of tumors that did form was decreased by 9-fold. Two hypotheses to explain the decreased growth rate of KO cells were investigated. Lack of ACSVL3 could reduce cell growth either by increasing apoptosis, or via effects on the cell cycle. We examined intrinsic, extrinsic, and caspase-independent apoptosis pathways; none were affected by lack of ACSVL3. However, significant differences in the cell cycle were seen in KO cells, suggesting arrest in S-phase. Levels of cyclin-dependent kinases 1, 2, and 4 were elevated in U87-KO cells, as were regulatory proteins p21 and p53 that promote cell cycle arrest. In contrast, lack of ACSVL3 reduced the level of the inhibitory regulatory protein p27. γ-H2AX, a marker of DNA double strand breaks, was elevated in U87-KO cells, while pH3, a mitotic index marker, was reduced. Previously reported alterations in sphingolipid metabolism in ACSVL3-depleted U87 cells may explain the effect of KO on cell cycle. These studies reinforce the notion that ACSVL3 is a promising therapeutic target in glioblastoma.

Stereotactic laser ablation in neuro-oncology - A survey among European neurosurgeons

Introduction

In the last decades, the application of stereotactic laser ablation (SLA) for the treatment of intracranial tumours has been growing, even though comparative trials are lacking. Our aim was to investigate the familiarity with SLA of neurosurgeons in Europe and their opinion regarding potential neuro-oncological indications. Furthermore, we investigated treatment preferences and variability for three exemplar neuro-oncological cases and willingness to refer for SLA.

Material and methods

A 26-questions survey was mailed to members of the EANS neuro-oncology section. We presented three clinical cases of respectively deep-seated glioblastoma, recurrent metastasis and recurrent glioblastoma. Descriptive statistics was applied to report results.

Results

110 respondents completed all questions. Recurrent glioblastoma and recurrent metastases were regarded as the most feasible indications for SLA (chosen by 69% and 58% of the respondents) followed by newly diagnosed high-grade gliomas (31%). Seventy percent of respondents would refer patients for SLA. The majority of respondents would consider SLA as a treatment option for all three presented cases: 79% for the deep-seated glioblastoma case, 65% for the recurrent metastasis case and 76% for the recurrent glioblastoma case. Among respondents who wouldn't consider SLA, preference for standard treatment and lack of clinical evidence were reported as the main reasons.

Conclusions

Most of respondents considered SLA as a treatment option for recurrent glioblastoma, recurrent metastases and newly diagnosed deep-seated glioblastoma. At the moment the current evidence to support such a treatment is very low. Comparative prospective trials are needed to support the use of SLA and determine proper indications.