Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis

Radiomic features on multiparametric MRI for differentiating pseudoprogression from recurrence in high-grade gliomas

BACKGROUND

Distinguishing between tumor recurrence and pseudoprogression (PsP) in high-grade glioma postoperatively is challenging. This study aims to enhance this differentiation using a combination of intratumoral and peritumoral radiomics.

PURPOSE

To assess the effectiveness of intratumoral and peritumoral radiomics in improving the differentiation between high-grade glioma recurrence and pseudoprogression after surgery.

MATERIAL AND METHODS

A total of 109 cases were randomly divided into training and validation sets, with 1316 features extracted from intratumoral and peritumoral volumes of interest (VOIs) on conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps. Feature selection was performed using the mRMR algorithm, resulting in intratumoral (100 features), peritumoral (100 features), and combined (200 features) subsets. Optimal features were then selected using PCC and RFE algorithms and modeled using LR, SVM, and LDA classifiers. Diagnostic performance was compared using area under the receiver operating characteristic curve (AUC), evaluated in the validation set. A nomogram was established using radscores from intratumoral, peritumoral, and combined models.

RESULTS

The combined model, utilizing 14 optimal features (8 peritumoral, 6 intratumoral) and LR as the best classifier, outperformed the single intratumoral and peritumoral models. In the training set, the AUC values for the combined model, intratumoral model, and peritumoral model were 0.938, 0.921, and 0.847, respectively; in the validation set, the AUC values were 0.841, 0.755, and 0.705. The nomogram model demonstrated AUCs of 0.960 (training set) and 0.850 (validation set).

CONCLUSION

The combination of intratumoral and peritumoral radiomics is effective in distinguishing high-grade glioma recurrence from pseudoprogression after surgery.

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

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.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

OBJECTIVE

To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection.

MATERIALS AND METHODS

Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression).

RESULTS

In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%.

CONCLUSIONS

Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection.

CLINICAL RELEVANCE STATEMENT

Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture.

KEY POINTS

• Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Clinical Theranostics in Recurrent Gliomas: A Review

Gliomas represent the most commonly occurring tumors in the central nervous system and account for approximately 80% of all malignant primary brain tumors. With a high malignancy and recurrence risk, the prognosis of high-grade gliomas is poor, with a mean survival time of 12-18 months. While contrast-enhanced MRI serves as the standard diagnostic imaging modality for gliomas, it faces limitations in the evaluation of recurrent gliomas, failing to distinguish between treatment-related changes and tumor progression, and offers no direct therapeutic options. Recent advances in imaging modalities have attempted to address some of these limitations, including positron emission tomography (PET), which has demonstrated success in delineating tumor margins and guiding the treatment of recurrent gliomas. Additionally, with the advent of theranostics in nuclear medicine, PET tracers, when combined with therapeutic agents, have also evolved beyond a purely diagnostic modality, serving both diagnostic and therapeutic roles. This review will discuss the growing involvement of theranostics in diagnosing and treating recurrent gliomas and address the associated impact on quality of life and functional recovery.

Cerebrospinal Fluid Liquid Biopsies in the Evaluation of Adult Gliomas

PURPOSE OF REVIEW

This review aims to discuss recent research regarding the biomolecules explored in liquid biopsies and their potential clinical uses for adult-type diffuse gliomas.

RECENT FINDINGS

Evaluation of tumor biomolecules via cerebrospinal fluid (CSF) is an emerging technology in neuro-oncology. Studies to date have already identified various circulating tumor DNA, extracellular vesicle, micro-messenger RNA and protein biomarkers of interest. These biomarkers show potential to assist in multiple avenues of central nervous system (CNS) tumor evaluation, including tumor differentiation and diagnosis, treatment selection, response assessment, detection of tumor progression, and prognosis. In addition, CSF liquid biopsies have the potential to better characterize tumor heterogeneity compared to conventional tissue collection and CNS imaging. Current imaging modalities are not sufficient to establish a definitive glioma diagnosis and repeated tissue sampling via conventional biopsy is risky, therefore, there is a great need to improve non-invasive and minimally invasive sampling methods. CSF liquid biopsies represent a promising, minimally invasive adjunct to current approaches which can provide diagnostic and prognostic information as well as aid in response assessment.

Artificial intelligence-based MRI radiomics and radiogenomics in glioma

The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of gliomas pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). Radiomics and radiogenomics present a potential to precisely diagnose and predict survival and treatment responses, via morphological, textural, and functional features derived from MRI data, as well as genomic data. In spite of their advantages, it is still lacking standardized processes of feature extraction and analysis methodology among different research groups, which have made external validations infeasible. Radiomics and radiogenomics can be used to better understand the genomic basis of gliomas, such as tumor spatial heterogeneity, treatment response, molecular classifications and tumor microenvironment immune infiltration. These novel techniques have also been used to predict histological features, grade or even overall survival in gliomas. In this review, workflows of radiomics and radiogenomics are elucidated, with recent research on machine learning or artificial intelligence in glioma.

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.

Post-treatment imaging of gliomas: challenging the existing dogmas

Gliomas are the commonest malignant central nervous system tumours in adults and imaging is the cornerstone of diagnosis, treatment, and post-treatment follow-up of these patients. With the ever-evolving treatment strategies post-treatment imaging and interpretation in glioma remains challenging, more so with the advent of anti-angiogenic drugs and immunotherapy, which can significantly alter the appearance in this setting, thus making interpretation of routine imaging findings such as contrast enhancement, oedema, and mass effect difficult to interpret. This review details the various methods of management of glioma including the upcoming novel therapies and their impact on imaging findings, with a comprehensive description of the imaging findings in conventional and advanced imaging techniques. A systematic appraisal for the existing and emerging techniques of imaging in these settings and their clinical application including various response assessment guidelines and artificial intelligence based response assessment will also be discussed.

Response Assessment in Brain Metastases Managed by Stereotactic Radiosurgery: A Reappraisal of the RANO-BM Criteria

BACKGROUND

Brain metastases (BM) are increasingly being treated using stereotactic radiosurgery (SRS). Standardized response criteria are necessary to improve research and treatment protocols. This study's goal was to validate the RANO-BM criteria thresholds for tumor progression in a cohort of patients with brain metastases managed using SRS.

METHODS

We performed a retrospective analysis of patients treated at least twice with SRS for brain metastases. Local progression, as defined by RANO-BM criteria, was compared to our multidisciplinary tumor board's treatment recommendation. A ROC curve was generated using varying diameter thresholds to assess the sensitivity and specificity of current RANO-BM criteria.

RESULTS

249 metastases in 67 patients were included in the analysis. RANO-BM criteria current progression thresholds yielded a sensitivity of 38%, a specificity of 95%, a positive predictive value of 71%, and a negative predictive value of 84% relative to our tumor board's treatment recommendation. Modified RANO-BM criteria using absolute diameter differences of 2.5 mm yielded a sensitivity of 83%, a specificity of 87%, a positive predictive value of 67% and a negative predictive value of 94%.

CONCLUSIONS

Current RANO-BM criteria unreliably identifies clinically relevant tumor progression. The use of absolute diameter differences thresholds appears superior in our BM cohort.

Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study

BACKGROUND

To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients.

METHODS

Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements.

RESULTS

The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88).

CONCLUSIONS

Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients.

Pseudoprogression of thoracic tumor after radiotherapy in the era of immunotherapy: a case series

Pseudoprogression is rarely mentioned after radiotherapy except for central nervous system tumors. With the widespread of immunotherapy, the incidence of pseudoprogression of thoracic tumor after radiotherapy is increasing. This study summarized the clinical features of pseudoprogression in 4 patients who had underwent thoracic radiotherapy after and/or followed by immunotherapy. All of them had received chemotherapy and immunotherapy before thoracic radiotherapy. After radiotherapy, pseudoprogression occurred within 3 months after initiation of immune consolidation/rechallenge therapy. At least a 20% increase in the sum of the longest diameter of target lesions were measured on their chest image. During this period, patients' ECOG PS scores remained stable, specific serum tumor markers did not increase significantly. Treatment strategies did not change after pseudoprogression. The causes of radiographic pseudoprogression in this case series may be attributed to disturbances such as pneumonitis, atelectasis, mucus blockages and infection. In the era of immunotherapy, pseudoprogression of thoracic tumors after chest radiotherapy might become a common phenomenon. It is important for us to identify pseudoprogression based on patient's general status, radiological changes, and laboratory tests.

Extracellular-Vesicle-Based Cancer Panels Diagnose Glioblastomas with High Sensitivity and Specificity

Glioblastoma is one of the most devastating neoplasms of the central nervous system. This study focused on the development of serum extracellular vesicle (EV)-based glioblastoma tumor marker panels that can be used in a clinic to diagnose glioblastomas and to monitor tumor burden, progression, and regression in response to treatment. RNA sequencing studies were performed using RNA isolated from serum EVs from both patients (n = 85) and control donors (n = 31). RNA sequencing results for preoperative glioblastoma EVs compared to control EVs revealed 569 differentially expressed genes (DEGs, 2XFC, FDR < 0.05). By using these DEGs, we developed serum-EV-based biomarker panels for the following glioblastomas: wild-type IDH1 (96% sensitivity/80% specificity), MGMT promoter methylation (91% sensitivity/73% specificity), p53 gene mutation (100% sensitivity/89% specificity), and TERT promoter mutation (89% sensitivity/100% specificity). This is the first study showing that serum-EV-based biomarker panels can be used to diagnose glioblastomas with a high sensitivity and specificity.

Charged particle therapy for high-grade gliomas in adults: a systematic review

High-grade gliomas are the most common intracranial malignancies, and their current prognosis remains poor despite standard aggressive therapy. Charged particle beams have unique physical and biological properties, especially high relative biological effectiveness (RBE) of carbon ion beam might improve the clinical treatment outcomes of malignant gliomas. We systematically reviewed the safety, efficacy, and dosimetry of carbon-ion or proton radiotherapy to treat high-grade gliomas. The protocol is detailed in the online PROSPERO database, registration No. CRD42021258495. PubMed, EMBASE, Web of Science, and The Cochrane Library databases were collected for data analysis on charged particle radiotherapy for high-grade gliomas. Until July 2022, two independent reviewers extracted data based on inclusion and exclusion criteria. Eleven articles were eligible for further analysis. Overall survival rates were marginally higher in patients with the current standard of care than those receiving concurrent intensity-modulated radiotherapy plus temozolomide. The most common side effects of carbon-ion-related therapy were grade 1-2 (such as dermatitis, headache, and alopecia). Long-term toxicities (more than three to six months) usually present as radiation necrosis; however, toxicities higher than grade 3 were not observed. Similarly, dermatitis, headache, and alopecia are among the most common acute side effects of proton therapy treatment. Despite improvement in survival rates, the method of dose-escalation using proton boost is associated with severe brain necrosis which should not be clinically underestimated. Regarding dosimetry, two studies compared proton therapy and intensity-modulated radiation therapy plans. Proton therapy plans aimed to minimize dose exposure to non-target tissues while maintaining target coverage. The use of charged-particle radiotherapy seems to be effective with acceptable adverse effects when used either alone or as a boost. The tendency of survival outcome shows that carbon ion boost is seemingly superior to proton boost. The proton beam could provide good target coverage, and it seems to reduce dose exposure to contralateral organs at risk significantly. This can potentially reduce the treatment-related dose- and volume-related side effects in long-term survivors, such as neurocognitive impairment. High-quality randomized control trials should be conducted in the future. Moreover, Systemic therapeutic options that can be paired with charged particles are necessary.

A Comparison of PET Tracers in Recurrent High-Grade Gliomas: A Systematic Review

Humans with high-grade gliomas have a poor prognosis, with a mean survival time of just 12-18 months for patients who undergo standard-of-care tumor resection and adjuvant therapy. Currently, surgery and chemoradiotherapy serve as standard treatments for this condition, yet these can be complicated by the tumor location, growth rate and recurrence. Currently, gadolinium-based, contrast-enhanced magnetic resonance imaging (CE-MRI) serves as the predominant imaging modality for recurrent high-grade gliomas, but it faces several drawbacks, including its inability to distinguish tumor recurrence from treatment-related changes and its failure to reveal the entirety of tumor burden (de novo or recurrent) due to limitations inherent to gadolinium contrast. As such, alternative imaging modalities that can address these limitations, including positron emission tomography (PET), are worth pursuing. To this end, the identification of PET-based markers for use in imaging of recurrent high-grade gliomas is paramount. This review will highlight several PET radiotracers that have been implemented in clinical practice and provide a comparison between them to assess the efficacy of these tracers.

Performance of 18 F-FAPI PET/CT in assessing glioblastoma before radiotherapy: a pilot study

BACKGROUND

We aimed to determine the performance of ¹⁸ F-FAPI PET/CT used for preprocedural assessment of glioblastoma before radiotherapy.

METHODS

Twelve glioblastoma patients having undergone incomplete surgical resection or biopsy were examined with ¹⁸ F-FAPI PET/CT and MRI scanning before radiotherapy. All patients had confirmed tumor residues according to findings of histopathological and/or long-term clinical and radiological follow-ups. Lesion characterization data, including SUV_max and tumor-to-background ratio (TBR) on PET/CT were attained. PET/CT and MRI findings were compared in terms of number of lesions. The correlation between immunohistochemistry, molecular expression, and PET/CT parameters was also evaluated.

RESULTS

¹⁸ F-FAPI PET/CT detected 16 FAPI-avid out of 23 lesions in 12 patients described on MRI. MRI was statistically different from ¹⁸ F-FAPI PET/CT for lesion detection according to the exact McNemar statistical test (P = 0.0156). The SUV_max and TBR of the glioblastomas was 7.08 ± 3.55 and 19.95 ± 13.22, respectively. The sensitivity and positive predictive value (PPV) of ¹⁸ F-FAPI PET were 69.6% and 100%, respectively. Neither the Ki-67 index nor the molecular expression was correlated with the FAPI-PET/CT parameters.

CONCLUSION

¹⁸ F-FAPI PET/CT detects glioblastomas at a lower rate than MRI. However, the 100% PPV of the examination may make it useful for differentiating controversial lesions detected on MRI. The ¹⁸ F-FAPI-avid lesions are displayed more clearly probably due to a higher TBR. ¹⁸ F-FAPI PET/CT imaging might find application in glioblastoma biopsy and radiotherapy planning.

Apatinib combined with temozolomide treatment for pseudoprogression in glioblastoma: A case report

RATIONALE

Glioblastoma is the most common malignant tumor of the central nervous system, which originates from glial cells and corresponding precursors. Due to its strong invasion and rapid growth, the prognosis of patients after treatment is very poor and easy to relapse.

PATIENT CONCERNS

In August 2015, a 48 years old man with a relapse of glioblastoma.

DIAGNOSES

The patient was diagnosed by computed tomography, magnetic resonance imaging, and pathological biopsy in this case report.

INTERVENTIONS

The patient underwent 2 surgeries, radiotherapy, and multiple regular chemotherapy sessions over the next 6 years. Apatinib, an inhibitor of vascular endothelial growth factor receptor 2 was given to treat recurrent glioma.

OUTCOMES

It was found that radiotherapy combined with temozolomide administration often increased the size of the original lesion or produced a new glioblastoma lesion. The lesion development was similar to tumor progression, which was called pseudoprogression. And it significantly prolonged the survival of this patient.

LESSONS

Surgery, radiotherapy and chemotherapy with apatinib and temozolomide are effective to treat the patients with pseudoprogression in glioblastoma.

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.

The Role of Apparent Diffusion Coefficient Values in Glioblastoma: Differentiating Tumor Progression Versus Treatment-Related Changes

OBJECTIVE

Glioblastoma represents the most common primary brain malignancy with a median survival of 15 months. Follow-up examinations are crucial to establish the presence of tumor recurrence, as well as treatment-associated changes such as ischemic infarction and radiation effects. Even though magnetic resonance imaging is a valuable tool, a histopathological diagnosis is often required because of imaging overlap between tumor recurrence and treatment associated changes. We set out to measure the apparent diffusion coefficient (ADC) values of the lesions in magnetic resonance imaging scans of treated glioblastoma patients to investigate if ADC values could accurately differentiate between tumor progression, radiation-related changes, and ischemic infarctions.

METHODS

We evaluated ADC values among 3 groups, patients with tumor progression, radiation necrosis, and ischemic infarctions. The regions of interest were placed in the areas of greatest hypointensity among solid lesions using the ADC maps, excluding areas with necrotic, cystic, or hemorrhagic changes. The ADC values of the contralateral normal appearing white matter were also measured as the reference value for each patient. The relative ADC (rADC) values were measured for all 3 groups. Comparison between lesions and normal white matter was evaluated by Wilcoxon signed test.

RESULTS

A total of 157 patients were included in the study; 49 patients classified as tumor progression, 58 patients as radiation necrosis, and 50 patients as ischemic infarctions. The mean ± SD ADC value was 752.8 ± 132.5 for tumor progression, 479.0 ± 105.2 for radiation-related changes, and 250.1 ± 57.2 for ischemic infarctions. The mean ± SD rADC value was 1.07 ± 0.22 for tumor progression, 0.66 ± 0.14 for radiation necrosis, and 0.34 ± 0.08 for ischemic infarctions. The mean rADC values were significantly higher in tumor progression, compared with both radiation necrosis and ischemic changes (P < 0.001).

CONCLUSIONS

The present study demonstrates that ADC values are a helpful tool to differentiate between tumor progression, radiation necrosis, and posttreatment ischemic changes.

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.

Iatrogenic Influence on Prognosis of Radiation-Induced Contrast Enhancements in Patients with Glioma WHO 1-3 following Photon and Proton Radiotherapy

BACKGROUND AND PURPOSE

Radiation-induced contrast enhancement (RICE) is a common side effect following radiotherapy for glioma, but both diagnosis and handling are challenging. Due to the potential risks associated with RICE and its challenges in differentiating RICE from tumor progression, it is critical to better understand how RICE prognosis depends on iatrogenic influence.

MATERIALS AND METHODS

We identified 99 patients diagnosed with RICE who were previously treated with either photon or proton therapy for World Health Organization (WHO) grade 1-3 primary gliomas. Post-treatment brain MRI-based volumetric analysis and clinical data collection was performed at multiple time points.

RESULTS

The most common histologic subtypes were astrocytoma (50%) and oligodendroglioma (46%). In 67%, it was graded WHO grade 2 and in 86% an IDH mutation was present. RICE first occurred after 16 months (range: 1 - 160) in median. At initial RICE occurrence, 39% were misinterpreted as tumor progression. A tumor-specific therapy including chemotherapy or re-irradiation led to a RICE size progression in 86% and 92% of cases, respectively and RICE symptom progression in 57% and 65% of cases, respectively. A RICE-specific therapy such as corticosteroids or Bevacizumab for larger or symptomatic RICE led to a RICE size regression in 81% of cases with symptom stability or regression in 62% of cases.

CONCLUSIONS

While with chemotherapy and re-irradiation a RICE progression was frequently observed, anti-edematous or anti-VEGF treatment frequently went along with a RICE regression. For RICE, correct diagnosis and treatment decisions are challenging and critical and should be made interdisciplinarily.

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.

The Value of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in the Differentiation of Pseudoprogression and Recurrence of Intracranial Gliomas

Objective

The objective of this study was to determine the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing postoperative changes in intracranial gliomas.

Method

A total of fifty-one patients who had new enhanced lesions after surgical resection followed by standard radiotherapy and chemotherapy were collected retrospectively from October 2014 to June 2021. The patients were divided into a pseudoprogression group (15 cases) and a recurrence group (36 cases) according to the pathological results of the second operation or a follow-up of more than six months. The follow-up data of all patients were complete, and DCE-MRI was performed. The images were processed to obtain the quantitative parameters K^trans, Ve, and Kep and the semiquantitative parameter iAUC, which were analysed with relevant statistical software.

Results

First, the difference in K^trans and iAUC values between the two groups was statistically significant (P < 0.05), and the difference in Ve and Kep values was not statistically significant (P > 0.05). Second, by comparing the area under the curve, threshold, sensitivity and specificity of K^trans, and iAUC, it was found that the iAUC threshold value was slightly higher than that of K^trans, and the specificity of K^trans was equal to that of iAUC, while the area under the curve and sensitivity of K^trans were higher than those of iAUC. Third, K^trans and iAUC had high accuracy in diagnosing recurrence and pseudoprogression, and K^trans had higher accuracy than iAUC.

Conclusion

In this study, DCE-MRI has a certain diagnostic value in the early differentiation of recurrence and pseudoprogression, offering a new method for the diagnosis and assessment of gliomas after surgery.

Delayed cerebral pseudoaneurysm following surgical and combined-modality therapy for glioblastoma multiforme: illustrative case

BACKGROUND

Post–radiation therapy and chemotherapy cerebral pseudoaneurysms are rare entities. Within previous tumor treatment areas on nonvascular imaging, they are potentially confused as recurrent tumor.

OBSERVATIONS

A 61-year-old man was a long-term survivor of glioblastoma multiforme whose treatment consisted of open biopsy followed by radiotherapy to 60 Gy and systemic carmustine. On surveillance imaging, enlargement of a posttreatment cyst and new enhancing lateral “mural nodule” was first noticed approximately 16 years after initial treatment. Over 12 months, both continued to enlarge. Initially referred to as recurrence, subsequent angiography showed the mural nodule to be an unruptured distal middle cerebral artery pseudoaneurysm within the previous tumor bed. The patient underwent repeat craniotomy for clipping of the aneurysm and biopsy of the cyst wall, which was negative for malignancy.

LESSONS

Delayed pseudoaneurysms following radiation therapy and chemotherapy for malignant brain tumors are rare but have been previously reported. Their appearance on cross-sectional imaging can mimic recurrence, and they should be kept in the differential of new, circumscribed enhancement within such treatment areas.

The Clinical Applications of Liquid Biopsies in Pediatric Brain Tumors: A Systematic Literature Review

Simple Summary

Brain tumors are the most common solid cancer in children and are traditionally diagnosed via a tissue biopsy or resection. Liquid biopsy offers the possibility to characterize brain tumors based on their circulating DNA in blood, cerebrospinal fluid or even urine. Moreover, disease progress can be monitored accurately and sometimes even detected before radiographic progression. More trials are needed to standardize the use of liquid biopsy in pediatric brain tumors.

Abstract

Background: Pediatric brain tumors are the most common solid tumor in children. Traditionally, tumor diagnosis and molecular analysis were carried out on tumor tissue harvested either via biopsy or resection. However, liquid biopsy allows analysis of circulating tumor DNA in corporeal fluids such as cerebrospinal fluid or blood. Methods: We performed a systematic review in Pubmed and Embase regarding the role of liquid biopsy in pediatric brain tumors. Results: Nine studies with a total of 570 patients were included. The preferred corporeal fluid for analysis with a relatively high yield of ct-DNA was cerebrospinal fluid (CSF). For high-grade glioma, liquid biopsy can successfully characterize H3K27mutations and predict tumor progression before it is radiographically detected. Moreover, liquid biopsy has the potential to distinguish between pseudo-progression and actual progression. In medulloblastoma, ct-DNA in the CSF can be used as a surrogate marker of measurable residual disease and correlates with response to therapy and progression of the tumor up to three months before radiographic detection. Conclusion: Liquid biopsy is primarily useful in high-grade pediatric brain tumors such as diffuse midline glioma or medulloblastoma. Disease detection and monitoring is feasible for both tumor entities. More trials to standardize its use for pediatric brain tumors are necessary.

TfR-T12 short peptide and pH sensitive cell transmembrane peptide modified nano-composite micelles for glioma treatment via remodeling tumor microenvironment

Two kinds of amphiphilic block copolymers of TfR-T12-PEG-PLGA and TATH7-PEG-PLGA were synthesized to self-assembly nano-composite micelles for encapsulating paclitaxel and imiquimod synchronously. TfR-T12 peptide modified nano-composite micelles can pass through BBB in a TfR-mediated way to achieve targeted delivery of chemotherapeutic drugs, and pH sensitive TATH7 peptide modified nano-composite micelles enhanced uptake efficiency more significantly under pH 5.5 medium than pH 7.4 medium. The results of pharmacodynamic evaluation in vivo showed that the nano-composite micelles had achieved good anti-tumor effect in subcutaneous and normotopia glioma models, and effectively prolonged the life cycle of tumor-bearing mice. The nano-composite micelles regulated the immunosuppression phenomenon of tumor microenvironment significantly, and promoted the M1 polarization of TAMs, then enhanced the proliferation and activation of CD8⁺ T cells in tumor microenvironment. It comes to conclusion that the nano-composite micelle achieves the purpose of effective treatment of glioma by chemotherapy combined with immunotherapy.

Short TE downfield magnetic resonance spectroscopy in a mouse model of brain glioma

PURPOSE

Enhanced cell proliferation in tumors can be associated with altered metabolic profiles and dramatic microenvironmental changes. Downfield magnetic resonance spectroscopy (MRS) has received increasing attention due to its ability to report on labile resonances of molecules not easily detected in upfield ¹ H MRS. Image-selected-in-vivo-spectroscopy-relaxation enhanced MRS (iRE-MRS) was recently introduced for acquiring short echo-time (TE) spectra. Here, iRE-MRS was used to investigate in-vivo downfield spectra in glioma-bearing mice.

METHODS

Experiments were performed in vivo in an immunocompetent glioma mouse model at 9.4 T using a cryogenic coil. iRE-MRS spectra were acquired in N = 6 glioma-bearing mice (voxel size = 2.2³  mm³ ) and N = 6 control mice. Spectra were modeled by a sum of Lorentzian peaks simulating known downfield resonances, and differences between controls and tumors were quantified using relative peak areas.

RESULTS

Short TE tumor spectra exhibited large qualitative differences compared to control spectra. Most peaks appeared modulated, with strong attenuation of NAA (∼7.82, 7.86 ppm) and changes in relative peak areas between 6.75 and 8.49 ppm. Peak areas tended to be smaller for DF_6.83 , DF_7.60 , DF_8.18 and NAA; and larger for DF_7.95 and DF_8.24 . Differences were also detected in signals resonating above 8.5 ppm, assumed to arise from NAD+.

CONCLUSIONS

In-vivo downfield ¹ H iRE-MRS of mouse glioma revealed differences between controls and tumor bearing mice, including in metabolites which are not easily detectable in the more commonly investigated upfield spectrum. These findings motivate future downfield MRS investigations exploring pH and exchange contributions to these differences.

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.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.

Advanced Imaging Techniques for Newly Diagnosed and Recurrent Gliomas

Management of gliomas following initial diagnosis requires thoughtful presurgical planning followed by regular imaging to monitor treatment response and survey for new tumor growth. Traditional MR imaging modalities such as T1 post-contrast and T2-weighted sequences have long been a staple of tumor diagnosis, surgical planning, and post-treatment surveillance. While these sequences remain integral in the management of gliomas, advances in imaging techniques have allowed for a more detailed characterization of tumor characteristics. Advanced MR sequences such as perfusion, diffusion, and susceptibility weighted imaging, as well as PET scans have emerged as valuable tools to inform clinical decision making and provide a non-invasive way to help distinguish between tumor recurrence and pseudoprogression. Furthermore, these advances in imaging have extended to the operating room and assist in making surgical resections safer. Nevertheless, surgery, chemotherapy, and radiation treatment continue to make the interpretation of MR changes difficult for glioma patients. As analytics and machine learning techniques improve, radiomics offers the potential to be more quantitative and personalized in the interpretation of imaging data for gliomas. In this review, we describe the role of these newer imaging modalities during the different stages of management for patients with gliomas, focusing on the pre-operative, post-operative, and surveillance periods. Finally, we discuss radiomics as a means of promoting personalized patient care in the future.

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.

A Comparison of Single- and Multiparametric MRI Models for Differentiation of Recurrent Glioblastoma from Treatment-Related Change

To evaluate single- and multiparametric MRI models to differentiate recurrent glioblastoma (GBM) and treatment-related changes (TRC) in clinical routine imaging. Selective and unselective apparent diffusion coefficient (ADC) and minimum, mean, and maximum cerebral blood volume (CBV) measurements in the lesion were performed. Minimum, mean, and maximum ratios_CBV (CBV_lesion to CBV_{healthy white matter}) were computed. All data were tested for lesion discrimination. A multiparametric model was compiled via multiple logistic regression using data demonstrating significant difference between GBM and TRC and tested for its diagnostic strength in an independent patient cohort. A total of 34 patients (17 patients with recurrent GBM and 17 patients with TRC) were included. ADC measurements showed no significant difference between both entities. All CBV and ratios_CBV measurements were significantly higher in patients with recurrent GBM than TRC. A minimum CBV of 8.5, mean CBV of 116.5, maximum CBV of 327 and ratio_CBV minimum of 0.17, ratio_CBV mean of 2.26 and ratio_CBV maximum of 3.82 were computed as optimal cut-off values. By integrating these parameters in a multiparametric model and testing it in an independent patient cohort, 9 of 10 patients, i.e., 90%, were classified correctly. The multiparametric model further improves radiological discrimination of GBM from TRC in comparison to single-parameter approaches and enables reliable identification of recurrent tumors.

Congress of Neurological Surgeons systematic review and evidence-based guidelines for the treatment of adults with progressive glioblastoma update: introduction and methods

INTRODUCTION

The management of glioblastoma at the time of progression is an important facet of all physicians involved in neuro-oncology. This is an update of the evidence-based guidelines for management of progressive glioblastoma published by the Congress of Neurological Surgeons and American Association of Neurological Surgeons in 2014.

METHODS

The medical literature from July 1, 2012 through March 31, 2019 was searched in MEDLINE® and Embase® and the Cochrane Database of Systematic Reviews, Cochrane Controlled Trials Registry, and Cochrane Database of Abstracts of Reviews of Effects to determine if information was available to update, modify or create new recommendations related to imaging, cytoreductive surgery, neuropathology, radiotherapy, cytotoxic chemotherapy, targeted therapy, and immunotherapy.

RESULTS

The writing group utilized the information from the updated literature search to formulate recommendations that were exclusively evidence based and not founded on potentially biased consensus or expert opinion.

CONCLUSION

The series of guideline documents provides an update of the information and recommendations that could be derived in the 2014 version. It sets a benchmark as to what we really know about the management of this difficult disease. It also provides clues to key investigations that are necessary to move us toward truly effective disease control.

Contribution of PET imaging to radiotherapy planning and monitoring in glioma patients - a report of the PET/RANO group

The management of patients with glioma usually requires multimodality treatment including surgery, radiotherapy, and systemic therapy. Accurate neuroimaging plays a central role for radiotherapy planning and follow-up after radiotherapy completion. In order to maximize the radiation dose to the tumor and to minimize toxic effects on the surrounding brain parenchyma, reliable identification of tumor extent and target volume delineation is crucial. The use of positron emission tomography (PET) for radiotherapy planning and monitoring in gliomas has gained considerable interest over the last several years, but Class I data are not yet available. Furthermore, PET has been used after radiotherapy for response assessment and to distinguish tumor progression from pseudoprogression or radiation necrosis. Here, the Response Assessment in Neuro-Oncology (RANO) working group provides a summary of the literature and recommendations for the use of PET imaging for radiotherapy of patients with glioma based on published studies, constituting levels 1-3 evidence according to the Oxford Centre for Evidence-based Medicine.

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.

Imaging Surveillance of Gliomas: Role of Basic and Advanced Imaging Techniques

It is essential to be aware of widely accepted criteria for grading of treatment response in both high-grade and low-grade gliomas. These criteria primarily take into account responses of measurable and nonmeasurable lesions on T2-weighted, fluid-attenuated inversion recovery, and postcontrast images to determine a final category of response for the patient. The additional role that other advanced imaging techniques, such as diffusion and perfusion imaging, can play in the surveillance of these tumors is discussed in this article.

Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma

AIM

To investigate machine learning based models combining clinical, radiomic, and molecular information to distinguish between early true progression (tPD) and pseudoprogression (psPD) in patients with glioblastoma.

MATERIALS AND METHODS

A retrospective analysis was undertaken of 76 patients (46 tPD, 30 psPD) with early enhancing disease following chemoradiotherapy for glioblastoma. Outcome was determined on follow-up until 6 months post-chemoradiotherapy. Models comprised clinical characteristics, O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation status, and 307 quantitative imaging features extracted from enhancing disease and perilesional oedema masks on early post-chemoradiotherapy contrast-enhanced T1-weighted imaging, T2-weighted imaging (T2WI), and apparent diffusion coefficient (ADC) maps. Feature selection was performed within bootstrapped cross-validated recursive feature elimination with a random forest algorithm. Naive Bayes five-fold cross-validation was used to validate the final model.

RESULTS

Top selected features included age, MGMT promoter methylation status, two shape-based features from the enhancing disease mask, three radiomic features from the enhancing disease mask on ADC, and one radiomic feature from the perilesional oedema mask on T2WI. The final model had an area under the receiver operating characteristics curve (AUC) of 0.80, sensitivity 78.2%, specificity 66.7%, and accuracy of 73.7%.

CONCLUSION

Incorporating a machine learning-based approach using quantitative radiomic features from standard-of-care magnetic resonance imaging (MRI), in combination with clinical characteristics and MGMT promoter methylation status has a complementary effect and improves model performance for early prediction of glioblastoma treatment response.

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.

The Definition and Delineation of the Target Area of Radiotherapy Based on the Recurrence Pattern of Glioblastoma After Temozolomide Chemoradiotherapy

Radiotherapy is an important treatment for glioblastoma (GBM), but there is no consensus on the target delineation for GBM radiotherapy. The Radiation Therapy Oncology Group (RTOG) and European Organisation for Research and Treatment of Cancer (EORTC) each have their own rules. Our center adopted a target volume delineation plan based on our previous studies. This study focuses on the recurrence pattern of GBM patients whose target delineations did not intentionally include the T2/fluid-attenuated inversion recovery (FLAIR) hyperintensity area outside of the gross tumor volume (GTV). We prospectively collected 162 GBM cases and retrospectively analysed the clinical data and continuous dynamic magnetic resonance images (MRI) of 55 patients with recurrent GBM. All patients received concurrent radiotherapy and chemotherapy with temozolomide (TMZ). The GTV that we defined includes the postoperative T1-weighted MRI enhancement area and resection cavity. Clinical target volume 1 (CTV1) and CTV2 were defined as GTVs with 1 and 2 cm margins, respectively. Planning target volume 1 (PTV1) and PTV2 were defined as CTV1 and CTV2 plus a 3 mm margin with prescribed doses of 60 and 54 Gy, respectively. The first recurrent contrast-enhanced T1-weighted MRI was introduced into the Varian Eclipse radiotherapy planning system and fused with the original planning computed tomography (CT) images to determine the recurrence pattern. The median follow-up time was 15.8 months. The median overall survival (OS) and progression-free survival (PFS) were 17.7 and 7.0 months, respectively. Among the patients, 44 had central recurrences, two had in-field recurrences, one had marginal recurrence occurred, 11 had distant recurrences, and three had subependymal recurrences. Five patients had multiple recurrence patterns. Compared to the EORTC protocol, target delineation that excludes the adjacent T2/FLAIR hyperintensity area reduces the brain volume exposed to high-dose radiation (P = 0.000) without an increased risk of marginal recurrence. Therefore, it is worthwhile to conduct a clinical trial investigating the feasibility of intentionally not including the T2/FLAIR hyperintensity region outside of the GTV.

A Review of Newly Diagnosed Glioblastoma

Glioblastoma is an aggressive and inevitably recurrent primary intra-axial brain tumor with a dismal prognosis. The current mainstay of treatment involves maximally safe surgical resection followed by radiotherapy over a 6-week period with concomitant temozolomide chemotherapy followed by temozolomide maintenance. This review provides a summary of the epidemiological, clinical, histologic and genetic characteristics of newly diagnosed disease as well as the current standard of care and potential future therapeutic prospects.

Advancements in Neuroimaging to Unravel Biological and Molecular Features of Brain Tumors

Simple Summary

Advanced neuroimaging is gaining increasing relevance for the characterization and the molecular profiling of brain tumor tissue. On one hand, for some tumor types, the most widespread advanced techniques, investigating diffusion and perfusion features, have been proven clinically feasible and rather robust for diagnosis and prognosis stratification. In addition, 2-hydroxyglutarate spectroscopy, for the first time, offers the possibility to directly measure a crucial molecular marker. On the other hand, numerous innovative approaches have been explored for a refined evaluation of tumor microenvironments, particularly assessing microstructural and microvascular properties, and the potential applications of these techniques are vast and still to be fully explored.

Abstract

In recent years, the clinical assessment of primary brain tumors has been increasingly dependent on advanced magnetic resonance imaging (MRI) techniques in order to infer tumor pathophysiological characteristics, such as hemodynamics, metabolism, and microstructure. Quantitative radiomic data extracted from advanced MRI have risen as potential in vivo noninvasive biomarkers for predicting tumor grades and molecular subtypes, opening the era of “molecular imaging” and radiogenomics. This review presents the most relevant advancements in quantitative neuroimaging of advanced MRI techniques, by means of radiomics analysis, applied to primary brain tumors, including lower-grade glioma and glioblastoma, with a special focus on peculiar oncologic entities of current interest. Novel findings from diffusion MRI (dMRI), perfusion-weighted imaging (PWI), and MR spectroscopy (MRS) are hereby sifted in order to evaluate the role of quantitative imaging in neuro-oncology as a tool for predicting molecular profiles, stratifying prognosis, and characterizing tumor tissue microenvironments. Furthermore, innovative technological approaches are briefly addressed, including artificial intelligence contributions and ultra-high-field imaging new techniques. Lastly, after providing an overview of the advancements, we illustrate current clinical applications and future perspectives.

Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review: Part 1 - Molecular, morphological and clinical features

With new therapeutic protocols, more patients treated for glioblastoma have experienced a suspicious radiologic image of progression (pseudoprogression) during follow-up. Pseudoprogression should be differentiated from true progression because the disease management is completely different. In the case of pseudoprogression, the follow-up continues, and the patient is considered stable. In the case of true progression, a treatment adjustment is necessary. Presently, a pseudoprogression diagnosis certainly needs to be pathologically confirmed. Some important efforts in the radiological, histopathological, and genomic fields have been made to differentiate pseudoprogression from true progression, and the assessment of response criteria exists but remains limited. The aim of this paper is to highlight clinical and pathological markers to differentiate pseudoprogression from true progression through a literature review.

Differentiating high-grade glioma recurrence from pseudoprogression: Comparing diffusion kurtosis imaging and diffusion tensor imaging

PURPOSE

To compare the diagnostic value of DKI and DTI in differentiation of high-grade glioma recurrence and pseudoprogression (PsP).

METHOD

Forty patients with high-grade gliomas who exhibited new enhancing lesions (24 high-grade glioma recurrence and 16 PsP) within 6 months after surgery followed by completion of chemoradiation therapy. All patients underwent repeat surgery or biopsy after routine MRI and DKI (including DTI). They were histologically classified into high-grade glioma recurrence and PsP groups. DKI (mean kurtosis [MK], axial kurtosis [Ka], and radial kurtosis [Kr]) and DTI (mean diffusivity [MD] and fractional anisotropy [FA]) parameters in the enhancing lesions and in the perilesional edema were measured. Inter-group differences between high-grade glioma recurrence and PsP were compared using the Mann-Whitney U test The receiver operating characteristic (ROC) curve was used to assess differential diagnostic efficacy of each parameter, and Z-scores were used to compare the value between DKI and DTI.

RESULTS

Relative MK (rMK) was significantly higher and relative MD (rMD) was significantly lower in the enhancing lesions of high-grade glioma recurrence compared to PsP (P <  0.001, P = 0.006, respectively). The AUC was 0.914 for rMK and 0.760 for rMD, and this difference was significant (P = 0.030). In the perilesional edema, rMK values were significantly higher and rMD values were significantly lower in high-grade glioma recurrence compared to PsP (P <  0.001, P =  0.005).

CONCLUSIONS

DKI had superior performance in differentiating high-grade glioma recurrence from PsP, and rMK appeared to be the best independent predictor.

Advanced magnetic resonance imaging to support clinical drug development for malignant glioma

Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.

Transferrin Receptor-Targeted PEG-PLA Polymeric Micelles for Chemotherapy Against Glioblastoma Multiforme

Background

The safe and efficient delivery of chemotherapeutic agents is critical to glioma therapy. However, chemotherapy for glioma is extremely challenging because the blood–brain barrier (BBB) rigorously prevents drugs from reaching the tumor region.

Materials and Methods

TfR-T12 peptide-modified PEG-PLA polymer was synthesized to deliver paclitaxel (PTX) for glioma therapy. TfR was significantly expressed on brain capillary endothelial cells and glioma cells; therefore, TfR-T12 peptide-modified micelles can cross the BBB system and target glioma cells.

Results

TfR-T12-PEG-PLA/PTX polymeric micelles (TfR-T12-PMs) could be absorbed rapidly by tumor cells, and traversed effectively the BBB monolayers. TfR-T12-PMs can effectively inhibit the proliferation of U87MG cells in vitro, and TfR-T12-PMs loaded with paclitaxel presented better antiglioma effect with prolonged median survival of nude mice-bearing glioma than the unmodified PMs.

Conclusion

The TfR-T12-PMs could effectively overcome the BBB barrier and accomplish glioma-targeted drug delivery, thus validating its potential in improving the therapeutic outcome in multiforme.

Glioblastoma in adults: a Society for Neuro-Oncology (SNO) and European Society of Neuro-Oncology (EANO) consensus review on current management and future directions

Glioblastomas are the most common form of malignant primary brain tumor and an important cause of morbidity and mortality. In recent years there have been important advances in understanding the molecular pathogenesis and biology of these tumors, but this has not translated into significantly improved outcomes for patients. In this consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of isocitrate dehydrogenase wildtype (IDHwt) glioblastomas will be discussed. In addition, novel therapies such as targeted molecular therapies, agents targeting DNA damage response and metabolism, immunotherapies, and viral therapies will be reviewed, as well as the current challenges and future directions for research.

Effective Treatment of Glioblastoma Multiforme With Oncolytic Virotherapy: A Case-Series

Glioblastoma multiforme (GBM) remains an incurable condition, associated with a median survival time of 15 months with best standard of care and 5-year survival rate of <10%. We report on four GBM patients on combination treatment regimens that included oncolytic virus (OV) immunotherapy, who achieved clinical and radiological responses with long-term survival, thus far, of up to 14 years, and good quality of life. We discuss the radiological findings that provide new insights into this treatment, the scientific rationale of this innovative and promising therapy, and considerations for future research.