Treatment-related changes in glioblastoma: a review on the controversies in response assessment criteria and the concepts of true progression, pseudoprogression, pseudoresponse and radionecrosis

Development and validation of a MRI-radiomics-based machine learning approach in High Grade Glioma to detect early recurrence

Purpose

Patients diagnosed with High Grade Gliomas (HGG) generally tend to have a relatively negative prognosis with a high risk of early tumor recurrence (TR) after post-operative radio-chemotherapy. The assessment of the pre-operative risk of early versus delayed TR can be crucial to develop a personalized surgical approach. The purpose of this article is to predict TR using MRI radiomic analysis.

Methods

Data were retrospectively collected from a database. A total of 248 patients were included based on the availability of 6-month TR results: 188 were used to train the model, the others to externally validate it. After manual segmentation of the tumor, Radiomic features were extracted and different machine learning models were implemented considering a combination of T1 and T2 weighted MR sequences. Receiver Operating Characteristic (ROC) curve was calculated with relative model performance metrics (accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)) at the best threshold based on the Youden Index.

Results

Models performance were evaluated based on test set results. The best model resulted to be the XGBoost, with an area under ROC curve of 0.72 (95% CI: 0.56 - 0.87). At the best threshold, the model exhibits 0.75 (95% CI: 0.63 - 0.75) as accuracy, 0.62 (95% CI: 0.38 - 0.83) as sensitivity 0.80 (95% CI: 0.66 - 0.89 as specificity, 0.53 (95% CI: 0.31 - 0.73) as PPV, 0.88 (95% CI: 0.72 - 0.94) as NPV.

Conclusion

MRI radiomic analysis represents a powerful tool to predict late HGG recurrence, which can be useful to plan personalized surgical treatments and to offer pertinent patient pre-operative counseling.

Circulating Liquid Biopsy Biomarkers in Glioblastoma: Advances and Challenges

Gliomas, particularly glioblastoma (GBM), represent the most prevalent and aggressive tumors of the central nervous system (CNS). Despite recent treatment advancements, patient survival rates remain low. The diagnosis of GBM traditionally relies on neuroimaging methods such as magnetic resonance imaging (MRI) or computed tomography (CT) scans and postoperative confirmation via histopathological and molecular analysis. Imaging techniques struggle to differentiate between tumor progression and treatment-related changes, leading to potential misinterpretation and treatment delays. Similarly, tissue biopsies, while informative, are invasive and not suitable for monitoring ongoing treatments. These challenges have led to the emergence of liquid biopsy, particularly through blood samples, as a promising alternative for GBM diagnosis and monitoring. Presently, blood and cerebrospinal fluid (CSF) sampling offers a minimally invasive means of obtaining tumor-related information to guide therapy. The idea that blood or any biofluid tests can be used to screen many cancer types has huge potential. Tumors release various components into the bloodstream or other biofluids, including cell-free nucleic acids such as microRNAs (miRNAs), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), proteins, extracellular vesicles (EVs) or exosomes, metabolites, and other factors. These factors have been shown to cross the blood-brain barrier (BBB), presenting an opportunity for the minimally invasive monitoring of GBM as well as for the real-time assessment of distinct genetic, epigenetic, transcriptomic, proteomic, and metabolomic changes associated with brain tumors. Despite their potential, the clinical utility of liquid biopsy-based circulating biomarkers is somewhat constrained by limitations such as the absence of standardized methodologies for blood or CSF collection, analyte extraction, analysis methods, and small cohort sizes. Additionally, tissue biopsies offer more precise insights into tumor morphology and the microenvironment. Therefore, the objective of a liquid biopsy should be to complement and enhance the diagnostic accuracy and monitoring of GBM patients by providing additional information alongside traditional tissue biopsies. Moreover, utilizing a combination of diverse biomarker types may enhance clinical effectiveness compared to solely relying on one biomarker category, potentially improving diagnostic sensitivity and specificity and addressing some of the existing limitations associated with liquid biomarkers for GBM. This review presents an overview of the latest research on circulating biomarkers found in GBM blood or CSF samples, discusses their potential as diagnostic, predictive, and prognostic indicators, and discusses associated challenges and future perspectives.

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.

Amino acid PET vs. RANO MRI for prediction of overall survival in patients with recurrent high grade glioma under bevacizumab therapy

PURPOSE

To summarize evidence on the comparative value of amino acid (AA) PET and conventional MRI for prediction of overall survival (OS) in patients with recurrent high grade glioma (rHGG) under bevacizumab therapy.

METHODS

Medical databases were screened for studies with individual data on OS, follow-up MRI, and PET findings in the same patient. MRI images were assessed according to the RANO criteria. A receiver operating characteristic curve analysis was used to predict OS at 9 months.

RESULTS

Five studies with a total of 72 patients were included. Median OS was significantly lower in the PET-positive than in the PET-negative group. PET findings predicted OS with a pooled sensitivity and specificity of 76% and 71%, respectively. Corresponding values for MRI were 32% and 82%. Area under the curve and sensitivity were significantly higher for PET than for MRI.

CONCLUSION

For monitoring of patients with rHGG under bevacizumab therapy, AA-PET should be preferred over RANO MRI.

Validating Brain Tumor Reporting and Data System (BT-RADS) as a Diagnostic Tool for Glioma Follow-Up after Surgery

Gliomas are a type of brain tumor that requires accurate monitoring for progression following surgery. The Brain Tumor Reporting and Data System (BT-RADS) has emerged as a potential tool for improving diagnostic accuracy and reducing the need for repeated operations. This prospective multicenter study aimed to evaluate the diagnostic accuracy and reliability of BT-RADS in predicting tumor progression (TP) in postoperative glioma patients and evaluate its acceptance in clinical practice. The study enrolled patients with a history of partial or complete resection of high-grade glioma. All patients underwent two consecutive follow-up brain MRI examinations. Five neuroradiologists independently evaluated the MRI examinations using the BT-RADS. The diagnostic accuracy of the BT-RADS for predicting TP was calculated using histopathology after reoperation and clinical and imaging follow-up as reference standards. Reliability based on inter-reader agreement (IRA) was assessed using kappa statistics. Reader acceptance was evaluated using a short survey. The final analysis included 73 patients (male, 67.1%; female, 32.9%; mean age, 43.2 ± 12.9 years; age range, 31-67 years); 47.9% showed TP, and 52.1% showed no TP. According to readers, TP was observed in 25-41.7% of BT-3a, 61.5-88.9% of BT-3b, 75-90.9% of BT-3c, and 91.7-100% of BT-RADS-4. Considering >BT-RADS-3a as a cutoff value for TP, the sensitivity, specificity, and accuracy of the BT-RADS were 68.6-85.7%, 84.2-92.1%, and 78.1-86.3%, respectively, according to the reader. The overall IRA was good (κ = 0.75) for the final BT-RADS classification and very good for detecting new lesions (κ = 0.89). The readers completely agreed with the statement "the application of the BT-RADS should be encouraged" (score = 25). The BT-RADS has good diagnostic accuracy and reliability for predicting TP in postoperative glioma patients. However, BT-RADS 3 needs further improvements to increase its diagnostic accuracy.

Low rCBV values in glioblastoma tumor progression under chemoradiotherapy

PURPOSE

After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence.

METHODS

Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software.

RESULTS

Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time.

CONCLUSION

Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.

[18F]-fluoroethyl-L-tyrosine (FET) in glioblastoma (FIG) TROG 18.06 study: protocol for a prospective, multicentre PET/CT trial

INTRODUCTION

Glioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based chemotherapy, tumours inevitably recur. Imaging with O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) has the potential to impact adjuvant radiotherapy (RT) planning, distinguish between treatment-induced pseudoprogression versus tumour progression as well as prognostication.

METHODS AND ANALYSIS

The FET-PET in Glioblastoma (FIG) study is a prospective, multicentre, non-randomised, phase II study across 10 Australian sites and will enrol up to 210 adults aged ≥18 years with newly diagnosed glioblastoma. FET-PET will be performed at up to three time points: (1) following initial surgery and prior to commencement of chemoradiation (FET-PET1); (2) 4 weeks following concurrent chemoradiation (FET-PET2); and (3) within 14 days of suspected clinical and/or radiological progression on MRI (performed at the time of clinical suspicion of tumour recurrence) (FET-PET3). The co-primary outcomes are: (1) to investigate how FET-PET versus standard MRI impacts RT volume delineation and (2) to determine the accuracy and management impact of FET-PET in distinguishing pseudoprogression from true tumour progression. The secondary outcomes are: (1) to investigate the relationships between FET-PET parameters (including dynamic uptake, tumour to background ratio, metabolic tumour volume) and progression-free survival and overall survival; (2) to assess the change in blood and tissue biomarkers determined by serum assay when comparing FET-PET data acquired prior to chemoradiation with other prognostic markers, looking at the relationships of FET-PET versus MRI-determined site/s of progressive disease post chemotherapy treatment with MRI and FET-PET imaging; and (3) to estimate the health economic impact of incorporating FET-PET into glioblastoma management and in the assessment of post-treatment pseudoprogression or recurrence/true progression. Exploratory outcomes include the correlation of multimodal imaging, blood and tumour biomarker analyses with patterns of failure and survival.

ETHICS AND DISSEMINATION

The study protocol V.2.0 dated 20 November 2020 has been approved by a lead Human Research Ethics Committee (Austin Health, Victoria). Other clinical sites will provide oversight through local governance processes, including obtaining informed consent from suitable participants. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results of the FIG study (TROG 18.06) will be disseminated via relevant scientific and consumer forums and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

ANZCTR ACTRN12619001735145.

Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

OBJECTIVE

Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI.

MATERIALS AND METHODS

The study included a total of 66 scans of patients with glioblastoma. Of these, 48 were acquired from 1 MRI vendor and 18 scans were acquired from a different MRI vendor and used as test data. Of the 48, 24 scans had biopsy results. Analysis included semi-automatic arterial input function (AIF) extraction, direct DCE pharmacokinetic-like feature extraction, and unsupervised clustering of the two tissue types. Validation was performed via (a) comparison to biopsy result (b) correlation to literature-based DCE curves for each tissue type, and (c) comparison to clinical outcome.

RESULTS

Consistency between the model prediction and biopsy results was found in 20/24 cases. An average correlation of 82% for active tumor and 90% for treatment-related changes was found between the predicted component and population-based templates. An agreement between the predicted results and radiologist's assessment, based on RANO criteria, was found in 11/12 cases.

CONCLUSION

The proposed method could serve as a non-invasive method for differentiation between lesion tissue and treatment-related changes.

Recent oncolytic virotherapy clinical trials outline a roadmap for the treatment of high-grade glioma

Adult and pediatric high-grade gliomas (HGGs) are aggressive cancers of the central nervous system that confer dismal clinical prognoses. Standard radiation and chemotherapy have demonstrated only limited efficacy in HGGs, motivating the accelerated investigation of novel modalities such as oncolytic virus (OV) therapies. OV centered therapies work through a mixed mechanism centered on oncolysis and the stimulation of an antitumor immune response. Three recent clinical trials utilizing herpes simplex virus-1 and adenovirus-based oncolytic virotherapy demonstrated not only the safety and efficacy of OVs but also novel dosing strategies that augment OV response potential. Considering these recent trials, herein we present a roadmap for future clinical trials of oncolytic immunovirotherapy in both adult and pediatric HGG, as well as persistent roadblocks related to the assessment of OV efficacy within and between trials.

Recent advances in label-free optical, electrochemical, and electronic biosensors for glioma biomarkers

Gliomas are the most commonly occurring primary brain tumor with poor prognosis and high mortality rate. Currently, the diagnostic and monitoring options for glioma mainly revolve around imaging techniques, which often provide limited information and require supervisory expertise. Liquid biopsy is a great alternative or complementary monitoring protocol that can be implemented along with other standard diagnosis protocols. However, standard detection schemes for sampling and monitoring biomarkers in different biological fluids lack the necessary sensitivity and ability for real-time analysis. Lately, biosensor-based diagnostic and monitoring technology has attracted significant attention due to several advantageous features, including high sensitivity and specificity, high-throughput analysis, minimally invasive, and multiplexing ability. In this review article, we have focused our attention on glioma and presented a literature survey summarizing the diagnostic, prognostic, and predictive biomarkers associated with glioma. Further, we discussed different biosensory approaches reported to date for the detection of specific glioma biomarkers. Current biosensors demonstrate high sensitivity and specificity, which can be used for point-of-care devices or liquid biopsies. However, for real clinical applications, these biosensors lack high-throughput and multiplexed analysis, which can be achieved via integration with microfluidic systems. We shared our perspective on the current state-of-the-art different biosensor-based diagnostic and monitoring technologies reported and the future research scopes. To the best of our knowledge, this is the first review focusing on biosensors for glioma detection, and it is anticipated that the review will offer a new pathway for the development of such biosensors and related diagnostic platforms.

Imaging of GBM in the Age of Molecular Markers and MRI Guided Adaptive Radiation Therapy

Glioblastoma (GBM) continues to be one of the most lethal malignancies and is almost always fatal. In this review article, the role of radiation therapy, systemic therapy, as well as the molecular basis of classifying GBM is described. Technological advances in the treatment of GBM are outlined as well as the diagnostic imaging characteristics of this tumor. In addition, factors that affect prognosis such as differentiating progression from treatment effect is discussed. The role of MRI guided radiation therapy and how this technology may provide a mechanism to improve the care of patients with this disease are described.

Early Recurrence Detection of Glioma Using 18 F-Fluorocholine PET/CT : GliReDe Pilot Study

OBJECTIVE

The aim of this study was to analyze the usefulness of 18 F-fluorocholine PET/CT in the early diagnosis of tumor recurrence, increasing the diagnosis confidence of MRI.

METHODS

Patients with a previous gross total resection of glioma and the first suspicious or doubtful for recurrence MRI were prospectively included and subjected to 18 F-fluorocholine PET/CT. An independent and combined assessment of 18 F-fluorocholine PET/CT and multimodal MRI was performed classifying the studies as positive or negative for tumor recurrence. Final diagnosis (recurrence or not) was obtained by histological confirmation or clinical and imaging follow-up. The relation of SUV max and tumor-to-background ratio with progression, the diagnostic performance of imaging techniques, and their concordance (κ Cohen) were analyzed.

RESULTS

Twenty-four studies on 21 patients were assessed. Recurrence was diagnosed in 20 cases. PET/CT was positive in 23 cases (3 false positive), whereas MRI was positive in 15 cases (1 false positive). MRI was false negative in 6 cases. There was no false negative on 18 F-fluorocholine PET/CT. Accuracy of PET/CT versus MRI was 87.5% and 70.8%, respectively. The combined evaluation of both techniques did not show any advantage with respect to PET/CT results alone. The concordance between both imaging techniques was low (κ = 0.135; P = 0.375). SUV max and tumor-to-background ratio were related to recurrence (areas under the curve of 0.844 [ P = 0.033] and 0.869 [ P = 0.022], respectively).

CONCLUSIONS

18 F-fluorocholine PET/CT was helpful for increasing the diagnostic confidence in the cases of MRI doubtful for recurrence in order to avoid a delayed diagnosis.

Multimodal MRI-Based Radiomic Nomogram for the Early Differentiation of Recurrence and Pseudoprogression of High-Grade Glioma

Objective

To evaluate the diagnostic value of multimodal MRI radiomics based on T2-weighted fluid attenuated inversion recovery imaging (T2WI-FLAIR) combined with T1-weighted contrast enhanced imaging (T1WI-CE) in the early differentiation of high-grade glioma recurrence from pseudoprogression.

Methods

A total of one hundred eighteen patients with brain gliomas who were diagnosed from March 2014 to April 2020 were retrospectively analyzed. According to the clinical characteristics, the patients were randomly split into a training group (n = 83) and a test group (n = 35) at a 7 : 3 ratio. The region of interest (ROI) was delineated, and 2632 radiomic features were extracted. We used multiple logistic regression to establish a classification model, including the T1 model, T2 model, and T1 + T2 model, to differentiate recurrence from pseudoprogression. The diagnostic efficiency of the model was evaluated by calculating the area under the receiver operating characteristic curve (AUC) and accuracy (ACC) and by analyzing the calibration curve of the nomogram and decision curve.

Results

There were 75 cases of recurrence and 43 cases of pseudoprogression. The diagnostic efficacies of the multimodal MRI-based radiomic model were relatively high. The AUC values and ACC of the training group were 0.831 and 77.11%, respectively, and the AUC values and ACC of the test group were 0.829 and 88.57%, respectively. The calibration curve of the nomogram showed that the discrimination probability was consistent with the actual occurrence in the training group, and the discrimination probability was roughly the same as the actual occurrence in the test group. In the decision curve analysis, the T1 + T2 model showed greater overall net efficiency.

Conclusion

The multimodal MRI radiomic model has relatively high efficiency in the early differentiation of recurrence from pseudoprogression, and it could be helpful for clinicians in devising correct treatment plans so that patients can be treated in a timely and accurate manner.

A brain tumor reporting and data system to optimize imaging surveillance and prognostication in high-grade gliomas

BACKGROUND AND PURPOSE

High-grade glioma (HGG), including glioblastoma, is the most common primary brain neoplasm and has a dismal prognosis. After initial treatment, follow-up decisions are guided by longitudinal MRI performed at routine intervals. The Brain Tumor Reporting and Data System (BT-RADS) is a proposed structured reporting system for posttreatment brain MRIs. The purpose of this study is to determine the relationship between BT-RADS scores and overall survival in HGG patients.

METHODS

Chart review of grade 4 glioma patients who had an MRI at a single institution from November 2018 to November 2019 was performed. BT-RADS scores, tumor characteristics, and overall survival were recorded. Likelihood of improvement, stability, or worsening on the subsequent study was calculated for each score. Survival analysis was performed using Kaplan-Meier method, log-rank test, and a time-dependent cox model. Significance level of .05 was used.

RESULTS

The study identified 91 HGG patients who underwent a total of 538 MRIs. Mean age of patients was 57 years old. Score with the highest likelihood for worsening on the next follow-up was 3b. The risk of death was 53% higher with each incremental increase in BT-RADS scores (hazard ratio, 1.53; 95% confidence interval [CI], 1.07-2.19; p = .019). The risk of death was 167% higher in O-6-methylguanine-DNA-methyltransferase unmethylated tumors (hazard ratio, 2.67; 95% CI, 1.34-5.33; p = .005).

CONCLUSIONS

BT-RADS scores can be used as a reference guide to anticipate whether patients' subsequent MRI will be improved, stable, or worsened. The scoring system can also be used to predict clinical outcomes and prognosis.

Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma

Simple Summary

Glioma is the most common primary malignant tumor of the adult central nervous system. Despite aggressive multimodal treatment, its prognosis remains poor. During follow-up, it remains challenging to distinguish treatment-related changes from tumor progression in treated patients with gliomas due to both share clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions). The early effective identification of tumor progression and treatment-related changes is of great significance for the prognosis and treatment of gliomas. We believe that advanced neuroimaging techniques can provide additional information for distinguishing both at an early stage. In this article, we focus on the research of magnetic resonance imaging technology and artificial intelligence in tumor progression and treatment-related changes. Finally, it provides new ideas and insights for clinical diagnosis.

Abstract

As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.

Radiomics for pseudoprogression prediction in high grade gliomas: added value of MR contrast agent

Objective

Material & methods

Results

Conclusion

•

Radiomics allows for prediction of pseudoprogression in high-grade gliomas.

•

Use of contrast media boosts the performance of the Radiomics prediction model.

Liquid Biopsy in Glioblastoma

Simple Summary

Glioblastoma is the most common and malignant primary brain tumor. Despite intensive research for new treatments, the survival of patients has not significantly improved in recent decades. Currently, glioblastoma is mainly diagnosed by neuroimaging techniques followed by histopathological and molecular analysis of the resected or biopsied tissue. Both imaging and tissue-based methods have, despite their advantages, some important limitations highlighting the necessity for alternative techniques such as liquid biopsy. It appears as an attractive and non-invasive alternative to support the diagnosis and the follow-up of patients with glioblastoma and to identify early recurrence. Liquid biopsy, primarily through blood tests, involves the detection and quantification of tumoral content released by tumors into the biofluids. The aim of the present review is to discuss the biological bases, the advantages, and the disadvantages of the most important circulating biomarkers so far proposed for glioblastoma.

Abstract

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. Despite recent advances in therapy modalities, the overall survival of GBM patients remains poor. GBM diagnosis relies on neuroimaging techniques. However, confirmation via histopathological and molecular analysis is necessary. Given the intrinsic limitations of such techniques, liquid biopsy (mainly via blood samples) emerged as a non-invasive and easy-to-implement alternative that could aid in both the diagnosis and the follow-up of GBM patients. Cancer cells release tumoral content into the bloodstream, such as circulating tumor DNA, circulating microRNAs, circulating tumor cells, extracellular vesicles, or circulating nucleosomes: all these could serve as a marker of GBM. In this narrative review, we discuss the current knowledge, the advantages, and the disadvantages of each circulating biomarker so far proposed.

Circulating Tumor DNA in Adults With Glioma: A Systematic Review and Meta-Analysis of Biomarker Performance

BACKGROUND

Circulating tumor DNA (ctDNA) has emerged as a promising noninvasive biomarker to capture tumor genetics in patients with brain tumors. Research into its clinical utility, however, has not been standardized because the sensitivity and specificity of ctDNA remain undefined.

OBJECTIVE

To (1) review the primary literature about ctDNA in adults with glioma to compare the sensitivity and specificity of ctDNA in the cerebrospinal fluid vs the plasma and (2) to evaluate the effect of tumor grade on detection of ctDNA.

METHODS

PRISMA-guided systematic review and meta-analysis was performed using published studies that assessed ctDNA in either plasma or cerebrospinal fluid among adult patients with confirmed glioma. Summary receiver operating characteristic curves were generated using the Rücker-Schumacher method, and area under the curve (AUC) was calculated.

RESULTS

Meta-analysis revealed improved biomarker performance for CSF (AUC = 0.947) vs plasma (AUC = 0.741) ctDNA, although this did not reach statistical significance (P = .141). Qualitative analysis revealed greater sensitivities among single-allele PCR and small, targeted next-generation sequencing panels compared with broader panels. It additionally demonstrated higher sensitivity of ctDNA detection in high-grade vs low-grade gliomas, although these analyses were limited by a lack of specificity reporting in many studies.

CONCLUSION

ctDNA seems to be a highly sensitive and specific noninvasive biomarker among adults with gliomas. To maximize its performance, CSF should be studied with targeted genetic analysis platforms, particularly in high-grade gliomas. Further studies on ctDNA are needed to define its clinical utility in diagnosis, prognostication, glioblastoma pseudoprogression, and other scenarios wherein neoadjuvant therapies may be considered.

Pharmacotherapeutic Treatment of Glioblastoma: Where Are We to Date?

The clinical management of glioblastoma (GBM) is still bereft of treatments able to significantly improve the poor prognosis of the disease. Despite the extreme clinical need for novel therapeutic drugs, only a small percentage of patients with GBM benefit from inclusion in a clinical trial. Moreover, often clinical studies do not lead to final interpretable conclusions. From the mistakes and negative results obtained in the last years, we are now able to plan a novel generation of clinical studies for patients with GBM, allowing the testing of multiple anticancer agents at the same time. This assumes critical importance, considering that, thanks to improved knowledge of altered molecular mechanisms related to the disease, we are now able to propose several potential effective compounds in patients with both newly diagnosed and recurrent GBM. Among the novel compounds assessed, the initially great enthusiasm toward trials employing immune checkpoint inhibitors (ICIs) was disappointing due to the negative results that emerged in three randomized phase III trials. However, novel biological insights into the disease suggest that immunotherapy can be a convincing and effective treatment in GBM even if ICIs failed to prolong the survival of these patients. In this regard, the most promising approach consists of engineered immune cells such as chimeric antigen receptor (CAR) T, CAR M, and CAR NK alone or in combination with other treatments. In this review, we discuss several issues related to systemic treatments in GBM patients. First, we assess critical issues toward the planning of clinical trials and the strategies employed to overcome these obstacles. We then move on to the most relevant interventional studies carried out on patients with previously untreated (newly diagnosed) GBM and those with recurrent and pretreated disease. Finally, we investigate novel immunotherapeutic approaches with special emphasis on preclinical and clinical data related to the administration of engineered immune cells in GBM.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Targeted next generation sequencing provides insight for the genetic alterations in liquid biopsy of Egyptian brain tumor patients

Background

Glioblastoma (GBM) is the commonest primary malignant cerebral tumor in adults. Detection of genetic mutations in liquid biopsy is endorsed rapidly throughout several solid neoplasms but still limited in GBM. Our study provides insight for the genetic alterations in liquid biopsy of the newly diagnosed GBM patients using next generation sequencing technology together with identification of the microsatellite instability (MSI) status in those patients.

Results

Eighteen variants detected in 15 genes which were (4, 12 and 2) missense, coding silent and intronic mutations, respectively. The 4 substitution–missense mutations were as follows: Drug responsive TP53 (p.Pro72Arg) variant was detected in 6 patients (85.7%). KDR (p.Gln472His) variant was noted in 4 patients (57.1%) as a result of substitution at c.1416A > T. Two patients revealed KIT (p.Met541Leu) variant which result from substitution at c.1621A > C. Only one patient showed mutation in JAK3 gene which was (p.Val718Leu) variant resulting from c.2152G > C substitution. Regarding MSI status, four cases (57.1%) were MSI-Low and three cases (42.9%) were MSI-High.

Conclusions

This study identifies the molecular landscape and microsatellite instability alternations in Egyptian brain tumor patients, which may have an important role in improving the outcome, survival and may help in evolving a characteristic individual therapy.

Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge

OBJECTIVES

Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO₂) and oxygen (O₂) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma.

MATERIALS AND METHODS

Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO₂ and O₂ standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns.

RESULTS

Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs.

CONCLUSIONS

Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO₂ and O₂ modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.

PET/MR in recurrent glioblastoma patients treated with regorafenib: [18F]FET and DWI-ADC for response assessment and survival prediction

Objective:

The use of regorafenib in recurrent glioblastoma patients has been recently approved by the Italian Medicines Agency (AIFA) and added to the National Comprehensive Cancer Network (NCCN) 2020 guidelines as a preferred regimen. Given its complex effects at the molecular level, the most appropriate imaging tools to assess early response to treatment is still a matter of debate. Diffusion-weighted imaging and O-(2-¹⁸F-fluoroethyl)-L-tyrosine positron emission tomography ([¹⁸F]FET PET) are promising methodologies providing additional information to the currently used RANO criteria. The aim of this study was to evaluate the variations in diffusion-weighted imaging/apparent diffusion coefficient (ADC) and [¹⁸F]FET PET-derived parameters in patients who underwent PET/MR at both baseline and after starting regorafenib.

Methods:

We retrospectively reviewed 16 consecutive GBM patients who underwent [¹⁸F]FET PET/MR before and after two cycles of regorafenib. Patients were sorted into stable (SD) or progressive disease (PD) categories in accordance with RANO criteria. We were also able to analyze four SD patients who underwent a third PET/MR after another four cycles of regorafenib. [¹⁸F]FET uptake greater than 1.6 times the mean background activity was used to define an area to be superimposed on an ADC map at baseline and after treatment. Several metrics were then derived and compared. Log-rank test was applied for overall survival analysis.

Results:

Percentage difference in FET volumes correlates with the corresponding percentage difference in ADC (R = 0.54). Patients with a twofold increase in FET after regorafenib showed a significantly higher increase in ADC pathological volume than the remaining subjects (p = 0.0023). Kaplan–Meier analysis, performed to compare the performance in overall survival prediction, revealed that the percentage variations of FET- and ADC-derived metrics performed at least as well as RANO criteria (p = 0.02, p = 0.024 and p = 0.04 respectively) and in some cases even better. TBR Max and TBR mean are not able to accurately predict overall survival.

Conclusion

In recurrent glioblastoma patients treated with regorafenib, [¹⁸F]FET and ADC metrics, are able to predict overall survival and being obtained from completely different measures as compared to RANO, could serve as semi-quantitative independent biomarkers of response to treatment.

Advances in knowledge

Simultaneous evaluation of [¹⁸F]FET and ADC metrics using PET/MR allows an early and reliable identification of response to treatment and predict overall survival.

Oncolytic Viro-Immunotherapy: An Emerging Option in the Treatment of Gliomas

The prognosis of malignant gliomas remains poor, with median survival fewer than 20 months and a 5-year survival rate merely 5%. Their primary location in the central nervous system (CNS) and its immunosuppressive environment with little T cell infiltration has rendered cancer therapies mostly ineffective, and breakthrough therapies such as immune checkpoint inhibitors (ICIs) have shown limited benefit. However, tumor immunotherapy is developing rapidly and can help overcome these obstacles. But for now, malignant gliomas remain fatal with short survival and limited therapeutic options. Oncolytic virotherapy (OVT) is a unique antitumor immunotherapy wherein viruses selectively or preferentially kill tumor cells, replicate and spread through tumors while inducing antitumor immune responses. OVTs can also recondition the tumor microenvironment and improve the efficacy of other immunotherapies by escalating the infiltration of immune cells into tumors. Some OVTs can penetrate the blood-brain barrier (BBB) and possess tropism for the CNS, enabling intravenous delivery. Despite the therapeutic potential displayed by oncolytic viruses (OVs), optimizing OVT has proved challenging in clinical development, and marketing approvals for OVTs have been rare. In June 2021 however, as a genetically engineered OV based on herpes simplex virus-1 (G47Δ), teserpaturev got conditional and time-limited approval for the treatment of malignant gliomas in Japan. In this review, we summarize the current state of OVT, the synergistic effect of OVT in combination with other immunotherapies as well as the hurdles to successful clinical use. We also provide some suggestions to overcome the challenges in treating of gliomas.

Diagnostic and Prognostic Potential of 18F-FET PET in the Differential Diagnosis of Glioma Recurrence and Treatment-Induced Changes After Chemoradiation Therapy

Background

MRI-based differential diagnosis of glioma recurrence (GR) and treatment-induced changes (TICs) remain elusive in up to 30% of treated glioma patients. We aimed to determine ¹⁸F-FET PET diagnostic performance in this clinical scenario, its outcome dependency on established prognostic factors, optimal ¹⁸F-FET semi-quantitative thresholds, and whether ¹⁸F-FET parameters may instantly predict progression-free survival (PFS) and overall survival (OS).

Methods

We retrospectively analyzed 45 glioma patients treated with chemoradiation therapy (32 males; mean age: 51 years, glioma grade: n=26 WHO4; n=15 WHO3; n=4 WHO2) who underwent ¹⁸F-FET PET to resolve differential diagnosis of GR and TICs raised by MRI performed in the preceding 2 weeks and depicting any of the following changes in their radiation field: volumetric increase of contrast-enhancing lesions; new contrast-enhancing lesion; significant increase in T2/FLAIR non-enhancing lesion without reducing corticosteroids. ¹⁸F-FET PET outcome relied on evaluation of maximum tumor-to-brain ratio (TBRmax), time-to-peak (TTP), and time-activity curve pattern (TAC). Metabolic tumor volume (MTV) and total tumor metabolism (TTM) were calculated for prognostic purposes. Standard of reference was repeat MRI performed 4–6 weeks after the previous MRI. Non-parametric statistics tested ¹⁸F-FET-based parameters for dependency on established prognostic markers. ROC curve analysis determined optimal cutoff values for ¹⁸F-FET semi-quantitative parameters. ¹⁸F-FET parameters and prognostic factors were evaluated for PFS and OS by Kaplan-Meier, univariate, and multivariate analyses.

Results

¹⁸F-FET PET sensitivity, specificity, positive predictive value, negative predictive value were 86.2, 81.3, 89.3, 76.5%, respectively; higher diagnostic accuracy was yielded in IDH-wild-type glioma patients compared to IDH-mutant glioma patients (sensitivity: 81.8 versus 88.9%; specificity: 80.8 versus 81.8%). KPS was the only prognostic factor differing according to ¹⁸F-FET PET outcome (negative versus positive). Optimal ¹⁸F-FET cutoff values for GR were TBRmax ≥ 2.1, SUVmax ≥ 3.5, and TTP ≤ 29 min. PFS differed based on ¹⁸F-FET outcome and related metrics and according to KPS; a different OS was observed according to KPS only. On multivariate analysis, ¹⁸F-FET PET outcome was the only significant PFS factor; KPS and age the only significant OS factors.

Conclusion

¹⁸F-FET PET demonstrated good diagnostic performance. ¹⁸F-FET PET outcome and metrics were significantly predictive only for PFS.

11C-methyl-L-methionine PET measuring parameters for the diagnosis of tumour progression against radiation-induced changes in brain metastases

Objectives:

Radiation-induced changes (RIC) secondary to focal radiotherapy can imitate tumour progression in brain metastases and make follow-up clinical decision making unreliable. ¹¹C-methyl-L-methionine-PET (MET-PET) is widely used for the diagnosis of RIC in brain metastases, but minimal literature exists regarding the optimum PET measuring parameter to be used. We analysed the diagnostic performance of different MET-PET measuring parameters in distinguishing between RIC and tumour progression in a retrospective cohort of brain metastasis patients.

Methods:

26 patients with 31 metastatic lesions were included on the basis of having undergone a PET scan due to radiological uncertainty of disease progression. The PET images were analysed and methionine uptake quantified using standardised-uptake-values (SUV) and tumour-to-normal tissue (T/N) ratios, generated as SUV_mean, SUV_max, SUV_peak, T/N_mean, T/N_max-mean and T/N_peak-mean. Metabolic-tumour-volume and total-lesion methionine metabolism were also computed. A definitive diagnosis of either RIC or tumour progression was established by clinicoradiological follow-up of least 4 months subsequent to the investigative PET scan.

Results:

All MET-PET parameters except metabolic-tumour-volume showed statistically significant differences between tumour progression and lesions with RIC. Receiver-operating-characteristic curve and area-under the-curve analysis demonstrated the highest value of 0.834 for SUV_max with a corresponding optimum threshold of 3.29. This associated with sensitivity, specificity, positive predictive and negative predictive values of 78.57, 70.59%, 74.32 and 75.25% respectively.

Conclusions

MET-PET is a useful modality for the diagnosis of RIC in brain metastases. SUV_max was the PET parameter with the greatest diagnostic performance.

Advances in knowledge:

More robust comparisons between SUV_max and SUV_peak could enhance follow-up treatment planning.

Multimodal imaging in the differential diagnosis of glioma recurrence from treatment-related effects: A protocol for systematic review and network meta-analysis

BACKGROUND

Glioma is the most common malignant primary brain tumor and it will always recur. To date, various multimodal imaging including magnetic resonance imaging (MRI) and positron emission tomography computed tomography (PET/CT) was used to differentiate the diagnosis of true tumor recurrent (TuR) and treatment-related effects (TrE) in glioma patient but with no overall conclusion. In this study, SROC curve and Bayesian network meta-analysis will be used to conduct a comprehensive analysis of the results of different clinical reports, and assess the efficacy of multimodal imaging in difference TuR and TrE.

METHODS

To find more comprehensive information about the application of multimodal imaging in glioma patients, we searched the EMBASE, Pubmed, and Cochrane Central Register of Controlled Trials for relevant clinical trials. We also reviewed their reference lists to avoid omissions. QUADAS-2, RevMan software, Stata, and R software will be used.

RESULTS

This study will provide reliable evidence for the efficacy of multimodal imaging in the differential diagnosis of TuR and TrE in glioma patients.

CONCLUSION

We will evaluate the effectiveness of different and rank each imaging method in glioma patients to provide a decision-making reference on which method to choose for clinicians. Protocol registration number: CRD42020217861.

Glioblastoma: Emerging Treatments and Novel Trial Designs

Simple Summary

Nowadays, very few systemic agents have shown clinical activity in patients with glioblastoma, making the research of novel therapeutic approaches a critical issue. Fortunately, the availability of novel compounds is increasing thanks to better biological knowledge of the disease. In this review we want to investigate more promising ongoing clinical trials in both primary and recurrent GBM. Furthermore, a great interest of the present work is focused on novel trial design strategies.

Abstract

Management of glioblastoma is a clinical challenge since very few systemic treatments have shown clinical efficacy in recurrent disease. Thanks to an increased knowledge of the biological and molecular mechanisms related to disease progression and growth, promising novel treatment strategies are emerging. The expanding availability of innovative compounds requires the design of a new generation of clinical trials, testing experimental compounds in a short time and tailoring the sample cohort based on molecular and clinical behaviors. In this review, we focused our attention on the assessment of promising novel treatment approaches, discussing novel trial design and possible future fields of development in this setting.

Protein corona profile of graphene oxide allows detection of glioblastoma multiforme using a simple one-dimensional gel electrophoresis technique: a proof-of-concept study

Glioblastoma multiforme (GBM) is the most aggressive form of gliomas. The development of supplementary approaches for glioblastoma diagnosis, limited to imaging techniques and tissue biopsies so far, is a necessity of clinical relevance. In this context, nanotechnology might afford tools to enable early diagnosis. Upon exposure to biological media, nanoparticles are coated with a layer of proteins, the protein corona (PC), whose composition is individual and personalized. Here we show that the PC of graphene oxide nanosheets has a capacity to detect GBM using a simple one-dimensional gel electrophoresis technique. In a range of molecular weights between 100 and 120 kDa, the personalized PC from GBM patients is completely discernible from that of healthy donors and that of cancer patients affected by pancreatic adenocarcinoma and colorectal cancer. Using tandem mass spectrometry, we found that inter-alpha-trypsin inhibitor (ITI) heavy chain H4 is enriched in the PC of all tested individuals but not in the GBM patients. Overall, if confirmed on a larger cohort series, this approach could be advantageous at the first level of investigation to decide whether to carry out more invasive analyses and/or to follow up patients after surgery and/or pharmacological treatment.

Laser interstitial thermal therapy for treatment of cerebral radiation necrosis

Radiation necrosis is a well described complication after radiosurgical treatment of intracranial pathologies - best recognized after the treatment of patients with arteriovenous malformations and brain metastases but possibly also affecting patients treated with radiosurgery for meningioma. The pathophysiology of radiation necrosis is still not well understood but is most likely a secondary local tissue inflammatory response to brain tissue injured by radiation. Radiation necrosis in brain metastases patients may present radiographically and behave clinically like recurrent tumor. Differentiation between radiation necrosis and recurrent tumor has been difficult based on radiographic changes alone. Biopsy or craniotomy therefore remains the gold standard method of diagnosis. For symptomatic patients, corticosteroids are first-line therapy, but patients may fail medical management due to intolerance of chronic steroids or persistence of symptoms. In these cases, open surgical resection has been shown to be successful in management of surgically amenable lesions but may be suboptimal in patients with deep-seated lesions or extensive prior cranial surgical history, both carrying high risk for peri-operative morbidity. Laser interstitial thermal therapy has emerged as a viable, alternative surgical option. In addition to allowing access to tissue for diagnosis, thermal treatment of the lesion can also be delivered precisely and accurately under real-time imaging guidance. This review highlights the pertinent studies that have shaped the impetus for use of laser interstitial thermal therapy in the treatment of radiation necrosis, reviewing indications, outcomes, and nuances toward successful application of this technology in patients with suspected radiation necrosis.

Qualitative Assessment of Advanced MRI in Post-Treatment High Grade Gliomas Follow Up: Do We Agree?

PURPOSE

MRI is commonly used in follow up of high grade glioma. Our purpose is to assess the interrater agreement on the increasingly used visual qualitative assessment of various conventional and advanced MR techniques in the setting of treated high grade glioma in comparison to the well established quantitative measurements.

METHODS

We prospectively enrolled HGG patients who underwent reresection of a new enhancing lesion on post-treatment 3T MR examination including DWI, DCE and DSC sequences. Two neuroradiologists objectively assessed the diffusion and perfusion maps by placing ROI on representative post-processed maps. They subjectively assessed the post-contrast, perfusion and diffusion sequences. Interrater agreement and concordance correlation coefficient were calculated.

RESULTS

Twenty-eight lesions were included. The interrater agreement on the qualitative assessment was good for k-trans (k = 0.73), moderate for Vp (k = 0.52), fair for AUC and Ve maps (k = 0.37 and 0.21), fair for corrected CBV (k = 0.39) and poor for the enhancement pattern and presence of diffusion restriction (k = 0.02 and 0.07). The concordance between the quantitative measurements was substantial for AUC and Vp (ρc = 0.98 and 0.97), moderate for k-trans and corrected CBV (ρc = 0.94) and poor for Ve and ADC (ρc = 0.86 and 0.24).

CONCLUSION

While the quantitative measurements of DSC and DCE perfusion maps show satisfactory inter-rater agreement, the qualitative assessment has lower interobserver agreement and should not be relied upon solely in the interpretation. Similarly, the suboptimal inter-rater agreement on the interpretation of enhancement pattern and diffusion restriction potentially limits their usefulness in differentiating glioma recurrence from treatment related changes.

Multimodal assessment of disease activity in glioblastoma : A single center experience

BACKGROUND

Assessment of disease activity in glioblastoma (GBM) can be challenging due to several clinical and radiological pitfalls. Besides MRI, FET-PET and neurocognitive assessment (NA) are used in several neuro-oncological centers in order to improve the specificity of response assessment. We performed a retrospective study to investigate whether the assessment by RANO (Response Assessment in NeuroOncology) corresponds to FET-PET imaging and NA results. Moreover, the concordance of RANO with a final recommendation of an interdisciplinary neuro-oncological tumor board recommendation (TBR) was analyzed.

METHODS

We enrolled 25 consecutive patients with newly diagnosed histologically confirmed GBM in a pilot study, accounting for 81 multimodal test results. All patients were selected after undergoing consecutive follow-up comprising MRI, FET-PET, and NA with a subsequent TBR. Results were analyzed for correlations between RANO, FET-PET and NA. An additional consistency analysis was performed to elucidate the impact of RANO on decision making.

RESULTS

A highly statistically significant correlation was found between RANO and FET-PET and NA results (all P < 0.01); however, 26% of follow-up tests exhibited inconsistent results in multimodal assessment, among which RANO was only 48% in accordance with the final TBR. The concordance of NA and FET-PET with the final TBR was 67% and 86%, respectively.

CONCLUSION

The RANO proved its value in the context of multimodal assessment of disease activity in GBM; however, because the implementation of multimodal assessment showed a considerably high percentage of inconsistent results, further studies are required to investigate the relationship between different assessment techniques, in addition to their overall significance to response rating.

Distinct Cerebrovascular Reactivity Patterns for Brain Radiation Necrosis

Background: Current imaging-based discrimination between radiation necrosis versus recurrent glioblastoma contrast-enhancing lesions remains imprecise but is paramount for prognostic and therapeutic evaluation. We examined whether patients with radiation necrosis exhibit distinct patterns of blood oxygenation-level dependent fMRI cerebrovascular reactivity (BOLD-CVR) as the first step to better distinguishing patients with radiation necrosis from recurrent glioblastoma compared with patients with newly diagnosed glioblastoma before surgery and radiotherapy. Methods: Eight consecutive patients with primary and secondary brain tumors and a multidisciplinary clinical and radiological diagnosis of radiation necrosis, and fourteen patients with a first diagnosis of glioblastoma underwent BOLD-CVR mapping. For all these patients, the contrast-enhancing lesion was derived from high-resolution T1-weighted MRI and rendered the volume-of-interest (VOI). From this primary VOI, additional 3 mm concentric expanding VOIs up to 30 mm were created for a detailed perilesional BOLD-CVR tissue analysis between the two groups. Receiver operating characteristic curves assessed the discriminative properties of BOLD-CVR for both groups. Results: Mean intralesional BOLD-CVR values were markedly lower in radiation necrosis than in glioblastoma contrast-enhancing lesions (0.001 ± 0.06 vs. 0.057 ± 0.05; p = 0.04). Perilesionally, a characteristic BOLD-CVR pattern was observed for radiation necrosis and glioblastoma patients, with an improvement of BOLD-CVR values in the radiation necrosis group and persisting lower perilesional BOLD-CVR values in glioblastoma patients. The ROC analysis discriminated against both groups when these two parameters were analyzed together (area under the curve: 0.85, 95% CI: 0.65-1.00). Conclusions: In this preliminary analysis, distinctive intralesional and perilesional BOLD-cerebrovascular reactivity patterns are found for radiation necrosis.

Dynamic Susceptibility Perfusion Imaging for Differentiating Progressive Disease from Pseudoprogression in Diffuse Glioma Molecular Subtypes

Rationale and Objectives: Advanced adjuvant therapy of diffuse gliomas can result in equivocal findings in follow-up imaging. We aimed to assess the additional value of dynamic susceptibility perfusion imaging in the differentiation of progressive disease (PD) from pseudoprogression (PsP) in different molecular glioma subtypes. Materials and Methods: 89 patients with treated diffuse glioma with different molecular subtypes (IDH wild type (Astro-IDH^wt), IDH mutant astrocytomas (Astro-IDH^mut) and oligodendrogliomas), and tumor-suspect lesions on post-treatment follow-up imaging were classified into two outcome groups (PD or PsP) retrospectively by histopathology or clinical follow-up. The relative cerebral blood volume (rCBV) was assessed in the tumor-suspect FLAIR and contrast-enhancing (CE) lesions. We analyzed how a multilevel classification using a molecular subtype, the presence of a CE lesion, and two rCBV histogram parameters performed for PD prediction compared with a decision tree model (DTM) using additional rCBV parameters. Results: The PD rate was 69% in the whole cohort, 86% in Astro-IDH^wt, 52% in Astro-IDH^mut, and 55% in oligodendrogliomas. In the presence of a CE lesion, the PD rate was higher with 82%, 94%, 59%, and 88%, respectively; if there was no CE lesion, however, the PD rate was only 44%, 60%, 40%, and 33%, respectively. The additional use of the rCBV parameters in the DTM yielded a prediction accuracy for PD of 99%, 100%, 93%, and 95%, respectively. Conclusion: Utilizing combined information about the molecular tumor type, the presence or absence of CE lesions and rCBV parameters increases PD prediction accuracy in diffuse glioma.

Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T1-weighted Contrast-enhanced Imaging

Background

Based on conventional MRI images, it is difficult to differentiatepseudoprogression from true progressionin GBM patients after standard treatment, which isa critical issue associated with survival. The aim of this study was to evaluate the diagnostic performance of machine learning using radiomics modelfrom T₁-weighted contrast enhanced imaging(T₁CE) in differentiating pseudoprogression from true progression after standard treatment for GBM.

Methods

Seventy-sevenGBM patients, including 51 with true progression and 26 with pseudoprogression,who underwent standard treatment and T₁CE, were retrospectively enrolled.Clinical information, including sex, age, KPS score, resection extent, neurological deficit and mean radiation dose, were also recorded collected for each patient. The whole tumor enhancementwas manually drawn on the T₁CE image, and a total of texture 9675 features were extracted and fed to a two-step feature selection scheme. A random forest (RF) classifier was trained to separate the patients by their outcomes.The diagnostic efficacies of the radiomics modeland radiologist assessment were further compared by using theaccuracy (ACC), sensitivity and specificity.

Results

No clinical features showed statistically significant differences between true progression and pseudoprogression.The radiomic classifier demonstrated ACC, sensitivity, and specificity of 72.78%(95% confidence interval [CI]: 0.45,0.91), 78.36%(95%CI: 0.56,1.00) and 61.33%(95%CI: 0.20,0.82).The accuracy, sensitivity and specificity of three radiologists’ assessment were66.23%(95% CI: 0.55,0.76), 61.50%(95% CI: 0.43,0.78) and 68.62%(95% CI: 0.55,0.80); 55.84%(95% CI: 0.45,0.66),69.25%(95% CI: 0.50,0.84) and 49.13%(95% CI: 0.36,0.62); 55.84%(95% CI: 0.45,0.66), 69.23%(95% CI: 0.50,0.84) and 47.06%(95% CI: 0.34,0.61), respectively.

Conclusion

T₁CE–based radiomics showed better classification performance compared with radiologists’ assessment.The radiomics modelwas promising in differentiating pseudoprogression from true progression.

Non-invasive assessment of telomere maintenance mechanisms in brain tumors

Telomere maintenance is a universal hallmark of cancer. Most tumors including low-grade oligodendrogliomas use telomerase reverse transcriptase (TERT) expression for telomere maintenance while astrocytomas use the alternative lengthening of telomeres (ALT) pathway. Although TERT and ALT are hallmarks of tumor proliferation and attractive therapeutic targets, translational methods of imaging TERT and ALT are lacking. Here we show that TERT and ALT are associated with unique 1H-magnetic resonance spectroscopy (MRS)-detectable metabolic signatures in genetically-engineered and patient-derived glioma models and patient biopsies. Importantly, we have leveraged this information to mechanistically validate hyperpolarized [1-13C]-alanine flux to pyruvate as an imaging biomarker of ALT status and hyperpolarized [1-13C]-alanine flux to lactate as an imaging biomarker of TERT status in low-grade gliomas. Collectively, we have identified metabolic biomarkers of TERT and ALT status that provide a way of integrating critical oncogenic information into non-invasive imaging modalities that can improve tumor diagnosis and treatment response monitoring.

Current trends in the use of O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in neurooncology

The diagnostic potential of PET using the amino acid analogue O-(2-[18F]fluoroethyl)-L-tyrosine ([18F]FET) in brain tumor diagnostics has been proven in many studies during the last two decades and is still the subject of multiple studies every year. In addition to standard magnetic resonance imaging (MRI), positron emission tomography (PET) using [18F]FET provides important diagnostic data concerning brain tumor delineation, therapy planning, treatment monitoring, and improved differentiation between treatment-related changes and tumor recurrence. The pharmacokinetics, uptake mechanisms and metabolism have been well described in various preclinical studies. The accumulation of [18F]FET in most benign lesions and healthy brain tissue has been shown to be low, thus providing a high contrast between tumor tissue and benign tissue alterations. Based on logistic advantages of F-18 labelling and convincing clinical results, [18F]FET has widely replaced short lived amino acid tracers such as L-[11C]methyl-methionine ([11C]MET) in many centers across Western Europe. This review summarizes the basic knowledge on [18F]FET and its contribution to the care of patients with brain tumors. In particular, recent studies about specificity, possible pitfalls, and the utility of [18F]FET PET in tumor grading and prognostication regarding the revised WHO classification of brain tumors are addressed.

Genomic Profiling of Circulating Tumor DNA From Cerebrospinal Fluid to Guide Clinical Decision Making for Patients With Primary and Metastatic Brain Tumors

Despite advances in systemic therapies for solid tumors, the development of brain metastases remains a significant contributor to overall cancer mortality and requires improved methods for diagnosing and treating these lesions. Similarly, the prognosis for malignant primary brain tumors remains poor with little improvement in overall survival over the last several decades. In both primary and metastatic central nervous system (CNS) tumors, the challenge from a clinical perspective centers on detecting CNS dissemination early and understanding how CNS lesions differ from the primary tumor, in order to determine potential treatment strategies. Acquiring tissue from CNS tumors has historically been accomplished through invasive neurosurgical procedures, which restricts the number of patients to those who can safely undergo a surgical procedure, and for which such interventions will add meaningful value to the care of the patient. In this review we discuss the potential of analyzing cell free DNA shed from tumor cells that is contained within the cerebrospinal fluid (CSF) as a sensitive and minimally invasive method to detect and characterize primary and metastatic tumors in the CNS.

A simple score to estimate the likelihood of pseudoprogression vs. recurrence following stereotactic radiosurgery for brain metastases: The Bergen Criteria

Background

A major challenge in the follow-up of patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) is to distinguish pseudoprogression (PP) from tumor recurrence (TR). The aim of the study was to develop a clinical risk assessment score.

Methods

Follow-up images of 87 of 97 consecutive patients treated with SRS for 348 BM were analyzed. Of these, 100 (28.7%) BM in 48 (53.9%) patients responded with either TR (n = 53, 15%) or PP (n = 47, 14%). Differences between the 2 groups were analyzed and used to develop a risk assessment score (the Bergen Criteria).

Results

Factors associated with a higher incidence of PP vs. TR were as follows: prior radiation with whole brain radiotherapy or SRS (P = .001), target cover ratio ≥98% (P = .048), BM volume ≤2 cm³ (P = .054), and primary lung cancer vs. other cancer types (P = .084). Based on the presence (0) or absence (1) of these 5 characteristics, the Bergen Criteria was established. A total score <2 points was associated with 100% PP, 2 points with 57% PP and 43% TR, 3 points with 57% TR and 43% PP, whereas >3 points were associated with 84% TR and 16% PP, P < .001.

Conclusion

Based on 5 characteristics at the time of SRS the Bergen Criteria could robustly differentiate between PP vs. TR following SRS. The score is user-friendly and provides a useful tool to guide the decision making whether to retreat or observe at appropriate follow-up intervals.

Hemodynamic investigation of peritumoral impaired blood oxygenation-level dependent cerebrovascular reactivity in patients with diffuse glioma

INTRODUCTION

The presence of peritumorally impaired blood oxygenation-level dependent cerebrovascular reactivity (BOLD-CVR) has been unequivocally demonstrated in patients with diffuse glioma, and may have value to better identify tumor infiltration zone. Since BOLD-CVR does not measure hemodynamic changes directly, we performed additional MR perfusion studies to better characterize the peritumoral hemodynamic environment.

METHODS

Seventeen patients with WHO grade III and IV diffuse glioma underwent high resolution advanced hemodynamic MR imaging including BOLD-CVR and MR perfusion. The obtained multiparametric hemodynamic factors (i.e., regional cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), mean transit time (MTT), time-to-peak (TTP) and BOLD-CVR, were analyzed within 10 concentric expanding 3 mm volumes of interest (VOIs) up to 30 mm from the tumor tissue mask.

RESULTS

BOLD-CVR impairment was found within the tumor tissue mask and the peritumoral VOIs up to 21 mm as compared to the contralateral flipped CVR analysis (p<0.05). In the affected hemisphere, we observed positive spatial correlations including all VOIs between BOLD-CVR and rCBV values (r=0.27; p<0.001), rCBF (r=0.42; p<0.001) and a negative correlation between BOLD-CVR and TTP (r=-0.47; p<0.001).

CONCLUSIONS

Peritumorally impaired BOLD-CVR is associated with concomitant hemodynamic alterations with severity correlating to tumor volume. The distribution of these multiparametric hemodynamic MRI patterns may be considered for future studies characterizing the hemodynamic peritumoral environment, thereby better identifying the extent of tumor infiltration.

Presence of Histopathological Treatment Effects at Resection of Recurrent Glioblastoma: Incidence and Effect on Outcome

BACKGROUND

Resection may be appropriate for select patients with recurrent glioblastoma. The incidence of histopathological findings related to prior treatment and their prognostic implications are incompletely characterized.

OBJECTIVE

To quantify the incidence and survival outcomes associated with treatment effect at resection of recurrent glioblastoma (GBM).

METHODS

Patients who underwent resection for recurrent GBM were retrospectively reviewed, and pathology, treatment history, and survival data were collected. Treatment effect was defined as any component of treatment-related changes on pathology.

RESULTS

In total, 110 patients underwent 146 reoperations. Median age at first reoperation was 57.2 yr and overall survival from reoperation was 10.8 mo. Treatment effect of any kind was noted in 81 of 146 reoperations (55%). Increased treatment effect was observed closer to radiotherapy; by quartile of time from radiotherapy, the rates of treatment effect were 77.8%, 55.6%, 40.7%, and 44.4% (P = .028). Treatment effect was associated with earlier reoperation (8.9 vs 13.8 mo after radiotherapy, P = .003), and the presence of treatment effect did not impact survival from primary surgery (25.4 vs 24.3 mo, P = .084). Patients treated with bevacizumab prior to reoperation were less likely to have treatment effect (20% vs 65%, P < .001).

CONCLUSION

Histopathological treatment-related changes are evident in a majority of patients undergoing resection for recurrent glioblastoma. There was no association of treatment effect with overall survival from primary surgery.

Circulating biomarkers in patients with glioblastoma

Gliomas are the most common tumours of the central nervous system and the most aggressive form is glioblastoma (GBM). Despite advances in treatment, patient survival remains low. GBM diagnosis typically relies on imaging techniques and postoperative pathological diagnosis; however, both procedures have their inherent limitations. Imaging modalities cannot differentiate tumour progression from treatment-related changes that mimic progression, known as pseudoprogression, which might lead to misinterpretation of therapy response and delay clinical interventions. In addition to imaging limitations, tissue biopsies are invasive and most of the time cannot be performed over the course of treatment to evaluate 'real-time' tumour dynamics. In an attempt to address these limitations, liquid biopsies have been proposed in the field. Blood sampling is a minimally invasive procedure for a patient to endure and could provide tumoural information to guide therapy. Tumours shed tumoural content, such as circulating tumour cells, cell-free nucleic acids, proteins and extracellular vesicles, into the circulation, and these biomarkers are reported to cross the blood-brain barrier. The use of liquid biopsies is emerging in the field of GBM. In this review, we aim to summarise the current literature on circulating biomarkers, namely circulating tumour cells, circulating tumour DNA and extracellular vesicles as potential non-invasively sampled biomarkers to manage the treatment of patients with GBM.

Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas

BACKGROUND

The Brain Tumor Reporting and Data System (BT-RADS) category 3 is suitable for identifying cases with intermediate probability of tumor recurrence that do not meet the Response Assessment in Neuro-Oncology (RANO) criteria for progression. The aim of this study was to evaluate the added value of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC PWI) and diffusion-weighted imaging (DWI) to BT-RADS for differentiating tumor recurrence from non-recurrence in postoperative high-grade glioma (HGG) patients with category 3 lesions.

METHODS

Patients with BT-RADS category 3 lesions were included. The maximal relative cerebral blood volume (rCBV_max) and the mean apparent diffusion coefficient (ADC_mean) values were measured. The added value of DSC PWI and DWI to BT-RADS was evaluated by receiver operating characteristic (ROC) curve analysis.

RESULTS

Fifty-one of 91 patients had tumor recurrence, and 40 patients did not. There were significant differences in rCBV_max and ADC_mean between the tumor recurrence group and non-recurrence group. Compared to BT-RADS alone, the addition of DSC PWI to BT-RADS increased the area under curve (AUC) from 0.76 (95% confidence interval [CI] 0.66-0.84) to 0.90 (95% CI 0.81-0.95) for differentiating tumor recurrence from non-recurrence. The addition of DWI to BT-RADS increased the AUC from 0.76 (95% CI 0.66-0.84) to 0.88 (95% CI 0.80-0.94). The combination of BT-RADS, DSC PWI, and DWI exhibited the best diagnostic performance (AUC = 0.95; 95% CI 0.88-0.98) for differentiating tumor recurrence from non-recurrence.

CONCLUSION

Adding DSC PWI and DWI to BT-RADS can significantly improve the diagnostic performance for differentiating tumor recurrence from non-recurrence in BT-RADS category 3 lesions.

Contribution of Different Positron Emission Tomography Tracers in Glioma Management: Focus on Glioblastoma

Although rare, glioblastomas account for the majority of primary brain lesions, with a dreadful prognosis. Magnetic resonance imaging (MRI) is currently the imaging method providing the higher resolution. However, it does not always succeed in distinguishing recurrences from non-specific temozolomide, have been shown to improve -related changes caused by the combination of radiotherapy, chemotherapy, and targeted therapy, also called pseudoprogression. Strenuous attempts to overcome this issue is highly required for these patients with a short life expectancy for both ethical and economic reasons. Additional reliable information may be obtained from positron emission tomography (PET) imaging. The development of this technique, along with the emerging of new classes of tracers, can help in the diagnosis, prognosis, and assessment of therapies. We reviewed the current data about the commonly used tracers, such as 18F-fluorodeoxyglucose (18F-FDG) and radiolabeled amino acids, as well as different PET tracers recently investigated, to report their strengths, limitations, and relevance in glioblastoma management.

18F-FET PET Imaging in Differentiating Glioma Progression from Treatment-Related Changes: A Single-Center Experience

In glioma patients, differentiation between tumor progression (TP) and treatment-related changes (TRCs) remains challenging. Difficulties in classifying imaging alterations may result in a delay or an unnecessary discontinuation of treatment. PET using O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) has been shown to be a useful tool for detecting TP and TRCs. Methods: We retrospectively evaluated 127 consecutive patients with World Health Organization grade II-IV glioma who underwent ¹⁸F-FET PET imaging to distinguish between TP and TRCs. ¹⁸F-FET PET findings were verified by neuropathology (40 patients) or clinicoradiologic follow-up (87 patients). Maximum tumor-to-brain ratios (TBR_max) of ¹⁸F-FET uptake and the slope of the time-activity curves (20-50 min after injection) were determined. The diagnostic accuracy of ¹⁸F-FET PET parameters was evaluated by receiver-operating-characteristic analysis and χ² testing. The prognostic value of ¹⁸F-FET PET was estimated using the Kaplan-Meier method. Results: TP was diagnosed in 94 patients (74%) and TRCs in 33 (26%). For differentiating TP from TRCs, receiver-operating-characteristic analysis yielded an optimal ¹⁸F-FET TBR_max cutoff of 1.95 (sensitivity, 70%; specificity, 71%; accuracy, 70%; area under the curve, 0.75 ± 0.05). The highest accuracy was achieved by a combination of TBR_max and slope (sensitivity, 86%; specificity, 67%; accuracy, 81%). However, accuracy was poorer when tumors harbored isocitrate dehydrogenase (IDH) mutations (91% in IDH-wild-type tumors, 67% in IDH-mutant tumors, P < 0.001). ¹⁸F-FET PET results correlated with overall survival (P < 0.001). Conclusion: In our neurooncology department, the diagnostic performance of ¹⁸F-FET PET was convincing but slightly inferior to that of previous reports.

Current and Future Imaging Methods for Evaluating Response to Immunotherapy in Neuro-Oncology

Imaging plays a central role in evaluating responses to therapy in neuro-oncology patients. The advancing clinical use of immunotherapies has demonstrated that treatment-related inflammatory responses mimic tumor growth via conventional imaging, thus spurring the development of new imaging approaches to adequately distinguish between pseudoprogression and progressive disease. To this end, an increasing number of advanced imaging techniques are being evaluated in preclinical and clinical studies. These novel molecular imaging approaches will serve to complement conventional response assessments during immunotherapy. The goal of these techniques is to provide definitive metrics of tumor response at earlier time points to inform treatment decisions, which has the potential to improve patient outcomes. This review summarizes the available immunotherapy regimens, clinical response criteria, current state-of-the-art imaging approaches, and groundbreaking strategies for future implementation to evaluate the anti-tumor and immune responses to immunotherapy in neuro-oncology applications.

Preclinical Evaluation of Radiolabeled Peptides for PET Imaging of Glioblastoma Multiforme

In this study, we have compared four ⁶⁸Ga-labeled peptides (three Arg-Gly-Asp (RGD) peptides and substance-P) with two ¹⁸F-tracers clinically approved for tumor imaging. We have studied in vitro and in vivo characteristics of selected radiolabeled tracers in a glioblastoma multiforme tumor model. The in vitro part of the study was mainly focused on the evaluation of radiotracers stability under various conditions. We have also determined in vivo stability of studied ⁶⁸Ga-radiotracers by analysis of murine urine collected at various time points after injection. The in vivo behavior of tested ⁶⁸Ga-peptides was evaluated through ex vivo biodistribution studies and PET/CT imaging. The obtained data were compared with clinically used ¹⁸F-tracers. ⁶⁸Ga-RGD peptides showed better imaging properties compared to ¹⁸F-tracers, i.e., higher tumor/background ratios and no accumulation in non-target organs except for excretory organs.

Biomarkers and smart intracranial devices for the diagnosis, treatment, and monitoring of high-grade gliomas: a review of the literature and future prospects

Glioblastoma (GBM) is the most common primary brain neoplasm with median overall survival (OS) around 15 months. There is a dearth of effective monitoring strategies for patients with high-grade gliomas. Relying on magnetic resonance images of brain has its challenges, and repeated brain biopsies add significant morbidity. Hence, it is imperative to establish a less invasive way to diagnose, monitor, and guide management of patients with high-grade gliomas. Currently, multiple biomarkers are in various phases of development and include tissue, serum, cerebrospinal fluid (CSF), and imaging biomarkers. Here we review and summarize the potential biomarkers found in blood and CSF, including extracellular macromolecules, extracellular vesicles, circulating tumor cells, immune cells, endothelial cells, and endothelial progenitor cells. The ability to detect tumor-specific biomarkers in blood and CSF will potentially not only reduce the need for repeated brain biopsies but also provide valuable information about the heterogeneity of tumor, response to current treatment, and identify disease resistance. This review also details the status and potential scope of brain tumor-related cranial devices and implants including Ommaya reservoir, microelectromechanical systems-based depot device, Alzet mini-osmotic pump, Metronomic Biofeedback Pump (MBP), ipsum G1 implant, ultra-thin needle implant, and putative devices. An ideal smart cranial implant will overcome the blood-brain barrier, deliver various drugs, provide access to brain tissue, and potentially measure and monitor levels of various biomarkers.

What Neuroradiologists Need to Know About Radiation Treatment for Neural Tumors

Radiation oncologists and radiologists have a unique and mutually dependent relationship. Radiation oncologists rely on diagnostic imaging to locate the tumor and define the treatment target volume, evaluation of response to therapy, and follow-up. Accurate interpretation of post-treatment imaging requires diagnostic radiologists to have a basic understanding of radiation treatment planning and delivery. There are various radiation treatment modalities such as 3D conformal radiation therapy, intensity modulated radiation therapy and stereotactic radiosurgery as well as different radiation modalities such as photons and protons that can be used for treatment. All of these have subtle differences in how the treatment is planned and how the imaging findings might be affected. This paper provides an overview of the basic principles of radiation oncology, different radiation treatment modalities, how radiation therapy is planned and delivered, how knowledge of this process can help interpretation of images, and how the radiologist can contribute to this process.