Response Assessment in Neuro-Oncology Criteria for Gliomas: Practical Approach Using Conventional and Advanced Techniques

Systematic review and epistemic meta-analysis to advance binomial AI-radiomics integration for predicting high-grade glioma progression and enhancing patient management

High-grade gliomas, particularly glioblastoma (MeSH:Glioblastoma), are among the most aggressive and lethal central nervous system tumors, necessitating advanced diagnostic and prognostic strategies. This systematic review and epistemic meta-analysis explore the integration of Artificial Intelligence (AI) and Radiomics Inter-field (AIRI) to enhance predictive modeling for tumor progression. A comprehensive literature search identified 19 high-quality studies, which were analyzed to evaluate radiomic features and machine learning models in predicting overall survival (OS) and progression-free survival (PFS). Key findings highlight the predictive strength of specific MRI-derived radiomic features such as log-filter and Gabor textures and the superior performance of Support Vector Machines (SVM) and Random Forest (RF) models, achieving high accuracy and AUC scores (e.g., 98% AUC and 98.7% accuracy for OS). This research demonstrates the current state of the AIRI field and shows that current articles report their results with different performance indicators and metrics, making outcomes heterogenous and hard to integrate knowledge. Additionally, it was explored that today some articles use biased methodologies. This study proposes a structured AIRI development roadmap and guidelines, to avoid bias and make results comparable, emphasizing standardized feature extraction and AI model training to improve reproducibility across clinical settings. By advancing precision medicine, AIRI integration has the potential to refine clinical decision-making and enhance patient outcomes.

Stereotactic radiosurgery for recurrent high-grade gliomas

INTRODUCTION

High-grade gliomas (WHO Grade III and IV) invariably recur. Standardized management in the recurrent setting is ill defined. Stereotactic radiosurgery (SRS) represents a non-invasive treatment modality. Evidence to date is limited and therefore further evaluation of the role of SRS in recurrent high-grade-gliomas (rHGG) is warranted.

METHODS

We conducted a retrospective cohort study consisting of 33 patients with rHGGs treated with SRS from January 2020 to June 2024. Baseline demographics, radiosurgical parameters, and outcomes/toxicity data were collected. Descriptive statistics were calculated for all continuous variables. Survival analysis was performed using the Kaplan Meier method. Univariate analysis was performed using Cox proportional hazard model. All statistics were performed in GraphPad Prism (V.10).

RESULTS

Thirty-three patients with 44 rHGG lesions underwent Gamma Knife SRS with a median of 5 fractions (range:1-5). Overall local control at 3-,6-, and 12-months was 69.9 %, 45.9 %, and 31.9 % respectively. Distant tumor control at 3-,6-, and 12-months was 71.7 %, 48.2 %, and 42.2 %. Global tumor control was at 3-,6, and 12-months was 69.9 %, 45.9 %, 31.9 % respectively. Median OS from the time of SRS was 7 months (95 % CI: 6.65-17.23). Median PFS from the time of SRS was 5.5 months (95 % CI: 4.79-14.31). MGMT methylated status was associated with improved OS (HR: 0.24 95 % CI: 0.07-0.60, P = 0.01).

CONCLUSIONS

SRS affords reasonable local control in the short term for patients with recurrent HGG who are otherwise poor surgical candidates. Local failure is more common than distant failure, albeit global control is critical in increasing PFS. MGMT methylated status is associated with increased overall survival.

A Delphi study of current practices and establishing consensus regarding assessment of fitness to drive among patients with brain tumours

PURPOSE

Evaluating fitness to drive among patients with brain tumours remains a challenge for clinicians. Due to difficulties in conducting prospective driving studies in this patient cohort, a Delphi study was performed to formulate new driving guidelines for patients with brain tumours.

METHODS

The survey questions, which were designed by utilising Australian driving guidelines and previous Delphi studies, established panelists' expertise, and then used a 9-point Likert scale to formulate new driving guidelines. An expert group of panelists comprising medical oncologists, radiation oncologists, neurosurgeons, and neurologists were chosen based on membership to professional societies with validation in part one of the survey. Two rounds of anonymised surveys were performed using REDCap for data entry, and a novel automated methodology on R for data analysis.

RESULTS

46 statements regarding fitness to drive were developed. Among the 37 surveys distributed, there were 26 responses (70.3% response rate) from round one, and 17 responses (65.4% response rate) for round two. Among the 46 statements, 19 (41.3%) achieved consensus. In addition to establishing a framework for assessing patients, there was notable consensus agreement for stable imaging required as part of evaluation and the need for continual reassessment.

CONCLUSION

Despite clinicians being aware of driving guidelines, determining fitness to drive among patients with brain tumours remains a challenge. This Delphi study identified consensus agreement for the need for stable imaging, and continually reassessing fitness to drive. These novel findings could be translated into future driving guidelines and consensus statements can be integrated into clinical practice.

The Role of PET/CT in Radiation Oncology for Central Nervous System Tumors

The investigation and application of PET modalities for the evaluation and treatment of patients with central nervous system (CNS) tumors continues to evolve, with anticipated increased uptake in the United States for both benign and malignant CNS tumors in the decade to come.

Proliferation-Diffusion Modeling in Glioblastoma: Impact of Supramaximal Resection on Survival

PURPOSE

To evaluate the role of tumor invasiveness profile in a homogeneous cohort of patients with newly diagnosed GBM (2021 WHO) that underwent SUPR by the RANO criteria, and to analyze its impact on survival outcomes.

METHODS

Patients with newly diagnosed, histologically confirmed glial tumors featuring contrast-enhancing lesions, who underwent surgery at our institution between January 2007 and January 2024, were retrospectively reviewed. Preoperative total tumor volume (T-TV), contrast-enhancing (CE), and infiltrative FLAIR tumor volume (FLAIR-TV) were calculated in cubic centimeters (cc) via manual segmentation. A neuronavigation system was utilized for surgery and lesions were molecularly evaluated following the 2021 WHO CNS tumor classification. Therefore, all patients were classified into extent of resection categories by the 2022 RANO-Resect classification. The tumor invasiveness profile was assessed using the proliferation/diffusion (ρ/D) ratio, calculated following Swanson's method. A statistical analysis was finally performed.

RESULTS

Between 2007 and 2024, 410 adult patients with newly diagnosed gliomas were treated at our institution. Methylation of the MGMT promoter was statistically significant (HR = 0.43, 95% CI: 0.20-0.94, p = 0.035), indicating that methylation has a protective effect on survival. In multivariate analysis, only MGMT status was confirmed to be an independent predictor of overall survival (OS). MGMT methylation was significantly associated with improved progression-free survival (PFS) in moderately diffuse tumors (HR = 0.18, 95% CI: 0.03-0.95, p = 0.044).

CONCLUSIONS

Using the proliferation-diffusion model to classify tumors, we identified moderately diffuse tumors with methylated MGMT status as a subgroup with significant survival benefits from SUPR.

An effective MRI perfusion threshold based workflow to triage additional 18F-FET PET in posttreatment high grade glioma

MRI is the preferred method for follow-up imaging of post-treatment WHO grade 3 or 4 gliomas. While positron emission tomography with O-(2-[18F]fluoroethyl)-L-tyrosine) (18F-FET PET) offers higher diagnostic accuracy, its use is limited due to low availability. We propose a sequential, threshold-based workflow to triage patients for additional 18F-FET PET scans based on MRI dynamic susceptibility contrast (DSC) perfusion-derived rCBV values, to optimize 18F-FET PET resource allocation. Patients with high-grade gliomas who had undergone standard-of-care treatment and developed new or enlarging contrast-enhancing post-treatment lesions on MRI were included, with a 18F-FET PET study performed within 4 months of the MRI. Patients were excluded if there were significant changes in lesion size or treatment between the MRI and 18F-FET PET scan. An rCBV threshold was determined and the performance of a threshold-based imaging workflow was evaluated compared to the gold standard defined here as surgical verification or long-term imaging follow-up without further intervention. Forty-one patients with a total of 49 lesions were included (tumor progression n = 40, treatment-related changes n = 9). Above the rCBV threshold of 2.4, MRI was 100% accurate (21/21 patients) in diagnosing tumor progression. Below the threshold, MRI identified 9 true negatives but produced 19 false negatives. 18F-FET PET reclassified 18/19 (95%) false negatives resulting in an overall accuracy of 48/49 (98%) for the workflow. Our MRI DSC perfusion rCBV-based threshold workflow for triaging patients for additional 18F-FET PET imaging in post-treatment high grade glioma has the potential to optimize 18F-FET PET resource allocation.

Reducing clinical target volume margins for multifocal glioblastoma: a multi-institutional analysis of patterns of recurrence and treatment response

PURPOSE

No guidelines exist to delineate radiation therapy (RT) targets for the treatment of multiple glioblastoma (mGBM). This study analyzes margins around the gross tumor volume (GTV) to create a clinical target volume (CTV), comparing response parameters and modalities of recurrence. Material and Methods: One-hundred and three mGBM patients with a CTV margin of 2 cm (GTV + 2.0 cm) or 1 cm (GTV + 1.0 cm) were retrospectively analyzed. All patients received a total dose of 59.4-60 Gy in 1.8-2.0 Gy daily fractions, delivered from 4 to 8 weeks after surgery, concomitantly with temozolomide (75 mg/m2). Overall survival (OS) and progression-free survival (PFS) were calculated from the date of surgery until diagnosis of disease progression performed by magnetic resonance imaging and classified as marginal, in-field, or distant, comparing site of progression with dose distribution in RT plan.

RESULTS

OS in mGBM CTV1 group was 11.2 months (95% confidence interval [CI], 10.3-12.1), and 9.2 months in mGBM CTV2 group (95% CI, 9.0-11.3). PFS in mGBM CTV1 group occurred within 8.3 months (95% CI, 7.3-9.3), and 7.3 months in mGBM CTV2 group (95% CI, 6.4-8.1). No difference was observed between the two groups in terms of OS and PFS time distribution. Adjusted to a multivariate Cox risk model, epidermal growth factor receptor amplification resulted a negative prognostic factor for both OS and PFS.

CONCLUSION

In mGBM, the use of a 1 cm CTV expansion seems feasible as it does not significantly affect oncological outcomes and progression outcome.

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks

This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as multiparametric MRI for capturing the complex nature of gliomas. It delves into the integration of DL with MRI, focusing on convolutional neural networks (CNNs) and their remarkable capabilities in tumor segmentation. Clinical applications of DL-based segmentation are highlighted, including treatment planning, monitoring treatment response, and distinguishing between tumor progression and pseudo-progression. Furthermore, the review examines the evolution of DL-based segmentation studies, from early CNN models to recent advancements such as attention mechanisms and transformer models. Challenges in data quality, gradient vanishing, and model interpretability are discussed. The review concludes with insights into future research directions, emphasizing the importance of addressing tumor heterogeneity, integrating genomic data, and ensuring responsible deployment of DL-driven healthcare technologies. EVIDENCE LEVEL: N/A TECHNICAL EFFICACY: Stage 2.

Evaluation of an Image-based Classification Model to Identify Glioma Subtypes Using Arterial Spin Labeling Perfusion MRI On the Publicly Available UCSF Glioma Dataset

PURPOSE

Glioma is a complex cancer comprising various subtypes and mutations, which may have different metabolic characteristics that can potentially be investigated and identified using perfusion imaging. Therefore, the aim of this work was to use radiomics and machine learning analysis of arterial spin labeling MRI data to automatically differentiate glioma subtypes and mutations.

METHODS

A total of 495 Arterial Spin Labeling (ASL) perfusion imaging datasets from the UCSF Glioma database were used in this study. These datasets were segmented to delineate the tumor volume and classified according to tumor grade, pathological diagnosis, and IDH status. Perfusion image data was obtained from a 3T MRI scanner using pseudo-continuous ASL. High level texture features were extracted for each ASL dataset using PyRadiomics after tumor volume segmentation and then analyzed using a machine learning framework consisting of ReliefF feature ranking and logistic model tree classification algorithms.

RESULTS

The results of the evaluation revealed balanced accuracies for the three endpoints ranging from 55.76% (SD = 4.28, 95% CI: 53.90-57.65) for the tumor grade using 25.4 ± 37.21 features, 62.53% (SD = 2.86, 95% CI: 61.27-63.78) for the mutation status with 23.3 ± 29.17 picked features, and 80.97% (SD = 1.83, 95% CI: 80.17-81.78) for the pathological diagnosis which used 47.3 ± 32.72 selected features.

CONCLUSIONS

Radiomics and machine learning analysis of ASL perfusion data in glioma patients hold potential for aiding in the diagnosis and treatment of glioma, mainly for discerning glioblastoma from astrocytoma, while performance for tumor grading and mutation status appears limited.

How useful is contrast-enhanced MRI in the long-term surveillance of glioma? A multicentre retrospective longitudinal cohort study

OBJECTIVE

To examine whether MRI with routine gadolinium-based contrast agent (GBCA) administration in the long-term surveillance of adult-type diffuse glioma identifies tumour progression earlier than T2-weighted (T2w) and/or T2w fluid-attenuated inversion recovery (FLAIR) MRI only.

MATERIALS AND METHODS

In this longitudinal retrospective multicentre cohort study patients with histopathologically confirmed adult-type diffuse glioma and at least two years survival after diagnosis in 2009-2010 were included. Progression was determined by the treating physician or during the multidisciplinary team meeting and defined as the moment a change in treatment or follow-up was required. The primary outcome was the proportion of patients that showed an increase of abnormalities on both contrast-enhanced T1-weighted (CET1w) and T2w/T2w-FLAIR at the time of progression. Chi-square testing was performed to analyse the relationship between the detection of progression on both scan sequences, with calculating the Phi coefficient to determine the degree of association.

RESULTS

One hundred eight consecutive patients were included (58 male; 53 grade 2, 21 grade 3, 34 grade 4). Progression was present in 82 patients and was determined on both CET1w and T2w/T2w-FLAIR images in 59 patients (72.0%). In 20 patients (24.4%), progression was determined based solely on T2w/T2w-FLAIR abnormalities. Only three patients showed progression exclusively on CET1w (3.7%). There was a strong positive significant relationship between the detection of progression on both scan types (p < 0.001; Phi = 0.467).

CONCLUSION

An increase in CET1w abnormalities was generally accompanied by an increase in T2w/T2w-FLAIR abnormalities, raising the question of whether routine administration of GBCA is always necessary for long-term survivors of glioma.

KEY POINTS

Question Long-term survivors with glioma undergo many contrast-enhanced MRI scans, which involve a patient, financial, and environmental burden. Findings In almost all patients, an increase in T2w/T2w-FLAIR abnormalities was present at the time of tumour progression, mostly but not always accompanying contrast-enhancing findings. Clinical relevance T2w/T2-FLAIR MRI seems to detect glioma progression in long-term surviving patients similar to contrast-enhanced T1w MRI, raising the question of whether the routine administration of GBCA is necessary and justified in patients under long-term surveillance of glioma.

Early Repeat Residual Resection Versus Adjuvant Therapy for Incompletely Resected Glioblastoma: A Case-Control Study

BACKGROUND AND OBJECTIVE

Maximal safe resection of newly diagnosed glioblastoma (GBM) optimizes clinical outcomes. For patients who receive biopsy or subtotal resection (STR), early repeat resection (ERR) to improve extent of resection can be considered but is controversial. Oncological outcomes of patients undergoing ERR for residual GBM to patients receiving upfront at least near-total resection were compared.

METHODS

This case-control study including patients with GBM treated at a single institution identified 3 treatment groups: (1) ERR patients underwent biopsy or STR (<95% cytoreduction), followed by ≥NTR (≥95% cytoreduction) within 8 weeks; (2) control patients underwent upfront ≥NTR; and (3) biopsy with chemoradiation only. ERR and control patients were 1:1 case-control matched by age, performance status, O6-methylguanine-DNA methyltransferase methylation status, isocitrate dehydrogenase mutation status, and completion of standard chemoradiation. Patient demographics, treatments, and oncological outcomes were analyzed. A P-value of <.05 was considered significant.

RESULTS

A total of 22 ERR patients (16 biopsies and 6 STR) were identified, and each was matched with a control patient. Baseline patient characteristics at presentation did not differ between matched patients. Time from first surgery to chemoradiation was longer in the ERR cohort (1.8 vs 1.1 months, P < .001). Median overall survival (mOS) (17.7 vs 20.3 months, P = .87) and progression-free survival (5.5 vs 4.5 months, P = .25) did not differ between ERR and control groups, respectively. In the biopsy-only group, mOS was 4.1. Univariate Cox-regression analysis suggested age, failure to complete chemoradiation, isocitrate dehydrogenase-wt, and hemorrhage at presentation were independent predictors of mOS, whereas only age and failure to complete chemoradiation remained independent predictors of mOS after multivariate analysis. Surgical complications were similar between cohorts.

CONCLUSION

ERR achieving ≥95% extent of resection within 8 weeks of initial surgery results in similar oncological outcomes to upfront ≥NTR in a case-control-matched analysis despite delayed initiation in chemoradiation for the ERR cohort.

A nationwide provider survey of neuro-oncology tumor boards in a lower-middle-income country: Comparing centers with and without tumor boards

OBJECTIVES

To provide information about implementation, resources, practice patterns and prevalent perceptions regarding neuro-oncology tumor boards (NOTBs) in a lower middle income country.

METHODS

A nationwide survey was designed to include licensed neurosurgeons involving data on practice, structure, and perceptions of NOTBs with non-probability sampling, a pre-validated proforma, data analysis using SPSS v27, and geospatial mapping using Quantum GIS.

RESULTS

139 neurosurgeons were surveyed from 63 neurosurgical centers of a lower middle income country. 15/63 neurosurgical centers had dedicated NOTBs. Neurosurgeons from centers with NOTBs had better access to palliative care with radiation oncologists (70 %) and services (73 %) as compared to those without NOTBs (44 %, p = 0.012 and 44 %, p = 0.004). 76.3 % of neurosurgeons routinely prescribed postoperative CT scans with higher rate in centers without NOTBs (94 % vs. 80 %, p = 0.024). 57.6 % of neurosurgeons prescribed postoperative MRI scans within six weeks for intra-axial pathology, with higher rates in NOTB centers (63 % vs. 56 %, not significant). The perceived positive effects of NOTBs included improved patient outcomes (87.6 %), expedited centralized patient care (88.3 %), decreased referral times (74.4 %), increased uptake of adjuvant management (66.4 %), decreased mortality/morbidity (73.1 %), and significant treatment (78.5 %) and diagnostic plan changes (77.4 %) while perceived negative effects included the time-consuming nature (20.7 %), and suffering of patients due to wait associated with NOTBs (36 %). The perceived barriers included "lack of administrative support" (17.1 %), "limited resources" (15.2 %), and "lack of standardized protocols or guidelines" (13.8 %).

CONCLUSION

In this nationwide situational report from a lower middle income country, only a quarter of neurosurgical units had dedicated NOTBs. The centers with NOTBs were mostly education/training centers, and had better access/availability to palliative decision-making and care. The neurosurgeons from centers with NOTBs had lower rates of prescribing immediate postoperative CT scans while higher rates of prescribing MRI scans within 6 weeks for intra-axial pathology. Therefore, NOTBs can help advocate for judicious use of neuroimaging and increased uptake of adjuvant palliative treatment. While perceived effects were similar, the nature of perceived barriers was different for LMIC and HIC. Our study can aid policymakers, hospitals, and healthcare professionals, and can provide a roadmap for future in-depth studies with geospatial mapping of resources/services to fully elucidate the inequalities.

Clinical and functional outcome for gliomas located in the primary and supplementary motor area. Surgical series and systematic Literature review

INTRODUCTION

This retrospective study and review aim to investigate diffuse adult gliomas in the motor cortex (primary motor area, M1, and secondary motor area, M2, which includes the supplementary motor area and premotor cortex). It explores the relationships between the histologic and molecular profiles of the lesions, their location, and the type of resection performed, and correlates them with patients' outcomes post-surgery.

MATERIAL AND METHODS

An Institutional retrospective review was conducted on a consecutive series of 200 selected patients with histologically confirmed Glioblastomas (GBM) treated surgically between September 2018 and February 2022. These patients were categorized into three subgroups: Group A (lesions contacting CST and/or M1), Group B (lesions related to SMA and pre-SMA), and Group C (lesions outside and distal to the Motor Pathways). The study examined the relationships between the histologic and molecular profiles of the gliomas, their locations, and the types of resections performed, correlating these data with patients' postoperative prognoses.

RESULTS

The findings indicate that the three subgroups did not exhibit significant deterioration in clinical and functional status. Lesions in M1/CST and SMA locations were not inherently associated with poorer outcomes. Notably, lesions involving SMA had a higher preoperative volume compared to those in other areas (Group A: 24.5 ± 24.3 cm3; Group B: 30.1 ± 22.7 cm3; Group C: 19.91 ± 15.8 cm3; p = 0.025).

CONCLUSIONS

These results align with existing literature, suggesting that although transient motor worsening is expected post-surgery, gliomas in motor areas do not significantly impact survival or functional status. Additionally, the molecular patterns of these tumors do not differ from those of lesions in other brain regions.

Health-related quality of life in 62 patients with diffuse low-grade glioma during a non-therapeutic and progression-free phase: a cross-sectional study

PURPOSE

Few studies have evaluated the health-related quality of life (HRQoL) of patients with diffuse low-grade glioma (LGG) during a clinical and radiological monitoring period. We report a cross sectional cohort study of HRQoL in patients with LGG and compare the results with normative population data. We then explore factors associated with HRQoL.

METHODS

We used the European Organisation for Research and Treatment of Cancer QLQ-C30, BN-20 and the Hospital Anxiety and Depression Scale (HADS) to evaluate HRQoL. Averaged QLQC30 and HADS scores were compared with scores of a normative population. A general linear model multivariate analysis of variance was used to investigate the association between HRQoL and independent factors.

RESULTS

A total of 62 patients with LGG completed HRQoL questionnaires. Compared with a normative population, LGG patients reported statistical and clinically significant lower cognitive, emotional, role and social functioning. Fatigue, anxiety, depression and sleep disturbances were frequently reported. Awake surgery and preserved high Karnofsky Performance Status were found to be independent prognostic factors for better global HRQoL, while radiotherapy was associated with worsened HRQoL.

CONCLUSION

Despite a non-therapeutic and progression free phase, LGG patients report noticeable limitations in several HRQoL subscales. Our study highlights the importance of HRQoL assessment not only at diagnosis or during active therapeutic stage. Further studies are needed to develop better adapted tools of HRQoL assessment.

Case report: Pseudoprogression mimicking neoplastic recurrence three months after completion of proton beam therapy for an IDH-mutant astrocytoma CNS WHO grade 3

Background

Radiation-induced changes following proton beam therapy in isocitrate dehydrogenase (IDH)-mutated diffuse central nervous system (CNS) World Health Organization (WHO) grade 2 and 3 gliomas are not well characterized. We present a patient with an IDH-mutant astrocytoma CNS WHO grade 3 treated with proton beam therapy and with postradiation MRI changes suggestive of neoplastic progression that surprisingly turned out to be reactive.

Case presentation

A man in his twenties underwent surgery with a near gross total resection for what turned out to be an IDH-mutant astrocytoma CNS WHO grade 3. He was included in the PRO-GLIO trial and randomized to receive proton beam therapy to a total dose of 59.4 Gray (Gy) relative biological effectiveness (RBE). Four weeks after completion of radiotherapy, adjuvant temozolomide was commenced. All treatment was well tolerated, and the patient was in excellent general condition. Surprisingly, magnetic resonance imaging (MRI) examination three months after completion of radiotherapy showed what was highly suggestive of a distant recurrence. The patient underwent resective surgery about seven months after his first surgery. Histological examination showed inflammatory changes without neoplastic tissue, albeit not very typical for postradiation changes. Adjuvant chemotherapy with temozolomide was continued.

Conclusion

The presented case clearly shows that caution must be taken when interpreting cerebral MRI changes postradiation, and in particular after proton therapy. Further understanding of this subject is crucial to distinguish between patients requiring intensified antineoplastic treatment and those for whom maintaining current therapy or ongoing watchful waiting is advisable.

Saturation transfer (CEST and MT) MRI for characterization of U-87 MG glioma in the rat

The focus of this work was to identify the optimal magnetic resonance imaging (MRI) contrast between orthotopic U-87 MG tumours and normal appearing brain with the eventual goal of treatment response monitoring. U-87 MG human glioblastoma cells were injected into the brain of RNU nude rats (n = 9). The rats were imaged at 7 T at three timepoints for all animals: 3-5, 7-9, and 11-13 days after implantation. Whole-brain T1-weighted (before and after gadolinium contrast agent injection), diffusion, and fluid-attenuated inversion recovery scans were performed. In addition, single-slice saturation-transfer-weighted chemical exchange saturation transfer (CEST), magnetization transfer (MT), and water saturation shift referencing (WASSR) contrast Z-spectra and T1 and T2 maps were also acquired. The MT and WASSR Z-spectra and T1 map were fitted to a two-pool quantitative MT model to estimate the T2 of the free and macromolecular-bound water molecules, the relative macromolecular pool size (M0, MT), and the magnetization exchange rate from the macromolecular pool to the free pool (RMT). The T1-corrected apparent exchange-dependent relaxation (AREX) metric to isolate the CEST contributions was also calculated. The lesion on M0, MT and AREX maps with a B1 of 2 μT best matched the hyperintensity on the post-contrast T1-weighted image. There was also good separation in Z-spectra between the lesion and contralateral cortex in the 2-μT CEST and 3- and 5-μT MT Z-spectra at all time points. A pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment on MRI parameters was performed and the differences between enhancing lesion and contralateral cortex for the MT ratio with 2 μT saturation at 3.6 ppm frequency offset (corresponding to the amide chemical group) and M0, MT were both strongly significant (p < 0.001) at all time points. This work has identified that differences between enhancing lesion and contralateral cortex are strongest in MTR with B1 = 2 μT at 3.6 ppm and relative macromolecular pool size (M0, MT) images over entire period of 3-13 days after cancer cell implantation.

Magnetic resonance imaging techniques for monitoring glioma response to chemoradiotherapy

PURPOSE

Treatment response assessment for gliomas currently uses changes in tumour size as measured with T1- and T2-weighted MRI. However, changes in tumour size may occur many weeks after therapy completion and are confounded by radiation treatment effects. Advanced MRI techniques sensitive to tumour physiology may provide complementary information to evaluate tumour response at early timepoints during therapy. The objective of this review is to provide a summary of the history and current knowledge regarding advanced MRI techniques for early treatment response evaluation in glioma.

METHODS

The literature survey included perfusion MRI, diffusion-weighted imaging, quantitative magnetization transfer imaging, and chemical exchange transfer MRI. Select articles spanning the history of each technique as applied to treatment response evaluation in glioma were chosen. This report is a narrative review, not formally systematic.

RESULTS

Chemical exchange saturation transfer imaging potentially offers the earliest method to detect tumour response due to changes in metabolism. Diffusion-weighted imaging is sensitive to changes in tumour cellularity later during radiotherapy and is prognostic for progression-free and overall survival. Substantial evidence suggests that perfusion MRI can differentiate between tumour recurrence and treatment effect, but consensus regarding acquisition, processing, and interpretation is still lacking. Magnetization transfer imaging shows promise for detecting subtle white matter damage which could indicate tumour invasion, but more research in this area is needed.

CONCLUSION

Advanced MRI techniques show potential for early treatment response assessment, but each technique alone lacks specificity. Multiparametric imaging may be necessary to aid biological interpretation and enable treatment guidance.

Evaluating Immunotherapy Responses in Neuro-Oncology for Glioblastoma and Brain Metastases: A Brief Review Featuring Three Cases

INTRODUCTION

Recent advancements in immunotherapy have offered new possibilities for treating aggressive glioblastoma (GBM) and brain metastases. However, evaluating treatment responses remains complex, prompting the development of the immunotherapy-specific Response Assessment in Neuro-Oncology (iRANO) criteria. Herein, we present case reports illustrating the intricacies of interpreting imaging changes post-immunotherapy, emphasizing the need for a comprehensive approach to assessing treatment effectiveness.

CASE REPORTS

Case 1 discusses a 41-year-old male with GBM, highlighting the challenges of differentiating tumor progression from treatment-induced pseudoprogression. Case 2 discusses a 45-year-old female with brain metastatic malignant melanoma, presenting radiological evidence of progressive disease while undergoing nivolumab treatment. Case 3 discusses a 37-year-old male with GBM, where radiological evidence indicates progressive disease while receiving pembrolizumab treatment.

MANAGEMENT AND OUTCOMES

In case 1, we discussed the challenges of distinguishing true tumor progression from treatment-induced pseudoprogression, leading to the continuation of the same treatment due to pseudoprogression. In case 2, post-surgery pathology revealed radionecrosis and treatment-related changes, guiding the continuation of nivolumab therapy. Case 3 involved a pathologically confirmed progression, and the patient received best supportive care due to his performance status.

DISCUSSION

Despite aggressive treatment regimens, the prognosis for GBM patients remains poor, underscoring the necessity for innovative therapeutic strategies. Immunotherapy holds promise in reshaping the treatment landscape for GBM and brain metastases, but further research and refinement of assessment criteria are crucial. Throughout our cases, we discuss the iRANO criteria, developed to overcome the limitations of the RANO criteria in capturing immunotherapy responses, particularly pseudoprogression.

Surgical identification of brain tumour margins through impedance monitoring and electrocorticography and the potential for their combined use: A systematic review

CONTEXT

Primary central nervous system tumours have poor survival outcomes. Surgery, the first-line treatment, presents technical limitations, such as visualising the whole tumour border. Intracranial impedance monitoring and electrocorticography techniques provide insights into the local field potential characteristics, resistance and capacitance properties of brain tissue. We hypothesised that measurements obtained by either modality can distinguish between tumour and healthy brain tissue intraoperatively.

METHODS

A "Preferred Reporting Items for Systematic Reviews and Meta-Analyses" (PRISMA)-compliant systematic review was conducted, searching PubMed, Ovid, Scopus, Cochrane and Web of Science. Studies on electrocorticography and impedance monitoring in patients with brain tumours were included. Data on patient demographics, technical details, obtained results and safety were extracted and analysed in Excel.

RESULTS

Eighteen studies involving 286 patients in total were identified. Ten impedance studies showed that brain tumour tissue has significantly different values than healthy tissue, while its resistivity varies, being either higher or lower. Eight electrocorticography studies indicated increased high gamma power and altered connectivity in tumour tissue. No studies integrated impedance monitoring and electrocorticography in one device.

CONCLUSION

Impedance and electrocorticography measurements have the potential of differentiating between tumour and unaffected issues intra-operatively. Larger studies with standardised protocols are needed to validate these findings. Additionally, the combination of these two modalities has the potential for improved specificity with a single device. Future research should explore the role of these modalities in enhancing tumour margin identification across different tumour subtypes and in improving survival outcomes.

Fotemustine in recurrent high‑grade glioma: MRI neuro‑radiological findings

The use of fotemustine (FTM) has been authorized in certain countries for the treatment of recurrent high-grade gliomas (HGG) after Stupp therapy. However, to the best of our knowledge, no studies have assessed changes in magnetic resonance imaging (MRI) during treatment with FTM monotherapy. The aim of the present study was to assess the neuroradiological findings in a cohort of patients with recurrent HGG treated with FTM monotherapy. Patients with HGG already undergoing the Stupp protocol were retrospectively included. MRIs (pre- and post-FTM treatment) were analyzed by two neuroradiologists in consensus: Volume and diffusion values of the contrast-enhanced component were measured on T1-weighted volumetric sequences after gadolinium injection and on apparent diffusion coefficient (ADC) maps, respectively. A total of 19 patients [median age, 49 years; interquartile range (IQR), 43-57 years] were included, 17 of whom had glioblastoma and 2 had astrocytoma isocitrate dehydrogenase-mutated grade 4. The median duration of FTM therapy was 4 months (IQR, 2-6 months). The median tumor volume measured on the contrast-enhanced component was 2,216 mm3 (IQR, 768-13,169 mm3) at baseline and 9,217 mm3 (IQR, 3,455-16,697 mm3) at the end of treatment, with a median change of +38% (IQR, -45-+574%). A total of seven patients showed a volume decrease. ADC value analysis of the enhancement area demonstrated no significant difference between the pre- and the post-FTM treatment periods (P=0.36); however, in three patients, the decreases in ADC levels were particularly marked. In conclusion, the present study described a series of patients with recurrent HGG treated with FTM in monotherapy, demonstrating a prevalent increase in lesion enhancement and three cases of marked restrictions on diffusion-weighted imaging. Further prospective studies are required to corroborate such preliminary results.

Automatic removal of large blood vasculature for objective assessment of brain tumors using quantitative dynamic contrast-enhanced magnetic resonance imaging

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE-MRI data acquisition. Quantitative DCE-MRI analysis was performed for computing various parameters such as wash-out slope (Slope-2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (Vp), and volume transfer constant (Ktrans). An approach based on data-clustering algorithm, morphological operations, and quantitative DCE-MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data-clustering algorithms were evaluated on two types of quantitative maps: (a) Slope-2, and (b) a new proposed combination of rCBV and Slope-2 maps. Fluid-attenuated inversion recovery-MRI hyperintense lesions were also automatically segmented using deep learning-based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE-MRI parameters were obtained in the segmented tumor. t-test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k-means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high-grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95th percentile values) of all parameters in the tumor region showed a statistically significant difference (p < 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low-grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and Vp maps show better visualization of tumor regions.

Prospective phase II trial of [68Ga]Ga-NOTA-AE105 uPAR-PET/MRI in patients with primary gliomas: Prognostic value and Implications for uPAR-targeted Radionuclide Therapy

BACKGROUND

Treatment of patients with low-grade and high-grade gliomas is highly variable due to the large difference in survival expectancy. New non-invasive tools are needed for risk stratification prior to treatment. The urokinase plasminogen activator receptor (uPAR) is expressed in several cancers, associated with poor prognosis and may be non-invasively imaged using uPAR-PET. We aimed to investigate the uptake of the uPAR-PET tracer [68Ga]Ga-NOTA-AE105 in primary gliomas and establish its prognostic value regarding overall survival (OS), and progression-free survival (PFS). Additionally, we analyzed the proportion of uPAR-PET positive tumors to estimate the potential number of candidates for future uPAR-PRRT.

METHODS

In a prospective phase II clinical trial, 24 patients suspected of primary glioma underwent a dynamic 60-min PET/MRI following the administration of approximately 200 MBq (range: 83-222 MBq) [68Ga]Ga-NOTA-AE105. Lesions were considered uPAR positive if the tumor-to-background ratio, calculated as the ratio of TumorSUVmax-to-Normal-BrainSUVmean tumor-SUVmax-to-background-SUVmean, was ≥ 2.0. The patients were followed over time to assess OS and PFS and stratified into high and low uPAR expression groups based on TumorSUVmax.

RESULTS

Of the 24 patients, 16 (67%) were diagnosed with WHO grade 4 gliomas, 6 (25%) with grade 3, and 2 (8%) with grade 2. Two-thirds of all patients (67%) presented with uPAR positive lesions and 94% grade 4 gliomas. At median follow up of 18.8 (2.1-45.6) months, 19 patients had disease progression and 14 had died. uPAR expression dichotomized into high and low, revealed significant worse prognosis for the high uPAR group for OS and PFS with HR of 14.3 (95% CI, 1.8-112.3; P = 0.011), and HR of 26.5 (95% CI, 3.3-214.0; P = 0.0021), respectively. uPAR expression as a continuous variable was associated with worse prognosis for OS and PFS with HR of 2.7 (95% CI, 1.5-4.8; P = 0.0012), and HR of 2.5 (95% CI, 1.5-4.2; P = 0.00073), respectively.

CONCLUSIONS

The majority of glioma patients and almost all with grade 4 gliomas displayed uPAR positive lesions underlining the feasibility of 68Ga-NOTA-AE105 PET/MRI in gliomas. High uPAR expression is significantly correlated with worse survival outcomes for patients. Additionally, the high proportion of uPAR positive gliomas underscores the potential of uPAR-targeted radionuclide therapy in these patients.

TRAIL REGISTRATION

EudraCT No: 2016-002417-21; the Scientific Ethics Committee: H-16,035,303; the Danish Data Protection Agency: 2012-58-0004; clinical trials registry: NCT02945826, 26Oct2016, URL: https://classic.

CLINICALTRIALS

gov/ct2/show/NCT02945826 .

T2-FLAIR imaging-based radiomic features for predicting early postoperative recurrence of grade II gliomas

Aim: To develop and validate a T2-weighted-fluid attenuated inversion recovery (T2-FLAIR) images-based radiomics model for predicting early postoperative recurrence (within 1 year) in patients with low-grade gliomas (LGGs).Methods: A retrospective analysis was performed by collecting clinical, pathological and magnetic resonance imaging (MRI) data from patients with LGG between 2017 and 2022. Regions of interest were delineated and radiomic features were extracted from T2-FLAIR images using 3D-Slicer software. To minimize redundant features, the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm was used. Patients were categorized into two groups based on recurrence status: the recurrence group (RG) and the non-recurrence group (NRG). Radiomic features were used to develop models using three machine learning approaches: logistic regression (LR), random forest (RF) and support vector machine (SVM). The performance of the radiomic features was validated using fivefold cross-validation.Results: After rigorous screening, 105 patients met the inclusion criteria, and five radiomic features were identified. After 5-folds cross-validation, the average areas under the curves for LR, RF and SVM were 0.813, 0.741 and 0.772, respectively.Conclusion: T2-FLAIR-based radiomic features effectively predicted early recurrence in postoperative LGGs.

Gliomas in adults: Guidance on investigations, diagnosis, treatment and surveillance

Primary brain tumours are rare but carry a significant morbidity and mortality burden. Malignant gliomas are the most common subtype and their incidence is increasing within our ageing population. The diagnosis and treatment of gliomas involves substantial interplay between multiple specialties, including general medical physicians, radiologists, pathologists, surgeons, oncologists and allied health professionals. At any point along this pathway, patients can present to acute medicine with complications of their cancer or anti-cancer therapy. Increasing the awareness of malignant gliomas among general physicians is paramount to delivering prompt radiological and histopathological diagnoses, facilitating access to earlier and individualised treatment options and allows for effective recognition and management of anticipated complications. This article discusses evidence-based real-world practice for malignant gliomas, encompassing patient presentation, diagnostic pathways, treatments and their complications, and prognosis to guide management outside of specialist centres.

Deep learning ensembles for detecting brain metastases in longitudinal multi-modal MRI studies

Metastatic brain cancer is a condition characterized by the migration of cancer cells to the brain from extracranial sites. Notably, metastatic brain tumors surpass primary brain tumors in prevalence by a significant factor, they exhibit an aggressive growth potential and have the capacity to spread across diverse cerebral locations simultaneously. Magnetic resonance imaging (MRI) scans of individuals afflicted with metastatic brain tumors unveil a wide spectrum of characteristics. These lesions vary in size and quantity, spanning from tiny nodules to substantial masses captured within MRI. Patients may present with a limited number of lesions or an extensive burden of hundreds of them. Moreover, longitudinal studies may depict surgical resection cavities, as well as areas of necrosis or edema. Thus, the manual analysis of such MRI scans is difficult, user-dependent and cost-inefficient, and - importantly - it lacks reproducibility. We address these challenges and propose a pipeline for detecting and analyzing brain metastases in longitudinal studies, which benefits from an ensemble of various deep learning architectures originally designed for different downstream tasks (detection and segmentation). The experiments, performed over 275 multi-modal MRI scans of 87 patients acquired in 53 sites, coupled with rigorously validated manual annotations, revealed that our pipeline, built upon open-source tools to ensure its reproducibility, offers high-quality detection, and allows for precisely tracking the disease progression. To objectively quantify the generalizability of models, we introduce a new data stratification approach that accommodates the heterogeneity of the dataset and is used to elaborate training-test splits in a data-robust manner, alongside a new set of quality metrics to objectively assess algorithms. Our system provides a fully automatic and quantitative approach that may support physicians in a laborious process of disease progression tracking and evaluation of treatment efficacy.

Randomized, open-label, phase 2 study of nivolumab plus ipilimumab or nivolumab monotherapy in patients with advanced or metastatic solid tumors of high tumor mutational burden

BACKGROUND

Checkpoint inhibitor therapy has demonstrated overall survival benefit in multiple tumor types. Tumor mutational burden (TMB) is a predictive biomarker for response to immunotherapies. This study evaluated the efficacy of nivolumab+ipilimumab in multiple tumor types based on TMB status evaluated using either tumor tissue (tTMB) or circulating tumor DNA in the blood (bTMB).

PATIENTS AND METHODS

Patients with metastatic or unresectable solid tumors with high (≥10 mutations per megabase) tTMB (tTMB-H) and/or bTMB (bTMB-H) who were refractory to standard therapies were randomized 2:1 to receive nivolumab+ipilimumab or nivolumab monotherapy in an open-label, phase 2 study (CheckMate 848; NCT03668119). tTMB and bTMB were determined by the Foundation Medicine FoundationOne® CDx test and bTMB Clinical Trial Assay, respectively. The dual primary endpoints were objective response rate (ORR) in patients with tTMB-H and/or bTMB-H tumors treated with nivolumab+ipilimumab.

RESULTS

In total, 201 patients refractory to standard therapies were randomized: 135 had tTMB-H and 125 had bTMB-H; 82 patients had dual tTMB-H/bTMB-H. In patients with tTMB-H, ORR was 38.6% (95% CI 28.4% to 49.6%) with nivolumab+ipilimumab and 29.8% (95% CI 17.3% to 44.9%) with nivolumab monotherapy. In patients with bTMB-H, ORR was 22.5% (95% CI 13.9% to 33.2%) with nivolumab+ipilimumab and 15.6% (95% CI 6.5% to 29.5%) with nivolumab monotherapy. Early and durable responses to treatment with nivolumab+ipilimumab were seen in patients with tTMB-H or bTMB-H. The safety profile of nivolumab+ipilimumab was manageable, with no new safety signals.

CONCLUSIONS

Patients with metastatic or unresectable solid tumors with TMB-H, as determined by tissue biopsy or by blood sample when tissue biopsy is unavailable, who have no other treatment options, may benefit from nivolumab+ipilimumab.

TRIAL REGISTRATION NUMBER

NCT03668119.

Imaging and Liquid Biopsy for Distinguishing True Progression From Pseudoprogression in Gliomas, Current Advances and Challenges

RATIONALE AND OBJECTIVES

Gliomas are aggressive brain tumors with a poor prognosis. Assessing treatment response is challenging because magnetic resonance imaging (MRI) may not distinguish true progression (TP) from pseudoprogression (PsP). This review aims to discuss imaging techniques and liquid biopsies used to distinguish TP from PsP.

MATERIALS AND METHODS

This review synthesizes existing literature to examine advances in imaging techniques, such as magnetic resonance diffusion imaging (MRDI), perfusion-weighted imaging (PWI) MRI, and liquid biopsies, for identifying TP or PsP through tumor markers and tissue characteristics.

RESULTS

Advanced imaging techniques, including MRDI and PWI MRI, have proven effective in delineating tumor tissue properties, offering valuable insights into glioma behavior. Similarly, liquid biopsy has emerged as a potent tool for identifying tumor-derived markers in biofluids, offering a non-invasive glimpse into tumor evolution. Despite their promise, these methodologies grapple with significant challenges. Their sensitivity remains inconsistent, complicating the accurate differentiation between TP and PSP. Furthermore, the absence of standardized protocols across platforms impedes the reliability of comparisons, while inherent biological variability adds complexity to data interpretation.

CONCLUSION

Their potential applications have been highlighted, but gaps remain before routine clinical use. Further research is needed to develop and validate these promising methods for distinguishing TP from PsP in gliomas.

The role of [18 F]FDOPA PET as an adjunct to conventional MRI in the diagnosis of aggressive glial lesions

BACKGROUND

Amino acid PET is recommended for the initial diagnosis of brain lesions, but its value for identifying aggressive lesions remains to be established. The current study therefore evaluates the added-value of dynamic [18 F]FDOPA PET as an adjunct to conventional MRI for determining the aggressiveness of presumed glial lesions at diagnosis.

METHODS

Consecutive patients, with a minimal 1 year-follow-up, underwent contrast-enhanced MRI (CE MRI) and dynamic [18 F]FDOPA PET to characterize their suspected glial lesion. Lesions were classified semi-automatically by their CE MRI (MRI-/+), and PET parameters (static tumor-to-background ratio, TBR; dynamic time-to-peak ratio, TTPratio). Diagnostic accuracies of MRI and PET parameters for the differentiation of tumor aggressiveness were evaluated by chi-square test or receiver operating characteristic analyses. Aggressive lesions were either defined as lesions with dismal molecular characteristics based on the WHO 2021 classification of brain tumors or with compatible clinico-radiological profiles. Time-to-treatment failure (TTF) and overall survival (OS) were evaluated.

RESULTS

Of the 109 patients included, 46 had aggressive lesions (45 confirmed by histo-molecular analyses). CE MRI identified aggressive lesions with an accuracy of 73%. TBRmax (threshold of 3.2), and TTPratio (threshold of 5.4 min) respectively identified aggressive lesions with an accuracy of 83% and 76% and were independent of CE MRI and clinical factors in the multivariate analysis. Among the MRI-lesions, 11/56 (20%) were aggressive and respectively 55% and 50% of these aggressive lesions showed high TBRmax and short TTPratio in PET. High TBRmax and short TTPratio in PET were significantly associated to poorer survivals (p ≤ 0.009).

CONCLUSION

Dynamic [18 F]FDOPA PET provides a similar diagnostic accuracy as contrast enhancement in MRI to identify the aggressiveness of suspected glial lesions at diagnosis. Both methods, however, are complementary and [18 F]FDOPA PET may be a useful additional tool in equivocal cases.

RNA biomarkers in cancer therapeutics: The promise of personalized oncology

Cancer therapy is a rapidly evolving and constantly expanding field. Current approaches include surgery, conventional chemotherapy and novel biologic agents as in immunotherapy, that together compose a wide armamentarium. The plethora of choices can, however, be clinically challenging in prescribing the most suitable treatment for any given patient. Fortunately, biomarkers can greatly facilitate the most appropriate selection. In recent years, RNA-based biomarkers have proven most promising. These molecules that range from small noncoding RNAs to protein coding gene transcripts can be valuable in cancer management and especially in cancer therapeutics. Compared to their DNA counterparts which are stable throughout treatment, RNA-biomarkers are dynamic. This allows prediction of success prior to treatment start and can identify alterations in expression that could reflect response. Moreover, improved nucleic acid technology allows RNA to be extracted from practically every biofluid/matrix and evaluated with exceedingly high analytic sensitivity. In addition, samples are largely obtained by minimally invasive procedures and as such can be used serially to assess treatment response real-time. This chapter provides the reader insight on currently known RNA biomarkers, the latest research employing Artificial Intelligence in the identification of such molecules and in clinical decisions driving forward the era of personalized oncology.

Amide proton transfer weighted imaging in pediatric neuro-oncology: initial experience

Amide proton transfer weighted (APTw) imaging enables in vivo assessment of tissue-bound mobile proteins and peptides through the detection of chemical exchange saturation transfer. Promising applications of APTw imaging have been shown in adult brain tumors. As pediatric brain tumors differ from their adult counterparts, we investigate the radiological appearance of pediatric brain tumors on APTw imaging. APTw imaging was conducted at 3 T. APTw maps were calculated using magnetization transfer ratio asymmetry at 3.5 ppm. First, the repeatability of APTw imaging was assessed in a phantom and in five healthy volunteers by calculating the within-subject coefficient of variation (wCV). APTw images of pediatric brain tumor patients were analyzed retrospectively. APTw levels were compared between solid tumor tissue and normal-appearing white matter (NAWM) and between pediatric high-grade glioma (pHGG) and pediatric low-grade glioma (pLGG) using t-tests. APTw maps were repeatable in supratentorial and infratentorial brain regions (wCV ranged from 11% to 39%), except those from the pontine region (wCV between 39% and 50%). APTw images of 23 children with brain tumor were analyzed (mean age 12 years ± 5, 12 male). Significantly higher APTw values are present in tumor compared with NAWM for both pHGG and pLGG (p < 0.05). APTw values were higher in pLGG subtype pilocytic astrocytoma compared with other pLGG subtypes (p < 0.05). Non-invasive characterization of pediatric brain tumor biology with APTw imaging could aid the radiologist in clinical decision-making.

Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits

BACKGROUND AND OBJECTIVES

In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditionally been the gold standard for maximizing tumor resection and improving patient outcomes. However, recent Level 1 evidence juxtaposes the efficacy of iMRI and 5-aminolevulinic acid (5-ALA), questioning the continued justification of iMRI because of its associated costs and extended surgical duration. Nonetheless, drawing from our clinical observations, we postulated that a subset of intricate HGGs may continue to benefit from the adjunctive application of iMRI.

METHODS

In a prospective study of 73 patients with HGG, 5-ALA was the primary technique for tumor delineation, complemented by iMRI to detect residual contrast-enhanced regions. Suboptimal 5-ALA efficacy was defined when (1) iMRI detected contrast-enhanced remnants despite 5-ALA's indication of a gross total resection or (2) surgeons observed residual fluorescence, contrary to iMRI findings. Radiomic features from preoperative MRIs were extracted using a U2-Net deep learning algorithm. Binary logistic regression was then used to predict compromised 5-ALA performance.

RESULTS

Resections guided solely by 5-ALA achieved an average removal of 93.14% of contrast-enhancing tumors. This efficacy increased to 97% with iMRI integration, albeit not statistically significant. Notably, for tumors with suboptimal 5-ALA performance, iMRI's inclusion significantly improved resection outcomes ( P -value: .00013). The developed deep learning-based model accurately pinpointed these scenarios, and when enriched with radiomic parameters, showcased high predictive accuracy, as indicated by a Nagelkerke R 2 of 0.565 and a receiver operating characteristic of 0.901.

CONCLUSION

Our machine learning-driven radiomics approach predicts scenarios where 5-ALA alone may be suboptimal in HGG surgery compared with its combined use with iMRI. Although 5-ALA typically yields favorable results, our analyses reveal that HGGs characterized by significant volume, complex morphology, and left-sided location compromise the effectiveness of resections relying exclusively on 5-ALA. For these intricate cases, we advocate for the continued relevance of iMRI.

7 Tesla magnetic resonance spectroscopic imaging predicting IDH status and glioma grading

INTRODUCTION

With the application of high-resolution 3D 7 Tesla Magnetic Resonance Spectroscopy Imaging (MRSI) in high-grade gliomas, we previously identified intratumoral metabolic heterogeneities. In this study, we evaluated the potential of 3D 7 T-MRSI for the preoperative noninvasive classification of glioma grade and isocitrate dehydrogenase (IDH) status. We demonstrated that IDH mutation and glioma grade are detectable by ultra-high field (UHF) MRI. This technique might potentially optimize the perioperative management of glioma patients.

METHODS

We prospectively included 36 patients with WHO 2021 grade 2-4 gliomas (20 IDH mutated, 16 IDH wildtype). Our 7 T 3D MRSI sequence provided high-resolution metabolic maps (e.g., choline, creatine, glutamine, and glycine) of these patients' brains. We employed multivariate random forest and support vector machine models to voxels within a tumor segmentation, for classification of glioma grade and IDH mutation status.

RESULTS

Random forest analysis yielded an area under the curve (AUC) of 0.86 for multivariate IDH classification based on metabolic ratios. We distinguished high- and low-grade tumors by total choline (tCho) / total N-acetyl-aspartate (tNAA) ratio difference, yielding an AUC of 0.99. Tumor categorization based on other measured metabolic ratios provided comparable accuracy.

CONCLUSIONS

We successfully classified IDH mutation status and high- versus low-grade gliomas preoperatively based on 7 T MRSI and clinical tumor segmentation. With this approach, we demonstrated imaging based tumor marker predictions at least as accurate as comparable studies, highlighting the potential application of MRSI for pre-operative tumor classifications.

Phase 2 Study of Sorafenib, Valproic Acid, and Sildenafil in the Treatment of Recurrent High-Grade Glioma

Here we report the results of a single-center phase 2 clinical trial combining sorafenib tosylate, valproic acid, and sildenafil for the treatment of patients with recurrent high-grade glioma (NCT01817751). Clinical toxicities were grade 1 and grade 2, with one grade 3 toxicity for maculopapular rash (6.4%). For all evaluable patients, the median progression-free survival was 3.65 months and overall survival (OS) 10.0 months. There was promising evidence showing clinical activity and benefit. In the 33 evaluable patients, low protein levels of the chaperone GRP78 (HSPA5) was significantly associated with a better OS (p < 0.0026). A correlation between the expression of PDGFRα and OS approached significance (p < 0.0728). Five patients presently have a mean OS of 73.6 months and remain alive. This is the first therapeutic intervention glioblastoma trial to significantly associate GRP78 expression to OS. Our data suggest that the combination of sorafenib tosylate, valproic acid, and sildenafil requires additional clinical development in the recurrent glioma population.

Methyl-11C-L-methionine positron emission tomography for radiotherapy planning for recurrent malignant glioma

OBJECTIVE

To investigate differences in uptake regions between methyl-11C-L-methionine positron emission tomography (11C-MET PET) and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI), and their impact on dose distribution, including changing of the threshold for tumor boundaries.

METHODS

Twenty consecutive patients with grade 3 or 4 glioma who had recurrence after postoperative radiotherapy (RT) between April 2016 and October 2017 were examined. The study was performed using simulation with the assumption that all patients received RT. The clinical target volume (CTV) was contoured using the Gd-enhanced region (CTV(Gd)), the tumor/normal tissue (T/N) ratios of 11C-MET PET of 1.3 and 2.0 (CTV (T/N 1.3), CTV (T/N 2.0)), and the PET-edge method (CTV(P-E)) for stereotactic RT planning. Differences among CTVs were evaluated. The brain dose at each CTV and the dose at each CTV defined by 11C-MET PET using MRI as the reference were evaluated.

RESULTS

The Jaccard index (JI) for concordance of CTV (Gd) with CTVs using 11C-MET PET was highest for CTV (T/N 2.0), with a value of 0.7. In a comparison of pixel values of MRI and PET, the correlation coefficient for cases with higher JI was significantly greater than that for lower JI cases (0.37 vs. 0.20, P = 0.007). D50% of the brain in RT planning using each CTV differed significantly (P = 0.03) and that using CTV (T/N 1.3) were higher than with use of CTV (Gd). V90% and V95% for each CTV differed in a simulation study for actual treatment using CTV (Gd) (P = 1.0 × 10-7 and 3.0 × 10-9, respectively) and those using CTV (T/N 1.3) and CTV (P-E) were lower than with CTV (Gd).

CONCLUSIONS

The region of 11C-MET accumulation is not necessarily consistent with and larger than the Gd-enhanced region. A change of the tumor boundary using 11C-MET PET can cause significant changes in doses to the brain and the CTV.

Dexamethasone in Patients with Glioblastoma: A Systematic Review and Meta-Analysis

OBJECTIVE

Glioblastomas are the most common primary central nervous system (CNS) tumors. Although modern management strategies have modestly improved overall survival, the prognosis remains dismal, with treatment side effects often impinging on the clinical course. Glioblastomas cause neurological dysfunction by infiltrating CNS tissue and via perifocal oedema formation. The administration of steroids such as dexamethasone is thought to alleviate symptoms by reducing oedema. However, despite its widespread use, the evidence for the administration of dexamethasone is limited and conflicting. Therefore, we aimed to review the current evidence concerning the use and outcomes of dexamethasone in patients with glioblastoma.

METHODS

We performed a systematic review and meta-analysis according to the PRISMA-P guidelines. We performed a restricted search using the keywords "Dexamethasone" and "Glioblastoma" on PubMed, Web of Science, Cochrane Library, and Academic Search Premier. We included studies reporting on overall survival (OS) and progression-free survival (PFS) in glioblastoma patients receiving higher or lower dexamethasone doses. The risk of bias was assessed using ROBINS-I. We performed a meta-analysis using a random effects model for OS and PFS.

RESULTS

Twenty-two retrospective studies were included. Higher doses of dexamethasone were associated with poorer OS (hazard ratio 1.62, confidence interval 1.40-1.88) and PFS (1.49, 1.23-1.81). OS remained worse even when studies corrected for clinical status (1.52, 1.38-1.67).

CONCLUSION

Despite the widespread use of dexamethasone in glioblastoma patients, its use is correlated with worse long-term outcomes. Consequently, Dexamethasone administration should be restricted to selected symptomatic patients. Future prospective studies are crucial to confirm these findings.

Challenges in radiological evaluation of brain metastases, beyond progression

MRI is the cornerstone in the evaluation of brain metastases. The clinical challenges lie in discriminating metastases from mimickers such as infections or primary tumors and in evaluating the response to treatment. The latter sometimes leads to growth, which must be framed as pseudo-progression or radionecrosis, both inflammatory phenomena attributable to treatment, or be considered as recurrence. To meet these needs, imaging techniques are the subject of constant research. However, an exponential growth after radiotherapy must be interpreted with caution, even in the presence of results suspicious of tumor progression by advanced techniques, because it may be due to inflammatory changes. The aim of this paper is to familiarize the reader with inflammatory phenomena of brain metastases treated with radiotherapy and to describe two related radiological signs: "the inflammatory cloud" and "incomplete ring enhancement", in order to adopt a conservative management with close follow-up.

Glioblastoma Therapy: Past, Present and Future

Glioblastoma (GB) stands out as the most prevalent and lethal form of brain cancer. Although great efforts have been made by clinicians and researchers, no significant improvement in survival has been achieved since the Stupp protocol became the standard of care (SOC) in 2005. Despite multimodality treatments, recurrence is almost universal with survival rates under 2 years after diagnosis. Here, we discuss the recent progress in our understanding of GB pathophysiology, in particular, the importance of glioma stem cells (GSCs), the tumor microenvironment conditions, and epigenetic mechanisms involved in GB growth, aggressiveness and recurrence. The discussion on therapeutic strategies first covers the SOC treatment and targeted therapies that have been shown to interfere with different signaling pathways (pRB/CDK4/RB1/P16ink4, TP53/MDM2/P14arf, PI3k/Akt-PTEN, RAS/RAF/MEK, PARP) involved in GB tumorigenesis, pathophysiology, and treatment resistance acquisition. Below, we analyze several immunotherapeutic approaches (i.e., checkpoint inhibitors, vaccines, CAR-modified NK or T cells, oncolytic virotherapy) that have been used in an attempt to enhance the immune response against GB, and thereby avoid recidivism or increase survival of GB patients. Finally, we present treatment attempts made using nanotherapies (nanometric structures having active anti-GB agents such as antibodies, chemotherapeutic/anti-angiogenic drugs or sensitizers, radionuclides, and molecules that target GB cellular receptors or open the blood-brain barrier) and non-ionizing energies (laser interstitial thermal therapy, high/low intensity focused ultrasounds, photodynamic/sonodynamic therapies and electroporation). The aim of this review is to discuss the advances and limitations of the current therapies and to present novel approaches that are under development or following clinical trials.

Application of PET imaging delta radiomics for predicting progression-free survival in rare high-grade glioma

This study assesses the feasibility of using a sample-efficient model to investigate radiomics changes over time for predicting progression-free survival in rare diseases. Eighteen high-grade glioma patients underwent two L-3,4-dihydroxy-6-[18F]-fluoro-phenylalanine positron emission tomography (PET) dynamic scans: the first during treatment and the second at temozolomide chemotherapy discontinuation. Radiomics features from static/dynamic parametric images, alongside conventional features, were extracted. After excluding highly correlated features, 16 different models were trained by combining various feature selection methods and time-to-event survival algorithms. Performance was assessed using cross-validation. To evaluate model robustness, an additional dataset including 35 patients with a single PET scan at therapy discontinuation was used. Model performance was compared with a strategy extracting informative features from the set of 35 patients and applying them to the 18 patients with 2 PET scans. Delta-absolute radiomics achieved the highest performance when the pipeline was directly applied to the 18-patient subset (support vector machine (SVM) and recursive feature elimination (RFE): C-index = 0.783 [0.744-0.818]). This result remained consistent when transferring informative features from 35 patients (SVM + RFE: C-index = 0.751 [0.716-0.784], p = 0.06). In addition, it significantly outperformed delta-absolute conventional (C-index = 0.584 [0.548-0.620], p < 0.001) and single-time-point radiomics features (C-index = 0.546 [0.512-0.580], p < 0.001), highlighting the considerable potential of delta radiomics in rare cancer cohorts.

Everolimus for Children With Recurrent or Progressive Low-Grade Glioma: Results From the Phase II PNOC001 Trial

PURPOSE

The PNOC001 phase II single-arm trial sought to estimate progression-free survival (PFS) associated with everolimus therapy for progressive/recurrent pediatric low-grade glioma (pLGG) on the basis of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway activation as measured by phosphorylated-ribosomal protein S6 and to identify prognostic and predictive biomarkers.

PATIENTS AND METHODS

Patients, age 3-21 years, with progressive/recurrent pLGG received everolimus orally, 5 mg/m2 once daily. Frequency of driver gene alterations was compared among independent pLGG cohorts of newly diagnosed and progressive/recurrent patients. PFS at 6 months (primary end point) and median PFS (secondary end point) were estimated for association with everolimus therapy.

RESULTS

Between 2012 and 2019, 65 subjects with progressive/recurrent pLGG (median age, 9.6 years; range, 3.0-19.9; 46% female) were enrolled, with a median follow-up of 57.5 months. The 6-month PFS was 67.4% (95% CI, 60.0 to 80.0) and median PFS was 11.1 months (95% CI, 7.6 to 19.8). Hypertriglyceridemia was the most common grade ≥3 adverse event. PI3K/AKT/mTOR pathway activation did not correlate with clinical outcomes (6-month PFS, active 68.4% v nonactive 63.3%; median PFS, active 11.2 months v nonactive 11.1 months; P = .80). Rare/novel KIAA1549::BRAF fusion breakpoints were most frequent in supratentorial midline pilocytic astrocytomas, in patients with progressive/recurrent disease, and correlated with poor clinical outcomes (median PFS, rare/novel KIAA1549::BRAF fusion breakpoints 6.1 months v common KIAA1549::BRAF fusion breakpoints 16.7 months; P < .05). Multivariate analysis confirmed their independent risk factor status for disease progression in PNOC001 and other, independent cohorts. Additionally, rare pathogenic germline variants in homologous recombination genes were identified in 6.8% of PNOC001 patients.

CONCLUSION

Everolimus is a well-tolerated therapy for progressive/recurrent pLGGs. Rare/novel KIAA1549::BRAF fusion breakpoints may define biomarkers for progressive disease and should be assessed in future clinical trials.

[Choice of fractionation regimen for Grade IV gliomas depending on rapid early progression]

OBJECTIVE

To investigate the effect of two fractionation regimens on survival in patients with Grade IV gliomas depending on rapid early progression (REP).

MATERIAL AND METHODS

Fractionation with prescribed doses of 2 and 3 Gy was alternately used in 140 patients with morphologically confirmed Grade IV glioma using a pairwise modeling strategy.

RESULTS

REP was diagnosed in 60 (42.9%) out of 140 patients with Grade IV gliomas and 55 (45.5%) out of 121 patients with glioblastomas. Fatal outcome was observed in 111 (79.3%) patients, 99 (70.7%) ones died from progression of glioma. In case of no REP, the median overall survival as of December 2023 was 32.20 (95% CI 25.7-38.7) months, with REP - only 16.03 (95% CI 13.5-18.6) months (p<0.0001). Median survival was slightly lower in patients with glioblastoma - 28.2 and 16.5 months, respectively (p<0.0001).

In patients with Grade IV gliomas and no REP, 3 Gy (n=40) fractionation regimen was followed by median overall survival 44.98 (95% Cl 15.3-74.6) months, 2 Gy (n=40) - 20.99 (95% CI 9.2-32.7) months (p=0.027). In case of glioblastoma, differences between fractionation regimes lose significance - medians 33.7 and 19.7 months, respectively (p=0.081). According to multivariate analysis, 3 Gy fractionation regimen is more effective than standard radiotherapy (p=0.009) in patients without REP, while significance of isoeffective doses <59.5Gy≥ is slightly lower (p=0.020). Radiotherapy on the background of temozolomide is equally important (p=0.007).

In patients with grade 4 gliomas and REP, 3 Gy (n=30) fractionation regimen was followed by median overall survival 17.18 (95% CI 14.2-20.2) months, 2 Gy (n=30) - 12.88 (95% CI 5.4-20.3) months (p=0.849). In case of glioblastoma, Cox model classification matrix looks as follows: fractionation variant (p=0.423), isoeffective dose <59.5Gy≥ (p<0.0001), temozolomide during radiotherapy (p=0.701), functional status (p=0.485).

CONCLUSION

In patients with Grade IV gliomas and no REP, 3 Gy fractionation regimen has significant advantages over standard radiotherapy regarding overall survival. In case of more aggressive course of tumor (REP), higher single dose does not improve treatment outcomes. Isoeffective dose ≥59.5Gy is of great importance.

[89Zr]-CD8 ImmunoPET imaging of glioblastoma multiforme response to combination oncolytic viral and checkpoint inhibitor immunotherapy reveals CD8 infiltration differential changes in preclinical models

Rationale: Novel immune-activating therapeutics for the treatment of glioblastoma multiforme (GBM) have shown potential for tumor regression and increased survival over standard therapies. However, immunotherapy efficacy remains inconsistent with response assessment being complicated by early treatment-induced apparent radiological tumor progression and slow downstream effects. This inability to determine early immunotherapeutic benefit results in a drastically decreased window for alternative, and potentially more effective, treatment options. The objective of this study is to evaluate the effects of combination immunotherapy on early CD8+ cell infiltration and its association with long term response in orthotopic syngeneic glioblastoma models. Methods: Luciferase positive GBM orthotopic mouse models (GSC005-luc) were imaged via [89Zr]-CD8 positron emission tomography (PET) one week following treatment with saline, anti-PD1, M002 oncolytic herpes simplex virus (oHSV) or combination immunotherapy. Subsequently, brains were excised, imaged via [89Zr]-CD8 ImmunoPET and evaluated though autoradiography and histology for H&E and CD8 immunohistochemistry. Longitudinal immunotherapeutic effects were evaluated through [89Zr]-CD8 PET imaging one- and three-weeks following treatment, with changes in tumor volume monitored on a three-day basis via bioluminescence imaging (BLI). Response classification was then performed based on long-term BLI signal changes. Statistical analysis was performed between groups using one-way ANOVA and two-sided unpaired T-test, with p < 0.05 considered significant. Correlations between imaging and biological validation were assessed via Pearson's correlation test. Results: [89Zr]-CD8 PET standardized uptake value (SUV) quantification was correlated with ex vivo SUV quantification (r = 0.61, p < 0.01), autoradiography (r = 0.46, p < 0.01), and IHC tumor CD8+ cell density (r = 0.55, p < 0.01). Classification of therapeutic responders, via bioluminescence signal, revealed a more homogeneous CD8+ immune cell distribution in responders (p < 0.05) one-week following immunotherapy. Conclusions: Assessment of early CD8+ cell infiltration and distribution in the tumor microenvironment provides potential imaging metrics for the characterization of oHSV and checkpoint blockade immunotherapy response in GBM. The combination therapies showed enhanced efficacy compared to single agent immunotherapies. Further development of immune-focused imaging methods can provide clinically relevant metrics associated with immune cell localization that can inform immunotherapeutic efficacy and subsequent treatment response in GBM patients.

Tumor volume features predict survival outcomes for patients diagnosed with diffuse intrinsic pontine glioma

Background

Diffuse intrinsic pontine glioma (DIPG) is a fatal childhood central nervous system tumor. Diagnosis and monitoring of tumor response to therapy is based on magnetic resonance imaging (MRI). MRI-based analyses of tumor volume and appearance may aid in the prediction of patient overall survival (OS).

Methods

Contrast-enhanced T1- and FLAIR/T2-weighted MR images were retrospectively collected from children with classical DIPG diagnosed by imaging (n = 43 patients). MRI features were evaluated at diagnosis (n = 43 patients) and post-radiation (n = 40 patients) to determine OS outcome predictors. Features included 3D tumor volume (Twv), contrast-enhancing tumor core volume (Tc), Tc relative to Twv (TC/Twv), and Twv relative to whole brain volume. Support vector machine (SVM) learning was used to identify feature combinations that predicted OS outcome (defined as OS shorter or longer than 12 months from diagnosis).

Results

Features associated with poor OS outcome included the presence of contrast-enhancing tumor at diagnosis, >15% Tc/Twv post-radiation therapy (RT), and >20% ∆Tc/Twv post-RT. Consistently, SVM learning identified Tc/Twv at diagnosis (prediction accuracy of 74%) and ∆Tc/Twv at <2 months post-RT (accuracy = 75%) as primary features of poor survival.

Conclusions

This study demonstrates that tumor imaging features at diagnosis and within 4 months of RT can predict differential OS outcomes in DIPG. These findings provide a framework for incorporating tumor volume-based predictive analyses into the clinical setting, with the potential for treatment customization based on tumor risk characteristics and future applications of machine-learning-based analysis.

Pyruvate kinase M2 (PKM-2) expression and prognostic significance in glioblastoma patients

PURPOSE

Pyruvate kinase M2 (PKM2) is a key enzyme that catalyzes the irreversible and final step of glycolysis. It is closely associated with cancer development and progression. The relationship between PKM2 and prognosis in glioblastoma (GB) patients is unknown. The aim of this study was to measure PKM2 expression and evaluate its effect on prognosis in GB patients.

METHODS

Patients who underwent radiotherapy (RT) for glioblastoma between 2010 and 2021 were evaluated immunohistochemically. A single pathologist evaluated pathology specimens of all patients. The intensity and extent of staining of tumor cells were scored. Patients were categorized as low and high PKM2.

RESULTS

A total of 119 patients were evaluated. While 80.7% of the cases had a low score, 19.3% had a high PKM2 score. It was observed that the group with high PKM2 expression had lower performance, received more hypofractionated RT and received adjuvant chemotherapy (CT) less frequently. Median overall survival (OS) was 15.77 months in the low PKM2 expression group and 6.50 months in the high PKM2 group. In univariate analyses, PKM2 expression, age, performance status, type of surgery, RT scheme, and concurrent and adjuvant CT were prognostic factors in predicting OS. In multivariate analyses, PKM2 expression, type of surgery, RT scheme and receiving adjuvant CT were prognostic factors for OS.

CONCLUSION

PKM2 is an independent prognostic factor for survival and is associated with poor prognosis in GBM patients treated with radiotherapy. It may be a potential therapeutic target for anticancer therapy.

Treatment of glioblastoma in Greenlandic patients

Glioblastoma (GBM), WHO grade IV, is the most common primary malignant brain tumour among adults with a devastating overall survival of 14-22 months. Standard treatment of GBM includes maximum safe resection, radiotherapy plus concomitant and adjuvant temozolomide (TMZ), given over a period of approximately 9 months. Treatment and follow-up for Greenlandic patients with GBM are managed at Rigshospitalet (RH), Copenhagen. Greenlandic GBM patients, therefore, travel back and forth to RH, often unaccompanied, and challenged by cognitive failure or other symptoms from their disease and/or treatment. Few Greenlandic patients are diagnosed with GBM annually, but considering the poor prognosis and short remaining lifespan, it would be preferable to limit their travels. TMZ is administrated as capsules. Health personnel at Queen Ingrid's Hospital (DIH), Nuuk, are trained in treating other oncological diseases and handling side effects. Hence, it could be investigated whether administration of adjuvant TMZ at DIH could be feasible after personnel education as well as economic consideration and compensation, in close collaboration with neuro oncologists at RH. In this article, we describe the Greenlandic cancer treatment, and the typical workflow from diagnosis of GBM to treatment to progression.

Post-chemo-radiotherapy response and pseudo-progression evaluation on glioma cell types by multi-parametric magnetic resonance imaging: a prospective study

BACKGROUND

We focused on Differentiated pseudoprogression (PPN) of progression (PN) and the response to radiotherapy (RT) or chemoradiotherapy (CRT) using diffusion and metabolic imaging.

METHODS

Seventy-five patients with glioma were included in this prospective study (approved by the Iranian Registry of Clinical Trials (IRCT) (IRCT20230904059352N1) in September 2023). Contrast-enhanced lesion volume (CELV), non-enhanced lesion volume (NELV), necrotic tumor volume (NTV), and quantitative values ​​of apparent diffusion coefficient (ADC) and magnetic resonance spectroscopy (Cho/Cr, Cho/NAA and NAA/Cr) were calculated by a neuroradiologist using a semi-automatic method. All patients were followed at one and six months after CRT.

RESULTS

The results of the study showed statistically significant changes before and six months after RT-CRT for M-CELV in all glioma types (𝑝 < 0.05). In glioma cell types, the changes in M-ADC, M-Cho/Cr, and Cho/NAA indices for PN were incremental and greater for PPN patients. M-NAA/Cr ratio decreased after six months which was significant only on PN for GBM, and Epn (𝑝 < 0.05). A significant difference was observed between diffusion indices, metabolic ratios, and CELV changes after six months in all types (𝑝 < 0.05). None of the patients were suspected PPN one month after treatment. The DWI/ADC indices had higher sensitivity and specificity (98.25% and 96.57%, respectively).

CONCLUSION

The results of the present study showed that ADC values and Cho/Cr and Cho/NAA ratios can be used to differentiate between patients with PPN and PN, although ADC is more sensitive and specific.

Predictors for delayed awakening in adult glioma patients receiving awake craniotomy under monitored anesthesia care

PURPOSE

Delayed awakening after anesthetic discontinuation during awake craniotomy is associated with somnolence during functional brain mapping. However, predictors of delayed awakening in patients receiving monitored anesthesia care for awake craniotomy are unknown.

METHODS

This retrospective cohort study analyzed 117 adult patients with supratentorial glioma in or near eloquent areas who received monitored anesthesia care for awake craniotomy between July 2020 and January 2023 at Linkou Chang Gung Memorial Hospital. These patients were divided into two groups according to their time to awakening (ability to speak their names) after propofol cessation: longer or shorter than 20 min (median duration). Because propofol was solely used anesthetic from skin incision to dural opening, parameters in Schnider model for propofol target-controlled infusion, such as age, sex, and BMI, were adjusted or propensity-matched to compare their anesthetic, surgical, and histopathological profiles.

RESULTS

After propensity-matched comparisons of age and BMI, significant predictors of delayed awakening included IDH1 wild-type tumors and repeated craniotomies. Subgroup analysis revealed that older age and larger T2 volume were predictors in patients undergoing the first craniotomy, while lower preoperative Karnofsky performance scale scores and depression were predictors in repeated craniotomy cases. Delayed awakening was also associated with somnolence and a lower gross total resection rate.

CONCLUSION

Our retrospective analysis of patients receiving monitored anesthesia care for awake craniotomy revealed that delayed awakening after propofol discontinuation occurred more often in patients with IDH1 wild-type tumors and repeated craniotomies. Also, delayed awakening was associated with somnolence during functional mapping and a lower gross total resection rate.

A Deep Learning Approach for Automatic Segmentation during Daily MRI-Linac Radiotherapy of Glioblastoma

Glioblastoma changes during chemoradiotherapy are inferred from high-field MRI before and after treatment but are rarely investigated during radiotherapy. The purpose of this study was to develop a deep learning network to automatically segment glioblastoma tumors on daily treatment set-up scans from the first glioblastoma patients treated on MRI-linac. Glioblastoma patients were prospectively imaged daily during chemoradiotherapy on 0.35T MRI-linac. Tumor and edema (tumor lesion) and resection cavity kinetics throughout the treatment were manually segmented on these daily MRI. Utilizing a convolutional neural network, an automatic segmentation deep learning network was built. A nine-fold cross-validation schema was used to train the network using 80:10:10 for training, validation, and testing. Thirty-six glioblastoma patients were imaged pre-treatment and 30 times during radiotherapy (n = 31 volumes, total of 930 MRIs). The average tumor lesion and resection cavity volumes were 94.56 ± 64.68 cc and 72.44 ± 35.08 cc, respectively. The average Dice similarity coefficient between manual and auto-segmentation for tumor lesion and resection cavity across all patients was 0.67 and 0.84, respectively. This is the first brain lesion segmentation network developed for MRI-linac. The network performed comparably to the only other published network for auto-segmentation of post-operative glioblastoma lesions. Segmented volumes can be utilized for adaptive radiotherapy and propagated across multiple MRI contrasts to create a prognostic model for glioblastoma based on multiparametric MRI.

Apparent Diffusion Coefficient Metrics to Differentiate between Treatment-Related Abnormalities and Tumor Progression in Post-Treatment Glioblastoma Patients: A Retrospective Study

Distinguishing treatment-related abnormalities (TRA) from tumor progression (TP) in glioblastoma patients is a diagnostic imaging challenge due to the identical morphology of conventional MR imaging sequences. Diffusion-weighted imaging (DWI) and its derived images of the apparent diffusion coefficient (ADC) have been suggested as diagnostic tools for this problem. The aim of this study is to determine the diagnostic accuracy of different cut-off values of the ADC to differentiate between TP and TRA. In total, 76 post-treatment glioblastoma patients with new contrast-enhancing lesions were selected. Lesions were segmented using a T1-weighted, contrast-enhanced scan. The mean ADC values of the segmentations were compared between TRA and TP groups. Diagnostic accuracy was compared by use of the area under the curve (AUC) and the derived sensitivity and specificity values from cutoff points. Although ADC values in TP (mean = 1.32 × 10-3 mm2/s; SD = 0.31 × 10-3 mm2/s) were significantly different compared to TRA (mean = 1.53 × 10-3 mm2/s; SD = 0.28 × 10-3 mm2/s) (p = 0.003), considerable overlap in their distributions exists. The AUC of ADC values to distinguish TP from TRA was 0.71, with a sensitivity and specificity of 65% and 70%, respectively, at an ADC value of 1.47 × 10-3 mm2/s. These findings therefore indicate that ADC maps should not be used in discerning between TP and TRA at a certain timepoint without information on temporal evolution.

Comparison of clinically available dynamic susceptibility contrast post processing software to differentiate progression from pseudoprogression in post-treatment high grade glioma

INTRODUCTION

The purpose of this retrospective study was to compare two, widely available software packages for calculation of Dynamic Susceptibility Contrast (DSC) perfusion MRI normalized relative Cerebral Blood Volume (rCBV) values to differentiate tumor progression from pseudoprogression in treated high-grade glioma patients.

MATERIAL AND METHODS

rCBV maps processed by Siemens Syngo.via (Siemens Healthineers) and Olea Sphere (Olea Medical) software packages were co-registered to contrast-enhanced T1 (T1-CE). Regions of interest based on T1-CE were transferred to the rCBV maps. rCBV was calculated using mean values and normalized using contralateral normal- appearing white matter. The Wilcoxon test was performed to assess for significant differences, and software-specific optimal rCBV cutoff values were determined using the Youden index. Interrater reliability was evaluated for two raters using the intraclass correlation coefficient.

RESULTS

41 patients (18 females; median age = 59 years; range 21-77 years) with 49 new or size-increasing post-treatment contrast-enhancing lesions were included (tumor progression = 40 lesions; pseudoprogression = 9 lesions). Optimal rCBV cutoffs of 1.31 (Syngo.via) and 2.40 (Olea) were significantly different, with an AUC of 0.74 and 0.78, respectively. Interrater reliability was 0.85.

DISCUSSION

We demonstrate that different clinically available MRI DSC-perfusion software packages generate significantly different rCBV cutoff values for the differentiation of tumor progression from pseudoprogression in standard-of-care treated high grade gliomas. Physicians may want to determine the unique value of their perfusion software packages on an institutional level in order to maximize diagnostic accuracy when faced with this clinical challenge. Furthermore, combined with implementation of current DSC-perfusion recommendations, multi-center comparability will be improved.