Malignant gliomas: MR imaging spectrum of radiation therapy- and chemotherapy-induced necrosis of the brain after treatment

Predicted probabilities of brain injury after carbon ion radiotherapy for head and neck and skull base tumors in long-term survivors

BACKGROUND AND PURPOSE

We aimed to determine the risk factors for radiation-induced brain injury (RIBI¹) after carbon ion radiotherapy (CIRT) to predict their probabilities in long-term survivors.

MATERIALS AND METHODS

We evaluated 104 patients with head, neck, and skull base tumors who underwent CIRT in a regimen of 32 fractions and were followed up for at least 24 months. RIBI was assessed using the Common Terminology Criteria for Adverse Events.

RESULTS

The median follow-up period was 45.5 months; 19 (18.3 %) patients developed grade ≥2 RIBI. The maximal absolute dose covering 5 mL of the brain (D5ml) was the only significant risk factor for grade ≥2 RIBI in the multivariate logistic regression analysis (p = 0.001). The tolerance doses of D5ml for the 5% and 50% probabilities of developing grade ≥2 RIBI were estimated to be 55.4 Gy (relative biological effectiveness [RBE]) and 68.4 Gy (RBE) by a logistic model, respectively.

CONCLUSION

D5ml was most significantly associated with grade ≥2 RIBI and may enable the prediction of its probability.

Current emerging MRI tools for radionecrosis and pseudoprogression diagnosis

PURPOSE OF REVIEW

This review aims to cover current MRI techniques for assessing treatment response in brain tumors, with a focus on radio-induced lesions.

RECENT FINDINGS

Pseudoprogression and radionecrosis are common radiological entities after brain tumor irradiation and are difficult to distinguish from real progression, with major consequences on daily patient care. To date, shortcomings of conventional MRI have been largely recognized but morphological sequences are still used in official response assessment criteria. Several complementary advanced techniques have been proposed but none of them have been validated, hampering their clinical use. Among advanced MRI, brain perfusion measures increase diagnostic accuracy, especially when added with spectroscopy and susceptibility-weighted imaging. However, lack of reproducibility, because of several hard-to-control variables, is still a major limitation for their standardization in routine protocols. Amide Proton Transfer is an emerging molecular imaging technique that promises to offer new metrics by indirectly quantifying intracellular mobile proteins and peptide concentration. Preliminary studies suggest that this noncontrast sequence may add key biomarkers in tumor evaluation, especially in posttherapeutic settings.

SUMMARY

Benefits and pitfalls of conventional and advanced imaging on posttreatment assessment are discussed and the potential added value of APT in this clinicoradiological evolving scenario is introduced.

Brain Tumor Causes, Symptoms, Diagnosis and Radiotherapy Treatment

The strategy used for the treatment of given brain cancer is critical in determining the post effects and survival. An oncological diagnosis of tumor evaluates a range of parameters such as shape, size, volume, location and neurological complexity that define the symptomatic severity. The evaluation determines a suitable treatment approach chosen from a range of options such as surgery, chemotherapy, hormone therapy, radiation therapy and other targeted therapies. Often, a combination of such therapies is applied to achieve superior results. Radiotherapy serves as a better treatment strategy because of a higher survival rate. It offers the flexibility of synergy with other treatment strategies and fewer side effects on organs at risk. This review presents a radiobiological perspective in the treatment of brain tumor. The cause, symptoms, diagnosis, treatment, post-treatment effects and the framework involved in its elimination are summarized.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

Value of PET imaging for radiation therapy

This comprehensive review written by experts in their field gives an overview on the current status of incorporating positron emission tomography (PET) into radiation treatment planning. Moreover, it highlights ongoing studies for treatment individualisation and per-treatment tumour response monitoring for various primary tumours. Novel tracers and image analysis methods are discussed. The authors believe this contribution to be of crucial value for experts in the field as well as for policy makers deciding on the reimbursement of this powerful imaging modality.

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.

Neuroimaging in the Era of the Evolving WHO Classification of Brain Tumors, From the AJR Special Series on Cancer Staging

The inclusion of molecular and genetic information with histopathologic information defines the framework for brain tumor classification and grading. This framework is reflected in the major restructuring of the WHO brain tumor classification system in 2016 and in numerous subsequent proposed updates reflecting ongoing developments in understanding the impact of tumor genotype on classification and grading. This incorporation of molecular and genetic features improves tumor diagnosis and prediction of tumor behavior and response to treatment. Neuroimaging is essential for the noninvasive assessment of pretreatment tumor grading and for identification and determination of therapeutic efficacy. Use of conventional neuroimaging and physiologic imaging techniques, such as diffusion- and perfusion-weighted MRI, can increase diagnostic confidence before and after treatment. Although the use of neuroimaging to consistently determine tumor genetics is not yet robust, promising developments are on the horizon. Given the complexity of the brain tumor microenvironment, the development and implementation of a standardized reporting system can aid in conveying to radiologists, referring providers, and patients important information about brain tumor response to treatment. The purpose of this article is to review the current state and role of neuroimaging in this continuously evolving field.

Diagnosis of Pseudoprogression Following Lomustine-Temozolomide Chemoradiation in Newly Diagnosed Glioblastoma Patients Using FET-PET

PURPOSE

The CeTeG/NOA-09 phase III trial demonstrated a significant survival benefit of lomustine-temozolomide chemoradiation in patients with newly diagnosed glioblastoma with methylated O⁶-methylguanine-DNA methyltransferase (MGMT) promoter. Following lomustine-temozolomide chemoradiation, late and prolonged pseudoprogression may occur. We here evaluated the value of amino acid PET using O-(2-[¹⁸F]fluoroethyl)-l-tyrosine (FET) for differentiating pseudoprogression from tumor progression.

EXPERIMENTAL DESIGN

We retrospectively identified patients (i) who were treated off-study according to the CeTeG/NOA-09 protocol, (ii) had equivocal MRI findings after radiotherapy, and (iii) underwent additional FET-PET imaging for diagnostic evaluation (number of scans, 1-3). Maximum and mean tumor-to-brain ratios (TBR_max, TBR_mean) and dynamic FET uptake parameters (e.g., time-to-peak) were calculated. In patients with more than one FET-PET scan, relative changes of TBR values were evaluated, that is, an increase or decrease of >10% compared with the reference scan was considered as tumor progression or pseudoprogression. Diagnostic performances were evaluated using ROC curve analyses and Fisher exact test. Diagnoses were confirmed histologically or clinicoradiologically.

RESULTS

We identified 23 patients with 32 FET-PET scans. Within 5-25 weeks after radiotherapy (median time, 9 weeks), pseudoprogression occurred in 11 patients (48%). The parameter TBR_mean calculated from the FET-PET performed 10 ± 7 days after the equivocal MRI showed the highest accuracy (87%) to identify pseudoprogression (threshold, <1.95; P = 0.029). The integration of relative changes of TBR_mean further improved the accuracy (91%; P < 0.001). Moreover, the combination of static and dynamic parameters increased the specificity to 100% (P = 0.005).

CONCLUSIONS

The data suggest that FET-PET parameters are of significant clinical value to diagnose pseudoprogression related to lomustine-temozolomide chemoradiation.

Comparison of diagnostic value of 68 Ga-DOTATOC PET/MRI and standalone MRI for the detection of intracranial meningiomas

To evaluate the diagnostic performance of magnetic resonance imaging (MRI) alone in comparison to positron emission tomography/ magnetic resonance imaging (PET/MRI) in patients with meningiomas. 57 patients with a total of 112 meningiomas of the brain were included. PET/MRI, including a fully diagnostic contrast enhanced MRI and PET, were acquired. PET/MRI was used as reference standard. The size and location of meningiomas was recorded. Likelihood-ratio chi-square tests were used to calculate p-values within logistic regression in order to compare different models. A multi-level logistic regression was applied to comply the hierarchical data structure. Multi-level regression adjusts for clustering in data was performed. The majority (n = 103) of meningiomas could be identified based on standard MRI sequences compared to PET/MRI. MRI alone achieved a sensitivity of 95% (95% CI 0.78, 0.99) and specificity of 88% (95% CI 0.58, 0.98). Based on intensity of contrast medium uptake, 97 meningiomas could be diagnosed with intense uptake (93.75%). Sensitivity was lowest with 74% for meningiomas < 0.5 cm³, high with 95% for meningiomas > 2cm³ and highest with 100% for meningiomas 0.5-1.0 cm³. Petroclival meningiomas showed lowest sensitivity with 88% compared to sphenoidal meningiomas with 94% and orbital meningiomas with 100%. Specificity of meningioma diagnostic with MRI was high with 100% for sphenoidal and hemispherical-dural meningiomas and meningiomas with 0.5-1.0 and 1.0-2.0 cm³. Overall MRI enables reliable detection of meningiomas compared to PET/MRI. PET/MRI imaging offers highest sensitivity and specificity for small or difficult located meningiomas.

Use of PET Imaging in Neuro-Oncological Surgery

Simple Summary

The use of positron emission tomography (PET) imaging in neuro-oncological surgery is an exciting field with thriving perspectives. Increasing evidence exists for amino acid-based PET to facilitate interpretation of imaging findings following therapeutic interventions in patients with glioma and brain metastases. In meningioma patients, radiolabeled somatostatin receptor ligands provide an improved tumor tissue visualization in lesions located in the vicinity of the skull base and differentiate between scar tissue and tumor recurrence. Moreover, they can be applied as an individual treatment option in recurrent atypical and anaplastic meningioma not eligible for further surgery and radiotherapy. With a focus on its clinical application, this review provides an overview of the emerging field of PET imaging in neuro-oncological surgery.

Abstract

This review provides an overview of current applications and perspectives of PET imaging in neuro-oncological surgery. The past and future of PET imaging in the management of patients with glioma and brain metastases are elucidated with an emphasis on amino acid tracers, such as O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (¹⁸F-FET). The thematic scope includes surgical resection planning, prognostication, non-invasive prediction of molecular tumor characteristics, depiction of intratumoral heterogeneity, response assessment, differentiation between tumor progression and treatment-related changes, and emerging new tracers. Furthermore, the role of PET using specific somatostatin receptor ligands for the management of patients with meningioma is discussed. Further advances in neuro-oncological imaging can be expected from promising new techniques, such as hybrid PET/MR scanners and the implementation of artificial intelligence methods, such as radiomics.

Simultaneously acquired PET and ASL imaging biomarkers may be helpful in differentiating progression from pseudo-progression in treated gliomas

OBJECTIVES

The aim of this work was investigating the methods based on coupling cerebral perfusion (ASL) and amino acid metabolism ([¹⁸F]DOPA-PET) measurements to evaluate the diagnostic performance of PET/MRI in glioma follow-up.

METHODS

Images were acquired using a 3-T PET/MR system, on a prospective cohort of patients addressed for possible glioma progression. Data were preprocessed with statistical parametric mapping (SPM), including registration on T1-weighted images, spatial and intensity normalization, and tumor segmentation. As index tests, tumor isocontour maps of [¹⁸F]DOPA-PET and ASL T-maps were created and metabolic/perfusion abnormalities were evaluated with the asymmetry index z-score. SPM map analysis of significant size clusters and semi-quantitative PET and ASL map evaluation were performed and compared to the gold standard diagnosis. Lastly, ASL and PET topography of significant clusters was compared to that of the initial tumor.

RESULTS

Fifty-eight patients with unilateral treated glioma were included (34 progressions and 24 pseudo-progressions). The tumor isocontour maps and T-maps showed the highest specificity (100%) and sensitivity (94.1%) for ASL and [¹⁸F]DOPA analysis, respectively. The sensitivity of qualitative SPM maps and semi-quantitative rCBF and rSUV analyses were the highest for glioblastoma.

CONCLUSION

Tumor isocontour T-maps and combined analysis of CBF and [¹⁸F]DOPA-PET uptake allow achieving high diagnostic performance in differentiating between progression and pseudo-progression in treated gliomas. The sensitivity is particularly high for glioblastomas.

KEY POINTS

• Applied separately, MRI and PET imaging modalities may be insufficient to characterize the brain glioma post-therapeutic profile. • Combined ASL and [¹⁸F]DOPA-PET map analysis allows differentiating between tumor progression and pseudo-progression.

Imaging of Neurologic Injury following Oncologic Therapy

Neurologic injury arises from treatment of central nervous system malignancies as result of direct toxic effects or indirect vascular, autoimmune, or infectious effects. Multimodality treatment may potentiate both therapeutic and toxic effects. Symptoms range from mild to severe and permanent. Injuries can be immediate or delayed. Many early complications are nonspecific. Other early and delayed neurologic injuries, such as posterior reversible encephalopathy syndrome, dural sinus thrombosis, infarctions, myelopathy, leukoencephalopathy, and hypophysitis, have unique imaging features. This article reviews treatment options for neurologic malignancies and common and uncommon neurologic injuries that can result from treatment, focusing on radiologic features.

Diffusion histology imaging differentiates distinct pediatric brain tumor histology

High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differentiation of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation, remains an unmet need in their clinical management. We employed a novel Diffusion Histology Imaging (DHI) approach employing diffusion basis spectrum imaging (DBSI) derived metrics as the input classifiers for deep neural network analysis. DHI aims to detect, differentiate, and quantify heterogeneous areas in pediatric high-grade brain tumors, which include normal white matter (WM), densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis, and hemorrhage. Distinct diffusion metric combination would thus indicate the unique distributions of each distinct tumor histology features. DHI, by incorporating DBSI metrics and the deep neural network algorithm, classified pediatric tumor histology with an overall accuracy of 85.8%. Receiver operating analysis (ROC) analysis suggested DHI’s great capability in distinguishing individual tumor histology with AUC values (95% CI) of 0.984 (0.982–0.986), 0.960 (0.956–0.963), 0.991 (0.990–0.993), 0.950 (0.944–0.956), 0.977 (0.973–0.981) and 0.976 (0.972–0.979) for normal WM, densely cellular tumor, less densely cellular tumor, infiltrating edge, necrosis and hemorrhage, respectively. Our results suggest that DBSI-DNN, or DHI, accurately characterized and classified multiple tumor histologic features in pediatric high-grade brain tumors. If these results could be further validated in patients, the novel DHI might emerge as a favorable alternative to the current neuroimaging techniques to better guide biopsy and resection as well as monitor therapeutic response in patients with high-grade brain tumors.

Sevoflurane Limits Glioma Progression by Regulating Cell Proliferation, Apoptosis, Migration, and Invasion via miR-218-5p/DEK/β-Catenin Axis in Glioma

Purpose

Sevoflurane (SEV) is a frequently used volatile anesthetic in cancer surgery. Sevoflurane treatment has been shown to suppress the migration and invasion of several human cancer cells. However, the effect of sevoflurane on glioma remains largely unclear.

Methods

Glioma cell lines (U251 and U343) were treated by various concentrations of sevoflurane. 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT), flow cytometry assay, and transwell assay were performed to detect the cell viability, apoptosis, migration and invasion. Western blot assay was employed to detect the protein levels of β-catenin, c-Myc, CyclinD1, β-catenin, N-cadherin, vimentin, and DEK. Moreover, quantitative real-time polymerase chain reaction (qRT-PCR) was used to examine the expression level of miR-218-5p. The target interaction between miR-218-5p and DEK was predicted through bioinformatics analysis and verified by dual-luciferase reporter assay system.

Results

We found that sevoflurane aberrantly inhibited the abilities on viability, migration, invasion, EMT and β-catenin signaling and promoted cell apoptosis in U251 and U343 cells in a dose-dependent manner. MiR-218-5p strikingly suppressed the abilities of proliferation, migration, invasion rather than apoptosis and activation of β-catenin signaling. Sevoflurane could facilitate the miR-218-5p expression, and its suppressing effects on glioma cells were reversed by pre-treatment with miR-218-5p inhibitors or pcDNA3.1/DEK in vitro and in vivo. Silencing of miR-218-5p reverted sh-DEK and sevoflurane-induced repression on proliferation, migration, invasion, and β-catenin signaling, and promotion on apoptosis in the glioma cells.

Conclusion

Our data showed that sevoflurane inhibited the proliferation, migration, invasion, and enhanced the apoptosis in glioma cells through regulating miR-218-5p/DEK/β-catenin axis.

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.

Benefit of Static FET PET in Pretreated Pediatric Brain Tumor Patients with Equivocal Conventional MRI Results

BACKGROUND

MRI has shortcomings in differentiation between tumor tissue and post-therapeutic changes in pretreated brain tumor patients.

PATIENTS

We assessed 22 static FET-PET/CT-scans of 17 pediatric patients (median age 12 years, range 2-16 years, ependymoma n=4, medulloblastoma n=4, low-grade glioma n=6, high-grade glioma n=3, germ cell tumor n=1, choroid plexus tumor n=1, median follow-up: 112 months) with multimodal treatment.

METHOD

FET-PET/CT-scans were analyzed visually by 3 independent nuclear medicine physicians. Additionally quantitative FET-Uptake for each lesion was determined by calculating standardized uptake values (SUVmaxT/SUVmeanB, SUVmeanT/SUVmeanB). Histology or clinical follow-up served as reference.

RESULTS

Static FET-PET/CT reliably distinguished between tumor tissue and post-therapeutic changes in 16 out of 17 patients. It identified correctly vital tumor tissue in 13 patients and post-therapeutic changes in 3 patients. SUV-based analyses were less sensitive than visual analyses. Except from a choroid plexus carcinoma, all tumor entities showed increased FET-uptake.

DISCUSSION

Our study comprises a limited number of patients but results corroborate the ability of FET to detect different brain tumor entities in pediatric patients and discriminate between residual/recurrent tumor and post-therapeutic changes.

CONCLUSIONS

We observed a clear benefit from additional static FET-PET/CT-scans when conventional MRI identified equivocal lesions in pretreated pediatric brain tumor patients. These results warrant prospective studies that should include dynamic scans.

Bevacizumab for radiation necrosis following radiotherapy of brain metastatic disease: a systematic review & meta-analysis

Background

Radiotherapy is the mainstay of brain metastasis (BM) management. Radiation necrosis (RN) is a serious complication of radiotherapy. Bevacizumab (BV), an anti-vascular endothelial growth factor monoclonal antibody, has been increasingly used for RN treatment. We systematically reviewed the medical literature for studies reporting the efficacy and safety of bevacizumab for treatment of RN in BM patients.

Materials and methods

PubMed, Medline, EMBASE, and Cochrane library were searched with various search keywords such as “bevacizumab” OR “anti-VEGF monoclonal antibody” AND “radiation necrosis” OR “radiation-induced brain necrosis” OR “RN” OR “RBN” AND “Brain metastases” OR “BM” until 1st Aug 2020. Studies reporting the efficacy and safety of BV treatment for BM patients with RN were retrieved. Study selection and data extraction were carried out by independent investigators. Open Meta Analyst software was used as a random effects model for meta-analysis to obtain mean reduction rates.

Results

Two prospective, seven retrospective, and three case report studies involving 89 patients with RN treated with BV were included in this systematic review and meta-analysis. In total, 83 (93%) patients had a recorded radiographic response to BV therapy, and six (6.7%) had experienced progressive disease. Seven studies (n = 73) reported mean volume reductions on gadolinium-enhanced T1 (mean: 47.03%, +/− 24.4) and T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI images (mean: 61.9%, +/− 23.3). Pooling together the T1 and T2 MRI reduction rates by random effects model revealed a mean of 48.58 (95% CI: 38.32–58.85) for T1 reduction rate and 62.017 (95% CI: 52.235–71.799) for T2W imaging studies. Eighty-five patients presented with neurological symptoms. After BV treatment, nine (10%) had stable symptoms, 39 (48%) had improved, and 34 (40%) patients had complete resolution of their symptoms. Individual patient data was available for 54 patients. Dexamethasone discontinuation or reduction in dosage was observed in 30 (97%) of 31 patients who had recorded dosage before and after BV treatment. Side effects were mild.

Conclusions

Bevacizumab presents a promising treatment strategy for patients with RN and brain metastatic disease. Radiographic response and clinical improvement was observed without any serious adverse events. Further class I evidence would be required to establish a bevacizumab recommendation in this group of patients.

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 recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation

The purpose of this study was to establish a high-performing radiomics strategy with machine learning from conventional and diffusion MRI to differentiate recurrent glioblastoma (GBM) from radiation necrosis (RN) after concurrent chemoradiotherapy (CCRT) or radiotherapy. Eighty-six patients with GBM were enrolled in the training set after they underwent CCRT or radiotherapy and presented with new or enlarging contrast enhancement within the radiation field on follow-up MRI. A diagnosis was established either pathologically or clinicoradiologically (63 recurrent GBM and 23 RN). Another 41 patients (23 recurrent GBM and 18 RN) from a different institution were enrolled in the test set. Conventional MRI sequences (T2-weighted and postcontrast T1-weighted images) and ADC were analyzed to extract 263 radiomic features. After feature selection, various machine learning models with oversampling methods were trained with combinations of MRI sequences and subsequently validated in the test set. In the independent test set, the model using ADC sequence showed the best diagnostic performance, with an AUC, accuracy, sensitivity, specificity of 0.80, 78%, 66.7%, and 87%, respectively. In conclusion, the radiomics models models using other MRI sequences showed AUCs ranging from 0.65 to 0.66 in the test set. The diffusion radiomics may be helpful in differentiating recurrent GBM from RN..

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.

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

Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.

Intracranial long-term complications of radiation therapy: an image-based review

BACKGROUND AND PURPOSE

Radiation therapy is commonly utilized in the majority of solid cancers and many hematologic malignancies and other disorders. While it has an undeniably major role in improving cancer survival, radiation therapy has long been recognized to have various negative effects, ranging from mild to severe. In this manuscript, we review several intracranial manifestations of therapeutic radiation, with particular attention to those that may be encountered by radiologists.

METHODS

We conducted an extensive literature review of known complications of intracranial radiation therapy. Based on this review, we selected complications that had salient, recognizable imaging findings. We searched our imaging database for illustrative examples of these complications, focusing only on patients who had a history of intracranial radiation therapy. We then selected cases that best exemplified expected imaging findings in these entities.

RESULTS

Based on our initial literature search and imaging database review, we selected cases of radiation-induced meningioma, radiation-induced glioma, cavernous malformation, enlarging perivascular spaces, leukoencephalopathy, stroke-like migraine after radiation therapy, Moyamoya syndrome, radiation necrosis, radiation-induced labyrinthitis, optic neuropathy, and retinopathy. Although retinopathy is not typically apparent on imaging, it has been included given its clinical overlap with optic neuropathy.

CONCLUSIONS

We describe the clinical and imaging features of selected sequelae of intracranial radiation therapy, with a focus on those most relevant to practicing radiologists. Knowledge of these complications and their imaging findings is important, because radiologists play a key role in early detection of these entities.

Frequency and Evolution of New Postoperative Enhancement on 3 Tesla Intraoperative and Early Postoperative Magnetic Resonance Imaging

BACKGROUND

Intraoperative magnetic resonance imaging (IO-MRI) provides real-time assessment of extent of resection of brain tumor. Development of new enhancement during IO-MRI can confound interpretation of residual enhancing tumor, although the incidence of this finding is unknown.

OBJECTIVE

To determine the frequency of new enhancement during brain tumor resection on intraoperative 3 Tesla (3T) MRI. To optimize the postoperative imaging window after brain tumor resection using 1.5 and 3T MRI.

METHODS

We retrospectively evaluated 64 IO-MRI performed for patients with enhancing brain lesions referred for biopsy or resection as well as a subset with an early postoperative MRI (EP-MRI) within 72 h of surgery (N = 42), and a subset with a late postoperative MRI (LP-MRI) performed between 120 h and 8 wk postsurgery (N = 34). Three radiologists assessed for new enhancement on IO-MRI, and change in enhancement on available EP-MRI and LP-MRI. Consensus was determined by majority response. Inter-rater agreement was assessed using percentage agreement.

RESULTS

A total of 10 out of 64 (16%) of the IO-MRI demonstrated new enhancement. Seven of 10 patients with available EP-MRI demonstrated decreased/resolved enhancement. One out of 42 (2%) of the EP-MRI demonstrated new enhancement, which decreased on LP-MRI. Agreement was 74% for the assessment of new enhancement on IO-MRI and 81% for the assessment of new enhancement on the EP-MRI.

CONCLUSION

New enhancement occurs in intraoperative 3T MRI in 16% of patients after brain tumor resection, which decreases or resolves on subsequent MRI within 72 h of surgery. Our findings indicate the opportunity for further study to optimize the postoperative imaging window.

FET PET Radiomics for Differentiating Pseudoprogression from Early Tumor Progression in Glioma Patients Post-Chemoradiation

Simple Summary

Following chemoradiation with alkylating agents in glioma patients, structural magnetic resonance imaging (MRI) may suggest tumor progression which subsequently improves during the course of the disease without any treatment change. This phenomenon has been termed pseudoprogression. Despite advances in medical imaging, a reliable diagnosis of pseudoprogression remains a challenging task. Radiomics is a subdiscipline of artificial intelligence and allows the identification and extraction of imaging features from various routine imaging modalities. These features can be used for the generation of mathematical models to improve diagnostics in patients with brain tumors. The present study highlights the potential of radiomics obtained from amino acid positron emission tomography (PET) for the diagnosis of pseudoprogression. In 34 patients with suspicious MRI early after chemoradiation completion, our radiomics model correctly identified all patients with pseudoprogression.

Abstract

Currently, a reliable diagnostic test for differentiating pseudoprogression from early tumor progression is lacking. We explored the potential of O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) radiomics for this clinically important task. Thirty-four patients (isocitrate dehydrogenase (IDH)-wildtype glioblastoma, 94%) with progressive magnetic resonance imaging (MRI) changes according to the Response Assessment in Neuro-Oncology (RANO) criteria within the first 12 weeks after completing temozolomide chemoradiation underwent a dynamic FET PET scan. Static and dynamic FET PET parameters were calculated. For radiomics analysis, the number of datasets was increased to 102 using data augmentation. After randomly assigning patients to a training and test dataset, 944 features were calculated on unfiltered and filtered images. The number of features for model generation was limited to four to avoid data overfitting. Eighteen patients were diagnosed with early tumor progression, and 16 patients had pseudoprogression. The FET PET radiomics model correctly diagnosed pseudoprogression in all test cohort patients (sensitivity, 100%; negative predictive value, 100%). In contrast, the diagnostic performance of the best FET PET parameter (TBR_max) was lower (sensitivity, 81%; negative predictive value, 80%). The results suggest that FET PET radiomics helps diagnose patients with pseudoprogression with a high diagnostic performance. Given the clinical significance, further studies are warranted.

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.

Management and Surveillance of Short- and Long-Term Sequelae of Radiation Therapy for the Treatment of Pediatric Brain Tumors

Radiation therapy (RT) is a mainstay for the treatment of pediatric brain tumors. As improvements in and sophistication of this modality continue to increase the survival of patients, the long-term sequelae of RT pose significant challenges in the clinical management of this patient population as they transition into adulthood. In this special edition, we review the short- and long-term effects of RT for the treatment of pediatric brain tumors and the necessary surveillance required for follow-up.

Recognizing Radiation-induced Changes in the Central Nervous System: Where to Look and What to Look For

Radiation therapy (RT) continues to play a central role as an effective therapeutic modality for a variety of tumors and vascular malformations in the central nervous system. Although the planning and delivery techniques of RT have evolved substantially during the past few decades, the structures surrounding the target lesion are inevitably exposed to radiation. A wide variety of radiation-induced changes may be observed at posttreatment imaging, which may be confusing when interpreting images. Histopathologically, radiation can have deleterious effects on the vascular endothelial cells as well as on neuroglial cells and their precursors. In addition, radiation induces oxidative stress and inflammation, leading to a cycle of further cellular toxic effects and tissue damage. On the basis of the time of expression, radiation-induced injury can be divided into three phases: acute, early delayed, and late delayed. Acute and early delayed injuries are usually transient and reversible, whereas late delayed injuries are generally irreversible. The authors provide a comprehensive review of the timeline and expected imaging appearances after RT, including the characteristic imaging features after RT with concomitant chemotherapy. Specific topics discussed are imaging features that help distinguish expected posttreatment changes from recurrent disease, followed by a discussion on the role of advanced imaging techniques. Knowledge of the RT plan, the amount of normal structures included, the location of the target lesion, and the amount of time elapsed since RT is highly important at follow-up imaging, and the reporting radiologist should be able to recognize the characteristic imaging features after RT and differentiate these findings from tumor recurrence. ^©RSNA, 2020.

Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation

BACKGROUND

The radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients.

OBJECTIVE

This research aims to develop a deep learning methodology for automated differentiation of tumor recurrence from radiation necrosis based on routine magnetic resonance imaging (MRI) scans.

METHODS

In this retrospective study, 146 patients who underwent radiation therapy after glioma resection and presented with suspected recurrent lesions at the follow-up MRI examination were selected for analysis. Routine MRI scans were acquired from each patient, including T1, T2, and gadolinium-contrast-enhanced T1 sequences. Of those cases, 96 (65.8%) were confirmed as glioma recurrence on postsurgical pathological examination, while 50 (34.2%) were diagnosed as necrosis. A light-weighted deep neural network (DNN) (ie, efficient radionecrosis neural network [ERN-Net]) was proposed to learn radiological features of gliomas and necrosis from MRI scans. Sensitivity, specificity, accuracy, and area under the curve (AUC) were used to evaluate performance of the model in both image-wise and subject-wise classifications. Preoperative diagnostic performance of the model was also compared to that of the state-of-the-art DNN models and five experienced neurosurgeons.

RESULTS

DNN models based on multimodal MRI outperformed single-modal models. ERN-Net achieved the highest AUC in both image-wise (0.915) and subject-wise (0.958) classification tasks. The evaluated DNN models achieved an average sensitivity of 0.947 (SD 0.033), specificity of 0.817 (SD 0.075), and accuracy of 0.903 (SD 0.026), which were significantly better than the tested neurosurgeons (P=.02 in sensitivity and P<.001 in specificity and accuracy).

CONCLUSIONS

Deep learning offers a useful computational tool for the differential diagnosis between recurrent gliomas and necrosis. The proposed ERN-Net model, a simple and effective DNN model, achieved excellent performance on routine MRI scans and showed a high clinical applicability.

Treatment-induced brain tissue necrosis: a clinical challenge in neuro-oncology

Cancer therapy-induced adverse effects on the brain are a major challenge in neuro-oncology. Brain tissue necrosis (treatment necrosis [TN]) as a consequence of brain directed cancer therapy remains an insufficiently characterized condition with diagnostic and therapeutic difficulties and is frequently associated with significant patient morbidity. A better understanding of the underlying mechanisms, improvement of diagnostic tools, development of preventive strategies, and implementation of evidence-based therapeutic practices are pivotal to improve patient management. In this comprehensive review, we address existing challenges associated with current TN-related clinical and research practices and highlight unanswered questions and areas in need of further research with the ultimate goal to improve management of patients affected by this important neuro-oncological condition.

Subtraction Maps Derived from Longitudinal Magnetic Resonance Imaging in Patients with Glioma Facilitate Early Detection of Tumor Progression

Progression of glioma is frequently characterized by increases or enhanced spread of a hyperintensity in fluid attenuated inversion recovery (FLAIR) sequences. However, changes in FLAIR signal over time can be subtle, and conventional (CONV) visual reading is time-consuming. The purpose of this monocentric, retrospective study was to compare CONV reading to reading of subtraction maps (SMs) for serial FLAIR imaging. FLAIR datasets of cranial 3-Tesla magnetic resonance imaging (MRI), acquired at two different time points (mean inter-scan interval: 5.4 ± 1.9 months), were considered per patient in a consecutive series of 100 patients (mean age: 49.0 ± 13.7 years) diagnosed with glioma (19 glioma World Health Organization [WHO] grade I and II, 81 glioma WHO grade III and IV). Two readers (R1 and R2) performed CONV and SM reading by assessing overall image quality and artifacts, alterations in tumor-associated FLAIR signal over time (stable/unchanged or progressive) including diagnostic confidence (1-very high to 5-very low diagnostic confidence), and time needed for reading. Gold-standard (GS) reading, including all available clinical and imaging information, was performed by a senior reader, revealing progressive FLAIR signal in 61 patients (tumor progression or recurrence in 38 patients, pseudoprogression in 10 patients, and unclear in the remaining 13 patients). SM reading used an officially certified and commercially available algorithm performing semi-automatic coregistration, intensity normalization, and color-coding to generate individual SMs. The approach of SM reading revealed FLAIR signal increases in a larger proportion of patients according to evaluations of both readers (R1: 61 patients/R2: 60 patients identified with FLAIR signal increase vs. R1: 45 patients/R2: 44 patients for CONV reading) with significantly higher diagnostic confidence (R1: 1.29 ± 0.48, R2: 1.26 ± 0.44 vs. R1: 1.73 ± 0.80, R2: 1.82 ± 0.85; p < 0.0001). This resulted in increased sensitivity (99.9% vs. 73.3%) with maintained high specificity (98.1% vs. 98.8%) for SM reading when compared to CONV reading. Furthermore, the time needed for SM reading was significantly lower compared to CONV assessments (p < 0.0001). In conclusion, SM reading may improve diagnostic accuracy and sensitivity while reducing reading time, thus potentially enabling earlier detection of disease progression.

Metabolic Imaging of Brain Tumor Recurrence

OBJECTIVE. Diagnosing brain tumor recurrence, especially with changes that occur after treatment, is a challenge. MRI has an exceptional structural resolution, which is important from the perspective of treatment planning. However, its reliability in diagnosing recurrence is relatively lower, when compared to metabolic imaging. The latter is more sensitive to the early changes associated with recurrence and relatively immune to confounding by treatment related changes. CONCLUSION. There is no one-stop shop for the diagnosis of recurrence in brain tumors. The sensitivity of metabolic imaging is not a substitute for the resolution of the MRI, making a multi-modal approach the only way forward.

A preliminary study on the application of DTI in the treatment of brain tumors in motor function areas with gamma knife

OBJECTIVES

The treatment safety and efficiency as well as the life quality of patients are still main concerns in gamma knife radiosurgery. In this study, the feasibility of applying diffusion tensor imaging (DTI) in gamma knife radiosurgery for the treatment of brain tumor in motor function areas was investigated, which aims to provide protection on the pyramidal tract and preserve the motor function in patients.

PATIENTS AND METHODS

Total 74 patients with solid brain tumor were enrolled and divided into DTI group and control group. The tumor control rate was assessed at 3 months after surgery. The muscle strength of affected limb, KPS scores, ZEW scores and complications were evaluated at 3 and 6 months after gamma knife radiosurgery.

RESULTS

Our results indicated that the tumor control rate, complication rate, the muscle strength of affected limb and KPS scores were not significantly different between the two groups at 3 months after surgery. At 6 months after gamma knife radiosurgery, the complication rate (0% vs 50 %, P = 0.044), KPS scores (64.9 % vs 37.8 %, P = 0.036) and ZEW scores (78.4 % vs 54.1 %, P = 0.044) of DTI group were better than the control group. Furthermore, the stability of muscle strength in patients with limb dysfunction was significantly improved in DTI group (86.4 % vs 50 %, P = 0.028).

CONCLUSION

In summary, the application of DTI in gamma knife radiosurgery for the treatment of brain tumors in motor function areas can precisely define the tumor edge from pyramidal tract, which will support on designing individual treatment plan, reducing the incidence of complications, and improving long-term life quality in patients.

PET imaging in patients with brain metastasis-report of the RANO/PET group

Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortality. Effective local treatment options are stereotactic radiotherapy, including radiosurgery or fractionated external beam radiotherapy, and surgical resection. The use of systemic treatment for intracranial disease control also is improving. BM diagnosis, treatment planning, and follow-up is most often based on contrast-enhanced magnetic resonance imaging (MRI). However, anatomic imaging modalities including standard MRI have limitations in accurately characterizing posttherapeutic reactive changes and treatment response. Molecular imaging techniques such as positron emission tomography (PET) characterize specific metabolic and cellular features of metastases, potentially providing clinically relevant information supplementing anatomic MRI. Here, the Response Assessment in Neuro-Oncology working group provides recommendations for the use of PET imaging in the clinical management of patients with BM based on evidence from studies validated by histology and/or clinical outcome.

A Radiomics Model for Predicting the Response to Bevacizumab in Brain Necrosis after Radiotherapy

PURPOSE

Bevacizumab is considered a promising therapy for brain necrosis after radiotherapy, while some patients fail to derive benefit or even worsen. Hence, we developed and validated a radiomics model for predicting the response to bevacizumab in patients with brain necrosis after radiotherapy.

EXPERIMENTAL DESIGN

A total of 149 patients (with 194 brain lesions; 101, 51, and 42 in the training, internal, and external validation sets, respectively) receiving bevacizumab were enrolled. In total, 1,301 radiomic features were extracted from the pretreatment MRI images of each lesion. In the training set, a radiomics signature was constructed using the least absolute shrinkage and selection operator algorithm. Multivariable logistic regression analysis was then used to develop a radiomics model incorporated in the radiomics signature and independent clinical predictors. The performance of the model was assessed by its discrimination, calibration, and clinical usefulness with internal and external validation.

RESULTS

The radiomics signature consisted of 18 selected features and showed good discrimination performance. The model, which integrates the radiomics signature, the interval between radiotherapy and diagnosis of brain necrosis, and the interval between diagnosis of brain necrosis and treatment with bevacizumab, showed favorable calibration and discrimination in the training set (AUC 0.916). These findings were confirmed in the validation sets (AUC 0.912 and 0.827, respectively). Decision curve analysis confirmed the clinical utility of the model.

CONCLUSIONS

The presented radiomics model, available as an online calculator, can serve as a user-friendly tool for individualized prediction of the response to bevacizumab in patients with brain necrosis after radiotherapy.

Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology

PURPOSE

Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical planning, and treatment evaluation remains an unmet need in the clinical management of GBMs.

EXPERIMENTAL DESIGN

We employ a novel diffusion histology imaging (DHI) approach, combining diffusion basis spectrum imaging (DBSI) and machine learning, to detect, differentiate, and quantify areas of high cellularity, tumor necrosis, and tumor infiltration in GBM.

RESULTS

Gadolinium-enhanced T1-weighted or hyperintense fluid-attenuated inversion recovery failed to reflect the morphologic complexity underlying tumor in patients with GBM. Contrary to the conventional wisdom that apparent diffusion coefficient (ADC) negatively correlates with increased tumor cellularity, we demonstrate disagreement between ADC and histologically confirmed tumor cellularity in GBM specimens, whereas DBSI-derived restricted isotropic diffusion fraction positively correlated with tumor cellularity in the same specimens. By incorporating DBSI metrics as classifiers for a supervised machine learning algorithm, we accurately predicted high tumor cellularity, tumor necrosis, and tumor infiltration with 87.5%, 89.0%, and 93.4% accuracy, respectively.

CONCLUSIONS

Our results suggest that DHI could serve as a favorable alternative to current neuroimaging techniques in guiding biopsy or surgery as well as monitoring therapeutic response in the treatment of GBM.

Biomarkers of Brain Damage Induced by Radiotherapy

Radiotherapy remains currently a critical component for both primary and metastatic brain tumors either alone or in combination with surgery, chemotherapy, and molecularly targeted agents, while it could cause simultaneously normal brain tissue injury leading to serious health consequences, that is, development of cognitive impairments following cranial radiotherapy is considered as a critical clinical disadvantage especially for the whole brain radiotherapy. Biomarkers can help to detect the accurate physiology or conditions of patients with brain tumor and develop effective treatment procedures for these patients. In the near future, biomarkers will become one of the prime driving forces of cancer treatment. In this minireview, we analyze the documented work on the acute brain damage and late consequences induced by radiotherapy, identify the biomarkers, in particular, the predictive biomarkers for the damage, and summarize the biological significance of the biomarkers. It is expected that translation of these research advance to radiotherapy would assist stratifying patients for optimized treatment and improving therapeutic efficacy and the quality of life.

Defining Treatment-Related Adverse Effects in Patients with Glioma: Distinctive Features of Pseudoprogression and Treatment-Induced Necrosis

Background

Pseudoprogression (PP) and treatment‐induced brain tissue necrosis (TN) are challenging cancer treatment–related effects. Both phenomena remain insufficiently defined; differentiation from recurrent disease frequently necessitates tissue biopsy. We here characterize distinctive features of PP and TN to facilitate noninvasive diagnosis and clinical management.

Materials and Methods

Patients with glioma and confirmed PP (defined as appearance <5 months after radiotherapy [RT] completion) or TN (>5 months after RT) were retrospectively compared using clinical, radiographic, and histopathological data. Each imaging event/lesion (region of interest [ROI]) diagnosed as PP or TN was longitudinally evaluated by serial imaging.

Results

We identified 64 cases of mostly (80%) biopsy‐confirmed PP (n = 27) and TN (n = 37), comprising 137 ROIs in total. Median time of onset for PP and TN was 1 and 11 months after RT, respectively. Clinically, PP occurred more frequently during active antineoplastic treatment, necessitated more steroid‐based interventions, and was associated with glioblastoma (81 vs. 40%), fewer IDH1 mutations, and shorter median overall survival. Radiographically, TN lesions often initially manifested periventricularly (n = 22/37; 60%), were more numerous (median, 2 vs. 1 ROIs), and contained fewer malignant elements upon biopsy. By contrast, PP predominantly developed around the tumor resection cavity as a non‐nodular, ring‐like enhancing structure. Both PP and TN lesions almost exclusively developed in the main prior radiation field. Presence of either condition appeared to be associated with above‐average overall survival.

Conclusion

PP and TN occur in clinically distinct patient populations and exhibit differences in spatial radiographic pattern. Increased familiarity with both conditions and their unique features will improve patient management and may avoid unnecessary surgical procedures.

Implications for Practice

Pseudoprogression (PP) and treatment‐induced brain tissue necrosis (TN) are challenging treatment‐related effects mimicking tumor progression in patients with brain cancer. Affected patients frequently require surgery to guide management. PP and TN remain arbitrarily defined and insufficiently characterized. Lack of clear diagnostic criteria compromises treatment and may adversely affect outcome interpretation in clinical trials. The present findings in a cohort of patients with glioma with PP/TN suggest that both phenomena exhibit unique clinical and imaging characteristics, manifest in different patient populations, and should be classified as distinct clinical conditions. Increased familiarity with PP and TN key features may guide clinicians toward timely noninvasive diagnosis, circumvent potentially unnecessary surgical procedures, and improve response assessment in neuro‐oncology.

Cancer treatment–related adverse effects on the brain are a major diagnostic and therapeutic challenge in neuro‐oncology. This article describes the key clinical and imaging features of pseudoprogression and treatment‐induced brain tissue necrosis in patients with malignant glioma in an attempt to improve the current understanding of these conditions, facilitate the noninvasive diagnosis of treatment‐related adverse effects, and improve response assessment in neuro‐oncology.

Laser Interstitial Thermal Therapy in the treatment of brain metastases and radiation necrosis

Stereotactic Radiosurgery has become the main treatment for patients with limited number of brain metastases (BM). Recently, with the increasing use of this modality, there is a growth in recurrence cases. Recurrence after radiation therapy can be divided in changes favoring either tumor recurrence or radiation necrosis (RN). Laser Interstitial Thermal Therapy (LITT) is minimally invasive treatment modality that has been used to treat primary and metastatic brain tumors. When associated with real-time thermometry using Magnetic Resonance Imaging, the extent of ablation can be controlled to provide maximum coverage and avoid eloquent areas. The objective of this study was to investigate the use of LITT in the treatment of BM. An extensive review of the relevant literature was conducted and the outcome results are discussed. There is an emphasis on safety and local control rate of patients treated with this modality. The findings of our study suggest that LITT is a viable safe technique to treat recurrent BM, especially in patients with deep-seated lesions where surgical resection is not an option.

Impact of mouse strain and sex when modeling radiation necrosis

Background

Murine models are among the most common type of preclinical animal models used to study the human condition, but a wide selection of different mice is currently in use with these differences potentially compromising study results and impairing the ability to reconcile interstudy results. Our goal was to determine how the strain and sex of the mice selection would affect the development of radiation necrosis in our murine model of radiation-induced cerebral necrosis.

Methods

We generated this model by using a preclinical irradiator to irradiate a sub-hemispheric portion of the brain of mice with single-fraction doses of 80 Gy. Eight possible combinations of mice made up of two different with two substrains each (BALB/cN, BALB/cJ, C57BL/6 N, and C57BL/6 J) and both sexes were irradiated in this study. Radiation necrosis development was tracked up to 8 weeks with a 7 T Bruker MRI utilizing T2-weighted and post-contrast T1-weighted imaging. MRI results were compared to and validated with the use of histology which utilized a scale from 0 to 3 in ascending order of damage.

Results

Both time post-irradiation and strain (BALB/c vs C57BL/6) were significant factors affecting radiation necrosis development. Sex was in general not a statistically significant parameter in terms of radiation necrosis development.

Conclusion

Mouse strain thus needs to be considered when evaluating the results of necrosis models. However, sex does not appear to be a variable needing major consideration.

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.

Late Contrast Enhancing Brain Lesions in Proton-Treated Patients With Low-Grade Glioma: Clinical Evidence for Increased Periventricular Sensitivity and Variable RBE

PURPOSE

Late radiation-induced contrast-enhancing brain lesions (CEBLs) on magnetic resonance imaging (MRI) after proton therapy of brain tumors have been observed to occur frequently in regions of high linear energy transfer (LET) and in proximity to the ventricular system. We analyzed 110 patients with low-grade glioma treated with proton therapy to determine whether the risk for CEBLs is increased in proximity to the ventricular system and if there is a relationship between relative biological effectiveness (RBE) and LET.

METHODS AND MATERIALS

We contoured CEBLs identified on follow-up T1-MRI scans and computed dose and dose-averaged LET (LET_d) distributions for all patients using the Monte Carlo method. We then performed cross-validated voxel-level logistic regression to predict local risks for image change and to extract model parameters, such as the RBE. From the voxel-level model, we derived a model for patient-level risk prediction based on the treatment plan.

RESULTS

Of 110 patients, 23 exhibited 1 or several CEBLs on follow-up MRI scans. The voxel-level logistic model has an accuracy as follows: area under the curve of 0.94 and Brier score of 2.6 × 10^-5. Model predictions are a 3-fold increased risk in the 4 mm region around the ventricular system and an LET_d-dependent RBE of, for example, 1.20 for LET_d = 2 keV/μm and 1.50 for LET_d = 5 keV/μm. The patient-level risk model has an accuracy as follows: area under the curve of 0.78 and Brier score of 0.13.

CONCLUSIONS

Our findings present clinical evidence for an increased risk in ventricular proximity and for a proton RBE that increases significantly with increasing LET. We present a voxel-level model that accurately predicts the localization of late MRI contrast change and extrapolate a patient-level model that allows treatment plan-based risk prediction.

Current Landscape and Emerging Fields of PET Imaging in Patients with Brain Tumors

The number of positron-emission tomography (PET) tracers used to evaluate patients with brain tumors has increased substantially over the last years. For the management of patients with brain tumors, the most important indications are the delineation of tumor extent (e.g., for planning of resection or radiotherapy), the assessment of treatment response to systemic treatment options such as alkylating chemotherapy, and the differentiation of treatment-related changes (e.g., pseudoprogression or radiation necrosis) from tumor progression. Furthermore, newer PET imaging approaches aim to address the need for noninvasive assessment of tumoral immune cell infiltration and response to immunotherapies (e.g., T-cell imaging). This review summarizes the clinical value of the landscape of tracers that have been used in recent years for the above-mentioned indications and also provides an overview of promising newer tracers for this group of patients.

The impact of extended adjuvant temozolomide in newly diagnosed glioblastoma multiforme: a meta-analysis and systematic review

Surgical resection followed by concurrent radiation therapy and temozolomide (TMZ) chemotherapy is the current standard treatment for glioblastoma multiforme (GBM). The present metaanalysis investigated the impact of prolonged TMZ maintenance therapy (more than 6 cycles) in comparison with standard TMZ maintenance therapy (exactly six cycles) on overall survival (OS) and progression-free survival (PFS) of patients with GBM. A meta-analysis of the literature was conducted using Medline, PubMed, EMBASE and the Cochrane Library in accordance with PRISMA guidelines. Seven articles involving 1018 patients were included. The overall survival was higher in the case group (>6 cycles TMZ) compared to the control group (6 cycles TMZ) (Z=2.375, P=0.018). The lower and upper limits were between 1.002-10.467 months. The case group had higher progression-free survival compared with the control group (Z=3.84; P<0.001). The lower and upper limits were between 2.559-7.894 months. Evidence from this meta-analysis suggests that prolonged TMZ therapy compared to the standard 6-cycle TMZ therapy was associated with higher survival in patients with glioblastoma.

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

The Response Assessment in Neuro-Oncology criteria were developed as an objective tool for radiologic assessment of treatment response in high-grade gliomas. Imaging plays a critical role in the management of the patient with glioma, from initial diagnosis to posttreatment follow-up, which can be particularly challenging for radiologists. Interpreting findings after surgery, radiation, and chemotherapy requires profound knowledge about the tumor biology, as well as the peculiar changes expected to ensue as a consequence of each treatment technique. In this article, we discuss the imaging findings associated with tumor progression, tumor response, pseudoprogression, and pseudoresponse according to the Response Assessment in Neuro-Oncology criteria for high-grade and lower-grade gliomas. We describe relevant practical issues when evaluating patients with glioma, such as the need for imaging in the first 48 hours, the radiation therapy planning and isodose curves, the significance of T2/FLAIR hyperintense lesions, the impact of the timing for the evaluation after radiation therapy, and the definition of progressive disease on the histologic specimen. We also illustrate the correlation among the findings on conventional MR imaging with advanced techniques, such as perfusion, diffusion-weighted imaging, spectroscopy, and amino acid PET. Because many of the new lesions represent a mixture of tumor cells and tissue with radiation injury, the radiologist aims to identify the predominant component of the lesion and categorize the findings according to Response Assessment in Neuro-Oncology criteria so that the patient can receive the best treatment.

Molecular imaging and advanced MRI findings following immunotherapy in patients with brain tumors

Introduction: Currently, immunotherapy using vaccination strategies or oncolytic virus approaches, cell-based immunotherapy, and the blockade of immune checkpoints are under evaluation in patients with brain cancer. Here we summarize clinically significant imaging findings such as treatment-related changes detected by advanced neuroimaging techniques following the most suitable immunotherapy options currently used in neuro-oncology. We, furthermore, provide an overview of how these advanced imaging techniques may help to overcome shortcomings of standard MRI in the assessment and follow-up of patients with brain cancer.Areas covered: The current literature on neuroimaging for immunotherapy in the field of brain tumors, with a focus on gliomas and brain metastases is summarized.Expert commentary: Data suggest that imaging parameters primarily derived from amino acid PET, diffusion- and perfusion-weighted MRI, or MR spectroscopy are particularly helpful for the evaluation of treatment response and provide valuable information for the differentiation of treatment-induced changes from actual brain tumor progression following various immunotherapy approaches.