Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas

PET Imaging in Neuro-Oncology: An Update and Overview of a Rapidly Growing Area

Simple Summary

Positron emission tomography (PET) is a functional imaging technique which plays an increasingly important role in the management of brain tumors. Owing different radiotracers, PET allows to image different metabolic aspects of the brain tumors. This review outlines currently available PET radiotracers and their respective indications in neuro-oncology. It specifically focuses on the investigation of gliomas, meningiomas, primary central nervous system lymphomas as well as brain metastases. Recent advances in the production of PET radiotracers, image analyses and translational applications to peptide radionuclide receptor therapy, which allow to treat brain tumors with radiotracers, are also discussed. The objective of this review is to provide a comprehensive overview of PET imaging’s potential in neuro-oncology as an adjunct to brain magnetic resonance imaging (MRI).

Abstract

PET plays an increasingly important role in the management of brain tumors. This review outlines currently available PET radiotracers and their respective indications. It specifically focuses on ¹⁸F-FDG, amino acid and somatostatin receptor radiotracers, for imaging gliomas, meningiomas, primary central nervous system lymphomas as well as brain metastases. Recent advances in radiopharmaceuticals, image analyses and translational applications to therapy are also discussed. The objective of this review is to provide a comprehensive overview of PET imaging’s potential in neuro-oncology as an adjunct to brain MRI for all medical professionals implicated in brain tumor diagnosis and care.

A Radiologist's Perspective on Treatment-Related Pseudoprogression: Clues and Hues

Pseudoprogression refers to the initial apparent increase in tumor burden observed on imaging after cancer therapy, with subsequent delayed response to the same treatment, thus giving a false initial appearance of disease progression. It is essential to differentiate pseudoprogression from true progression to prevent the patients from getting deprived of the benefits of their ongoing cancer therapy owing to their early withdrawal. It also affects their recruitment for clinical trials. Pseudoprogression, albeit uncommon, has been observed after various types of cancer therapy; however, this phenomenon has gained momentum of late due to the emergence of immunotherapy for the treatment of various malignancies. Besides immunotherapy, pseudoprogression has predominantly been of concern in a few patients after radiation therapy for brain tumors and metastasis, after molecular targeted therapy for a variety of tumors, and after chemotherapy in metastatic bone lesions. This article reviews the available data on imaging of pseudoprogression from various types of cancer therapies, highlighting ways to suspect or identify it on imaging.

The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T

Background. With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). Methods. Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). Results. Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). Conclusions. This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors.

In vivo imaging of nanoparticle-labeled CAR T cells

Metastatic osteosarcoma has a poor prognosis with a 2-y, event-free survival rate of ∼15 to 20%, highlighting the need for the advancement of efficacious therapeutics. Chimeric antigen receptor (CAR) T-cell therapy is a potent strategy for eliminating tumors by harnessing the immune system. However, clinical trials with CAR T cells in solid tumors have encountered significant challenges and have not yet demonstrated convincing evidence of efficacy for a large number of patients. A major bottleneck for the success of CAR T-cell therapy is our inability to monitor the accumulation of the CAR T cells in the tumor with clinical-imaging techniques. To address this, we developed a clinically translatable approach for labeling CAR T cells with iron oxide nanoparticles, which enabled the noninvasive detection of the iron-labeled T cells with magnetic resonance imaging (MRI), photoacoustic imaging (PAT), and magnetic particle imaging (MPI). Using a custom-made microfluidics device for T-cell labeling by mechanoporation, we achieved significant nanoparticle uptake in the CAR T cells, while preserving T-cell proliferation, viability, and function. Multimodal MRI, PAT, and MPI demonstrated homing of the T cells to osteosarcomas and off-target sites in animals administered with T cells labeled with the iron oxide nanoparticles, while T cells were not visualized in animals infused with unlabeled cells. This study details the successful labeling of CAR T cells with ferumoxytol, thereby paving the way for monitoring CAR T cells in solid tumors.

Treatment Response and Prognosis Evaluation in High-Grade Glioma: An Imaging Review Based on MRI

In recent years, the development of advanced magnetic resonance imaging (MRI) technology and machine learning (ML) have created new tools for evaluating treatment response and prognosis of patients with high-grade gliomas (HGG); however, patient prognosis has not improved significantly. This is mainly due to the heterogeneity between and within HGG tumors, resulting in standard treatment methods not benefitting all patients. Moreover, the survival of patients with HGG is not only related to tumor cells, but also to noncancer cells in the tumor microenvironment (TME). Therefore, during preoperative diagnosis and follow-up treatment of patients with HGG, noninvasive imaging markers are needed to characterize intratumoral heterogeneity, and then to evaluate treatment response and predict prognosis, timeously adjust treatment strategies, and achieve individualized diagnosis and treatment. In this review, we summarize the research progress of conventional MRI, advanced MRI technology, and ML in evaluation of treatment response and prognosis of patients with HGG. We further discuss the significance of the TME in the prognosis of HGG patients, associate imaging features with the TME, indirectly reflecting the heterogeneity within the tumor, and shifting treatment strategies from tumor cells alone to systemic therapy of the TME, which may be a major development direction in the future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 4.

Follow-Up of High-Grade Glial Tumor; Differentiation of Posttreatment Enhancement and Tumoral Enhancement by DCE-MR Perfusion

Purpose

To search for the utility of DCE-MRP to differentiate between posttreatment enhancement (PT) and tumoral enhancement (TM) in high-grade glial tumors.

Materials and Methods

Thirty-four patients with glioma (11 grade 3; 23 grade 4) were enrolled. Enhancement in the vicinity of the resection cavity demonstrated by DCE-MRP was taken into consideration. Based on the follow-up scans, reoperation or biopsy results, the enhancement type was categorized as PT or TM. Measurements were performed at the enhancing area near the resection cavity (ERC), nearby (NNA) and contralateral nonenhancing areas (CLNA). Perfusion parameters of the ERC were also subtracted from NNA and CLNA. Intragroup comparison (paired sample t-test) and intergroup comparison (Student's t-test) were made.

Results

There were 7 PTs and 27 TMs. In the PT, the subtracted values of Ve and IAUC from the CLNA and NNA and the subtracted value of Kep from NNA were statistically different. In TM, all metrics were significantly different comparing the CLNA and NNA. Comparing PT with TM, Ktrans, IAUC, Kep, and subtracted values of Ktrans and IAUC from both NNA and CLNA were significantly different.

Conclusions

In PT, only Ktrans values did not reveal any difference comparing NNA and CLNA. To differentiate PT from TM, Ktrans, Kep, IAUC, and subtracted values of Ktrans and IAUC from NNA and CLNA can be used. These findings are in concordance with literature.

Current Understanding of Exosomal MicroRNAs in Glioma Immune Regulation and Therapeutic Responses

Exosomes, the small extracellular vesicles, are released by multiple cell types, including tumor cells, and represent a novel avenue for intercellular communication via transferring diverse biomolecules. Recently, microRNAs (miRNAs) were demonstrated to be enclosed in exosomes and therefore was protected from degradation. Such exosomal miRNAs can be transmitted to recipient cells where they could regulate multiple cancer-associated biological processes. Accumulative evidence suggests that exosomal miRNAs serve essential roles in modifying the glioma immune microenvironment and potentially affecting the malignant behaviors and therapeutic responses. As exosomal miRNAs are detectable in almost all kinds of biofluids and correlated with clinicopathological characteristics of glioma, they might be served as promising biomarkers for gliomas. We reviewed the novel findings regarding the biological functions of exosomal miRNAs during glioma pathogenesis and immune regulation. Furthermore, we elaborated on their potential clinical applications as biomarkers in glioma diagnosis, prognosis and treatment response prediction. Finally, we summarized the accessible databases that can be employed for exosome-associated miRNAs identification and functional exploration of cancers, including glioma.

Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

OBJECTIVE

Monitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies.

METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018-01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965).

RESULTS

Eighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC.

CONCLUSION

ML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.

Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review

Background: Glioblastoma is the most frequent malignant primitive brain tumor in adults. The treatment includes surgery, radiotherapy, and chemotherapy. During follow-up, combined chemoradiotherapy can induce treatment-related changes mimicking tumor progression on medical imaging, such as pseudoprogression (PsP). Differentiating PsP from true progression (TP) remains a challenge for radiologists and oncologists, who need to promptly start a second-line treatment in the case of TP. Advanced magnetic resonance imaging (MRI) techniques such as diffusion-weighted imaging, perfusion MRI, and proton magnetic resonance spectroscopic imaging are more efficient than conventional MRI in differentiating PsP from TP. None of these techniques are fully effective, but current advances in computer science and the advent of artificial intelligence are opening up new possibilities in the imaging field with radiomics (i.e., extraction of a large number of quantitative MRI features describing tumor density, texture, and geometry). These features are used to build predictive models for diagnosis, prognosis, and therapeutic response. Method: Out of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, we screened 574 papers. A total of 228 were eligible, and we analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis.

Radiotherapy for glioblastoma: clinical issues and nanotechnology strategies

Glioblastoma multiforme (GBM) is the most common primary brain cancer in adults with poor prognosis. Despite the current state of knowledge on its genetic characteristics, relatively little progress has been made in improving the treatment of patients with this fatal disease. Radiotherapy (RT) has been identified as a crucial treatment for GBM following surgical resection to improve both local control and survival. Unfortunately, radiotherapy resistance is frequently observed in GBM patients, which is the major reason for the high mortality rate of cancer patients. Radioresistance of GBM is often multifactorial and heterogeneous, and associated with the recurrence of GBM after surgery. Nanotechnology has gained increasing attention and has already been investigated for optimization of radiosensitization due to the unique properties of nanobiomaterials, such as photoelectric decay characteristics or potential as carriers for drug delivery to the central nervous system. A large body of preclinical data has accumulated over the past several years, in which nanotechnology-based strategies exhibit promising potential to enhance the radiosensitivity of GBM, both in cellular and animal models. In this review, we summarize the mechanisms of GBM radioresistance, including tumor cell-intrinsic factors as well as tumor microenvironment (TME). We further discuss current nano-biotechnology-based radiosensitizer in the treatment of GBM, summarize the latest findings, highlight challenges, and put forward prospects for the future of nano-radiosensitizers. These data suggest that nanotechnology has the potential to address many of the clinical challenges and nanobiomaterials would become promising next-generation radiotherapy sensitizers for GBM treatment.

Repurposing ferumoxytol: Diagnostic and therapeutic applications of an FDA-approved nanoparticle

Ferumoxytol is an intravenous iron oxide nanoparticle formulation that has been approved by the U.S. Food and Drug Administration (FDA) for treating anemia in patients with chronic kidney disease. In recent years, ferumoxytol has also been demonstrated to have potential for many additional biomedical applications due to its excellent inherent physical properties, such as superparamagnetism, biocatalytic activity, and immunomodulatory behavior. With good safety and clearance profiles, ferumoxytol has been extensively utilized in both preclinical and clinical studies. Here, we first introduce the medical needs and the value of current iron oxide nanoparticle formulations in the market. We then focus on ferumoxytol nanoparticles and their physicochemical, diagnostic, and therapeutic properties. We include examples describing their use in various biomedical applications, including magnetic resonance imaging (MRI), multimodality imaging, iron deficiency treatment, immunotherapy, microbial biofilm treatment and drug delivery. Finally, we provide a brief conclusion and offer our perspectives on the current limitations and emerging applications of ferumoxytol in biomedicine. Overall, this review provides a comprehensive summary of the developments of ferumoxytol as an agent with diagnostic, therapeutic, and theranostic functionalities.

Moderately hypofractionated versus conventionally fractionated radiation therapy with temozolomide for young and fit patients with glioblastoma: an institutional experience and meta-analysis of literature

PURPOSE

Shorter hypofractionated radiation therapy (HF-RT) schedules may have radiobiological, patient convenience and healthcare resource advantages over conventionally fractionated radiation therapy (CF-RT) in glioblastoma (GBM). We report outcomes of young, fit GBM patients treated with HF-RT and CF-RT during the COVID-19 pandemic, and a meta-analysis of HF-RT literature in this patient subgroup.

METHODS

Hospital records of patients with IDH-wildtype GBM treated with HF-RT (50 Gy/20 fractions) and CF-RT (60 Gy/30 fractions) between January 2020 and September 2021 were reviewed. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan-Meier method. Univariable analysis was performed using Cox regression analysis. A systematic search and meta-analysis of studies from January 2000 to January 2022 was performed.

RESULTS

41 patients were treated (HF-RT:15, CF-RT:26). For both HF-RT and CF-RT groups, median age was 58 years and 80-90% were ECOG 0-1. There were more methylated tumours in the HF-RT group. All patients received concurrent/adjuvant temozolomide. At 19.2 months median follow-up, median OS was 19.8 months and not-reached for HF-RT and CF-RT (p = 0.5), and median PFS was 7.7 and 5.8 months, respectively (p = 0.8). HF-RT or CF-RT did not influence OS/PFS on univariable analysis. Grade 3 radionecrosis rate was 6.7% and 7.7%, respectively. 15 of 1135 studies screened from a systematic search were eligible for meta-analysis. For studies involving temozolomide, pooled median OS and PFS with HF-RT were 17.5 and 9.9 months (927 and 862 patients). Studies using shortened HF-RT schedules reported 0-2% Grade 3 radionecrosis rates.

CONCLUSION

HF-RT may offer equivalent outcomes and reduce treatment burden compared to CF-RT in young, fit GBM patients.

[18F] Fluorothymidine Positron Emission Tomography Imaging in Primary Brain Tumours: A Systematic Review

PURPOSE

This review aimed to summarize the available literature on the clinical application of [¹⁸F] FLT PET imaging in primary brain tumours.

METHODS

A comprehensive search strategy based on Pubmed/Medline, Scopus, Web of Science, Cochrane Library, Google Scholar, and the Embase databases was carried on using the following search string: ('3` Fluorothymidine'/exp OR 'FLT' OR '[81F]-FLT' OR '[¹⁸F] Fluorothymidine') AND ('pet'/exp OR 'pet' OR 'positron emission tomography') AND ('glioma'/exp OR 'glioma' OR 'brain tumour'/exp OR 'brain tumour'). The search was updated till March 2021 and only articles in English and studies investigating the clinical applications of [¹⁸F] FLT PET and PET/CT in primary brain tumours were considered eligible for inclusion.

RESULTS

The literature search ultimately yielded 52 studies included in the systematic review, with main results as follows: a) the uptake of [¹⁸F] FLT may guide stereotactic biopsy but does not discriminate between grade II and III glioma. b) [¹⁸F] FLT uptake and texture parameters correlate with overall survival (OS) in newly diagnosed gliomas. c) In patients with recurrent glioma, proliferative volume (PV) and tumour-to-normal brain (T/N) uptake ratio are independent predictors of survival. d) Patients demonstrating response to therapy at [¹⁸F] FLT PET scan show longer OS compared to non-responders. e) [¹⁸F] FLT PET demonstrated good performance in discriminating tumour recurrence from radionecrosis. However, controversial results exist in comparative literature examining the performance of [¹⁸F] FLT vs. other radiotracers in the assessment of recurrence.

CONCLUSION

[¹⁸F] FLT PET imaging has demonstrated potential benefits for grading, diagnostic and prognostic purposes, despite the small sample size studies due to the relatively low availability of the radiotracer.

Pseudoprogression is frequent following front-line radiotherapy in pediatric low-grade glioma - results from the German LGG cohort

PURPOSE

Expansion of MRI T2- and/or T1-tumor lesion volume after radiotherapy (RT) may indicate pseudoprogression (PsPD). The differentiation between true progression and PsPD is a clinical challenge and under-investigated in pediatric low-grade glioma (LGG). We evaluated radiological criteria for PsPD following front-line RT and investigated the frequency and duration of PsPD following three RT-modalities within the framework of the [Anonymized for Review] LGG-studies.

METHODS

Baseline and follow-up MRI-scans of 136 patients (72 [52.9%] male, median age at start of RT 11.3 years [range 0.8-25.9]) of the [Anonymized for Review] cohorts (¹²⁵iodine-interstitial RT [IS; n=51], photon-beam [XRT; n=60] or proton-beam RT [PBT; n=25]) were centrally evaluated for: Increasing 1) total tumor-associated T2-lesion, 2) focal tumor-associated T2-lesion and 3) contrast-enhancing tumor over a period of 24 months following RT. The pattern of these criteria initiated "suspicion" of PsPD, their evolution determined "definite" PsPD.

RESULTS

Definite PsPD was radiologically determined in 54/136 (39.7%) without differences in frequency between RT-modalities: IS 22/48 vs. XRT 24/54 vs. PBT 11/20; p=0.780. Definite PsPD occurred at median 6.3 months (IS 7.2 months; XRT 4.4 months; PBT 6.5 months) after RT-initiation and persisted for median 7.2 months (IS 8.5 months; XRT 7 months; PBT 7.4 months). Appearance of necrosis within the focal tumor-associated T2-lesion proved to be a relevant associated predictor of definite PsPD (p<0.001).

CONCLUSIONS

PsPD is frequent following irradiation of pediatric LGG and independent of the RT-modality (IS vs. XRT vs. PBT). Adequate identification of PsPD versus true progression is imperative to prevent unneeded salvage treatment.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma

RATIONALE AND OBJECTIVES

Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression.

MATERIALS AND METHODS

We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRM_rFLAIR+), decreased (PRM_rFLAIR-), or unchanged (PRM_rFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRM_rFLAIR between weeks 10 and 20 and continuously until the PRM_rFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection.

RESULTS

Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRM_rFLAIR+ (PFS: p <0.01; OS: p <0.001). PRM_rFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRM_rFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001).

CONCLUSION

PRM_rFLAIR may provide an early biomarker of disease progression in glioblastoma.

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

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.

The centrally restricted diffusion sign on MRI for assessment of radiation necrosis in metastases treated with stereotactic radiosurgery

Purpose

Differentiation of radiation necrosis from tumor progression in brain metastases treated with stereotactic radiosurgery (SRS) is challenging. For this, we assessed the performance of the centrally restricted diffusion sign.

Methods

Patients with brain metastases treated with SRS who underwent a subsequent intervention (biopsy/resection) for a ring-enhancing lesion on preoperative MRI between 2000 and 2020 were included. Excluded were lesions containing increased susceptibility limiting assessment of DWI. Two neuroradiologists classified the location of the diffusion restriction with respect to the post-contrast T1 images as centrally within the ring-enhancement (the centrally restricted diffusion sign), peripherally correlating to the rim of contrast enhancement, both locations, or none. Measures of diagnostic accuracy and 95% CI were calculated for the centrally restricted diffusion sign. Cohen's kappa was calculated to identify the interobserver agreement.

Results

Fifty-nine patients (36 female; mean age 59, range 40 to 80) were included, 36 with tumor progression and 23 with radiation necrosis based on histopathology. Primary tumors included 34 lung, 12 breast, 5 melanoma, 3 colorectal, 2 esophagus, 1 head and neck, 1 endometrium, and 1 thyroid. The centrally restricted diffusion sign was seen in 19/23 radiation necrosis cases (sensitivity 83% (95% CI 63 to 93%), specificity 64% (95% CI 48 to 78%), PPV 59% (95% CI 42 to 74%), NPV 85% (95% CI 68 to 94%)) and 13/36 tumor progression cases (difference p < 0.001). Interobserver agreement was substantial, at 0.61 (95% CI 0.45 to 70.8).

Conclusion

We found a low probability of radiation necrosis in the absence of the centrally restricted diffusion sign.

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

Background

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

Methods

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

Results

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

Conclusion

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

RNA m1A Methyltransferase TRMT6 Predicts Poorer Prognosis and Promotes Malignant Behavior in Glioma

Background: Glioma is the most prevalent central nervous system tumor in humans, and its prognosis remains unsatisfactory due to a lack of effective therapeutic targets. The ectopic expression of N1-methyladenosine (m1A) regulators is a key participant in tumorigenesis and progression. However, the m1A regulator expression status, prognostic value, and relationship with tumor clinical features in glioma remain unclear. Methods: Public datasets were used to analyze the mRNA and protein expression levels of m1A regulators. Kaplan-Meier and Cox regression analyses were performed to confirm the prognostic value of m1A regulators in glioma. Cellular experiments were conducted to verify the effect of TRMT6 on cell function. A comprehensive bioinformatics analysis was conducted to identify the potential molecular mechanisms regulated by TEMT6 in glioma. Results: We found that the dysregulation of m1A regulators was closely associated with tumorigenesis and progression in glioma. Furthermore, TRMT6 might be a powerful and independent biomarker for prognosis in glioma. Our study showed that inhibition of TRMT6 suppressed the proliferation, migration, and invasion of glioma cells. Mechanistically, TRMT6 may be involved in glioma progression by regulating cell cycle, PI3K-AKT, TGF-beta, MTORC1, NOTCH, and MYC pathways. Conclusions: Variation in m1A regulators was closely associated with malignant progression in glioma. Silencing TRMT6 suppressed the cell proliferation, migration, and invasion in glioma. m1A regulators, especially TRMT6, might play an essential role in the malignant progression of glioma.

Reirradiation With Stereotactic Radiosurgery After Local or Marginal Recurrence of Brain Metastases From Previous Radiosurgery

PURPOSE

Brain metastases represent a major indication for stereotactic radiosurgery (SRS), but further study is needed regarding repeat SRS (SRS2) after local or marginal recurrence after prior SRS (SRS1). We report local tumor control (LC) after SRS2 and identify predictors of radiation necrosis (RN) and symptomatic RN (SRN).

METHODS AND MATERIALS

Patients had biopsy-proven non-small cell lung cancer and at least 1 brain metastasis previously treated with SRS. SRS2 was performed from 2015 to 2020 and required overlap of the prescription isodose lines with those from SRS1. Patients treated with preoperative SRS were excluded. Primary endpoints were LC by Response Assessment in Neuro-oncology criteria, RN, and SRN.

RESULTS

From 8 institutions, 102 patients with 123 treated lesions were included. SRS2 was performed at a median 12 months after SRS1. SRS2 delivered a median 18 Gy (interquartile range [IQR], 16-18) margin dose to the 50% (IQR, 50%-70%) isodose line, maximum dose of 30.5 Gy (IQR, 25.0-36.0), and V12Gy of 3.38 cm³ (IQR, 0.83-7.64). One-year and 2-year LC were 79% and 72%, respectively. Local tumor control was improved with tumor volume ≤1 cm³ (P < .005). There were 25 (20%) cases of RN and 9 (7%) cases of SRN. For SRS1 and SRS2, SRN rates were higher with maximum doses ≥40 Gy or SRS2 V12Gy >9 cm³ (P < .025 for each). SRS1 and SRS2 maximum dose ≥40 Gy was also predictive of increased RN (P < .05 for each). Prior immunotherapy was not predictive of RN or SRN.

CONCLUSIONS

Repeat SRS afforded a high rate of local tumor control and a low rate of SRN. At SRS2, V12Gy ≤9 cm³ and maximum dose <40 Gy may reduce the risks of RN and SRN. These results are most applicable to lesions with approximately 1 cm³ volume and 1-year interval between SRS courses.

Redo craniotomy or bevacizumab for symptomatic steroid-refractory true or pseudoprogression following IMRT for glioblastoma

Background

There is minimal evidence to support decision making for symptomatic steroid-refractory pseudoprogression or true progression occurring after intensity-modulated radiation therapy (IMRT) for glioblastoma (GBM). This study audited the survival outcome of patients managed with redo craniotomy (RedoSx) or bevacizumab (BEV) for steroid-refractory mass effect after IMRT for GBM.

Methods

Patients with GBM managed between 2008 and 2019 with the EORTC-NCIC Protocol were entered into a prospective database. Patients with symptomatic steroid-refractory mass effect within 6 months of IMRT managed with either RedoSx or BEV were identified for analysis. For the primary endpoint of median overall survival (OS) postintervention, outcome was analyzed in regards to potential prognostic factors, and differences between groups were assessed by log-rank analyses.

Results

Of the 399 patients managed with the EORTC-NCIC Protocol, 78 required an intervention within 6 months of IMRT completion for either true or pseudoprogression (49 with RedoSx and 29 with BEV). Subsequently, 20 of the 43 patients managed with RedoSx when BEV was clinically available, required salvage with BEV within 6 months after RedoSx. Median OS postintervention was 8.7 months (95% CI: 7.84-11.61) for the total group; and 8.7 months (95% CI: 6.8-13.1) for RedoSx and 9.4 months (95% CI: 7.8-13.6) for BEV (P = .38). Subsequent use of BEV in RedoSx patients was not associated with improved survival compared with RedoSx alone (P = .10). Age, time from IMRT, and ECOG performance status were not associated with OS. In the RedoSx patients, immunohistochemical features such as Ki-67% reduction correlated with survival. The presence of pure necrosis and residual tumor cells only had improved survival compared with the presence of gross tumor (P < .001).

Conclusions

At time of symptomatic steroid-refractory true or pseudoprogression following IMRT for GBM, BEV was equivalent to RedoSx in terms of OS. Pseudoprogression with residual cells at RedoSx was not associated with worse outcome compared to pure necrosis.

PET/MRI Improves Management of Children with Cancer

Integrated PET/MRI has shown significant clinical value for staging and restaging of children with cancer by providing functional and anatomic tumor evaluation with a 1-stop imaging test and with up to 80% reduced radiation exposure compared with 18F-FDG PET/CT. This article reviews clinical applications of 18F-FDG PET/MRI that are relevant for pediatric oncology, with particular attention to the value of PET/MRI for patient management. Early adopters from 4 different institutions share their insights about specific advantages of PET/MRI technology for the assessment of young children with cancer. We discuss how whole-body PET/MRI can be of value in the evaluation of certain anatomic regions, such as soft tissues and bone marrow, as well as specific PET/MRI interpretation hallmarks in pediatric patients. We highlight how whole-body PET/MRI can improve the clinical management of children with lymphoma, sarcoma, and neurofibromatosis, by reducing the number of radiologic examinations needed (and consequently the radiation exposure), without losing diagnostic accuracy. We examine how PET/MRI can help in differentiating malignant tumors versus infectious or inflammatory diseases. Future research directions toward the use of PET/MRI for treatment evaluation of patients undergoing immunotherapy and assessment of different theranostic agents are also briefly explored. Lessons learned from applications in children might also be extended to evaluations of adult patients.

Imaging Advances for Central Nervous System Tumors

This article reviews recent advances in the use of standard and advanced imaging techniques for diagnosis and treatment of central nervous system (CNS) tumors, including glioma and brain metastasis. Following the recent transition from a histology-based approach in classifying CNS tumors to one that integrates histology with the molecular information of tumor, the approaches for imaging CNS tumors have also been adapted to this new framework. Some challenges related to the diagnosis and treatment of CNS tumors, such as differentiating tumor from treatment-related imaging changes, require further progress to implement advanced imaging for clinical use.

Prognostic and Predictive Biomarkers in Gliomas

Gliomas are the most common central nervous system tumors. New technologies, including genetic research and advanced statistical methods, revolutionize the therapeutic approach to the patient and reveal new points of treatment options. Moreover, the 2021 World Health Organization Classification of Tumors of the Central Nervous System has fundamentally changed the classification of gliomas and incorporated many molecular biomarkers. Given the rapid progress in neuro-oncology, here we compile the latest research on prognostic and predictive biomarkers in gliomas. In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. Finally, we discussed liquid biopsies, which are promising diagnostic, prognostic, and predictive techniques, but further work is needed to implement these novel technologies in clinical practice.

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

Objectives:

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

Methods:

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

Results:

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

Conclusions

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

Advances in knowledge:

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

Clinical case of lung spindle cell carcinoma markedly responsive to pembrolizumab

A 52‐year‐old man underwent pneumonectomy of the left lung for previously diagnosed primary spindle cell carcinoma (pT4aN1M0, stage III B) with programmed death‐ligand 1 expression (tumor proportion score ≥95%) and without epidermal growth factor receptor gene mutation and anaplastic lymphoma kinase fusion gene. However, brain metastasis and chest wall tumor relapse occurred. Considering insufficient improvement with gamma knife treatment for brain metastasis and combination chemotherapy (paclitaxel, carboplatin, and bevacizumab), pembrolizumab monotherapy and palliative irradiation therapy for chest metastases were started after brain tumor volume reduction using craniotomy. Brain edema and chest wall metastases markedly improved following a pseudoprogression of the brain edema accompanied by a performance status decline; this effect continued until 11 cycles of pembrolizumab administration.

A Phase 2 Study of Dose-intensified Chemoradiation Using Biologically Based Target Volume Definition in Patients With Newly Diagnosed Glioblastoma

PURPOSE

We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TVHCV) and hyperperfused (TVCBV) tumor volumes would improve outcomes in patients with glioblastoma.

METHODS AND MATERIALS

This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TVHCV/TVCBV >1 cm3, identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TVHCV/TVCBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TVHCV/TVCBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised.

RESULTS

Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TVHCV alone, and 13 patients were boosted to both TVHCV/TVCBV. Gross or subtotal resection was performed in 87% of patients; 22% were O6-methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TVHCV/TVCBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TVHCV/TVCBV decreased to less than the median volume (3 cm3) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy.

CONCLUSIONS

Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy.

Fully automated analysis combining [18F]-FET-PET and multiparametric MRI including DSC perfusion and APTw imaging: a promising tool for objective evaluation of glioma progression

Purpose

To evaluate diagnostic accuracy of fully automated analysis of multimodal imaging data using [¹⁸F]-FET-PET and MRI (including amide proton transfer-weighted (APTw) imaging and dynamic-susceptibility-contrast (DSC) perfusion) in differentiation of tumor progression from treatment-related changes in patients with glioma.

Material and methods

At suspected tumor progression, MRI and [¹⁸F]-FET-PET data as part of a retrospective analysis of an observational cohort of 66 patients/74 scans (51 glioblastoma and 23 lower-grade-glioma, 8 patients included at two different time points) were automatically segmented into necrosis, FLAIR-hyperintense, and contrast-enhancing areas using an ensemble of deep learning algorithms. In parallel, previous MR exam was processed in a similar way to subtract preexisting tumor areas and focus on progressive tumor only. Within these progressive areas, intensity statistics were automatically extracted from [¹⁸F]-FET-PET, APTw, and DSC-derived cerebral-blood-volume (CBV) maps and used to train a Random Forest classifier with threefold cross-validation. To evaluate contribution of the imaging modalities to the classifier’s performance, impurity-based importance measures were collected. Classifier performance was compared with radiology reports and interdisciplinary tumor board assessments.

Results

In 57/74 cases (77%), tumor progression was confirmed histopathologically (39 cases) or via follow-up imaging (18 cases), while remaining 17 cases were diagnosed as treatment-related changes. The classification accuracy of the Random Forest classifier was 0.86, 95% CI 0.77–0.93 (sensitivity 0.91, 95% CI 0.81–0.97; specificity 0.71, 95% CI 0.44–0.9), significantly above the no-information rate of 0.77 (p = 0.03), and higher compared to an accuracy of 0.82 for MRI (95% CI 0.72–0.9), 0.81 for [¹⁸F]-FET-PET (95% CI 0.7–0.89), and 0.81 for expert consensus (95% CI 0.7–0.89), although these differences were not statistically significant (p > 0.1 for all comparisons, McNemar test). [¹⁸F]-FET-PET hot-spot volume was single-most important variable, with relevant contribution from all imaging modalities.

Conclusion

Automated, joint image analysis of [¹⁸F]-FET-PET and advanced MR imaging techniques APTw and DSC perfusion is a promising tool for objective response assessment in gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05427-8.

Mismatch repair-deficient prostate cancer with parenchymal brain metastases treated with immune checkpoint blockade

Parenchymal brain metastases from prostate cancer are unusual and are associated with poor prognosis. Given the rarity of this entity, little is known about its molecular and histologic characteristics. Here we describe a patient with metastatic castration-resistant, mismatch repair-deficient (dMMR) prostate cancer with parenchymal brain metastases. Analysis of a brain metastasis revealed MLH1 loss consistent with dMMR, yet few tumor-infiltrating lymphocytes (TILs). He was treated with immune checkpoint blockade (ICB) and exhibited an extra-central nervous system (CNS) systemic response but CNS progression. Subsequent assessment of a brain metastasis following ICB treatment surprisingly showed increased TIL density and depletion of macrophages, suggestive of an enhanced antitumor immune response. Post-treatment tumoral DNA sequencing did not reveal acquired mutations that might confer resistance to ICB. This is the first description of ICB therapy for a patient with prostate cancer with parenchymal brain metastases, with pre- and post-treatment immunogenomic analyses.

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.

Phase II trial of proton therapy versus photon IMRT for GBM: secondary analysis comparison of progression-free survival between RANO versus clinical assessment

Background

This secondary image analysis of a randomized trial of proton radiotherapy (PT) versus photon intensity-modulated radiotherapy (IMRT) compares tumor progression based on clinical radiological assessment versus Response Assessment in Neuro-Oncology (RANO).

Methods

Eligible patients were enrolled in the randomized trial and had MR imaging at baseline and follow-up beyond 12 weeks from completion of radiotherapy. “Clinical progression” was based on a clinical radiology report of progression and/or change in treatment for progression.

Results

Of 90 enrolled patients, 66 were evaluable. Median clinical progression-free survival (PFS) was 10.8 (range: 9.4–14.7) months; 10.8 months IMRT versus 11.2 months PT (P = .14). Median RANO-PFS was 8.2 (range: 6.9, 12): 8.9 months IMRT versus 6.6 months PT (P = .24). RANO-PFS was significantly shorter than clinical PFS overall (P = .001) and for both the IMRT (P = .01) and PT (P = .04) groups. There were 31 (46.3%) discrepant cases of which 17 had RANO progression more than a month prior to clinical progression, and 14 had progression by RANO but not clinical criteria.

Conclusions

Based on this secondary analysis of a trial of PT versus IMRT for glioblastoma, while no difference in PFS was noted relative to treatment technique, RANO criteria identified progression more often and earlier than clinical assessment. This highlights the disconnect between measures of tumor response in clinical trials versus clinical practice. With growing efforts to utilize real-world data and personalized treatment with timely adaptation, there is a growing need to improve the consistency of determining tumor progression within clinical trials and clinical practice.

Role of post-therapy 99mTc-MIBI single-photon emission computed tomography/computed tomography scan in predicting survival in patients with high-grade glioma

OBJECTIVE

High-grade gliomas (HGGs) carry dismal prognosis with survival typically reported as less than a year. We explored the predictive value of qualitative and quantitative evaluations of post-treatment 99m-technetium-labelled methoxyisobutylisonitrile (99mmTc-MIBI) brain single-photon emission computed tomography-computed tomography (SPECT/CT) tumor uptake in relation to overall survival (OS) in patients with HGG.

METHODS

Thirty patients with pathologically or radiologically documented high-grade glioma (HGG) were prospectively recruited for this study (24 male, 6 female; mean age 43 ± 14 years). All patients had a clinical or radiological suspicion of residual/recurrent tumor after initial therapy. 99mTc-MIBI brain SPECT/CT scanning was performed, and the scans were evaluated qualitatively on a five-point probability score (1-5, scores ≥3 considered positive for residual/recurrent tumor); and quantitively via drawing volumes of interest (VOI) on the suspected lesions and normal contralateral brain tissue. All patients were followed up for 1 year or till death.

RESULTS

Positive visual MIBI results were associated with poor survival. Among 10 patients with negative MIBI scores, only two patients died (OS = 75%), while 11/20 patients reported positive on MIBI died, with a median survival of 9 months (OS = 14.5%; P = 0.03). All patients with active isocontour volume ≤1.96 cm3 were alive at the end of the study, compared to a median survival of 9 months and OS of 12% for patients with an isocontour volume of >1.97% (P = 0.003).

CONCLUSION

In patients with HGG, post-therapy brain SPECT/CT with 99mTc-MIBI can provide useful prognostic information.

Longitudinal structural and perfusion MRI enhanced by machine learning outperforms standalone modalities and radiological expertise in high-grade glioma surveillance

PURPOSE

Surveillance of patients with high-grade glioma (HGG) and identification of disease progression remain a major challenge in neurooncology. This study aimed to develop a support vector machine (SVM) classifier, employing combined longitudinal structural and perfusion MRI studies, to classify between stable disease, pseudoprogression and progressive disease (3-class problem).

METHODS

Study participants were separated into two groups: group I (total cohort: 64 patients) with a single DSC time point and group II (19 patients) with longitudinal DSC time points (2-3). We retrospectively analysed 269 structural MRI and 92 dynamic susceptibility contrast perfusion (DSC) MRI scans. The SVM classifier was trained using all available MRI studies for each group. Classification accuracy was assessed for different feature dataset and time point combinations and compared to radiologists' classifications.

RESULTS

SVM classification based on combined perfusion and structural features outperformed radiologists' classification across all groups. For the identification of progressive disease, use of combined features and longitudinal DSC time points improved classification performance (lowest error rate 1.6%). Optimal performance was observed in group II (multiple time points) with SVM sensitivity/specificity/accuracy of 100/91.67/94.7% (first time point analysis) and 85.71/100/94.7% (longitudinal analysis), compared to 60/78/68% and 70/90/84.2% for the respective radiologist classifications. In group I (single time point), the SVM classifier also outperformed radiologists' classifications with sensitivity/specificity/accuracy of 86.49/75.00/81.53% (SVM) compared to 75.7/68.9/73.84% (radiologists).

CONCLUSION

Our results indicate that utilisation of a machine learning (SVM) classifier based on analysis of longitudinal perfusion time points and combined structural and perfusion features significantly enhances classification outcome (p value= 0.0001).

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive diagnosis still relies on surgical pathology. Machine learning has been applied to the analysis of MRI data in glioma research and has the potential to change clinical practice and improve patient outcomes. This systematic review synthesizes and analyzes the current state of machine learning applications to glioma MRI data and explores the use of machine learning for systematic review automation. Various datapoints were extracted from the 153 studies that met inclusion criteria and analyzed. Natural language processing (NLP) analysis involved keyword extraction, topic modeling and document classification. Machine learning has been applied to tumor grading and diagnosis, tumor segmentation, non-invasive genomic biomarker identification, detection of progression and patient survival prediction. Model performance was generally strong (AUC = 0.87 ± 0.09; sensitivity = 0.87 ± 0.10; specificity = 0.0.86 ± 0.10; precision = 0.88 ± 0.11). Convolutional neural network, support vector machine and random forest algorithms were top performers. Deep learning document classifiers yielded acceptable performance (mean 5-fold cross-validation AUC = 0.71). Machine learning tools and data resources were synthesized and summarized to facilitate future research. Machine learning has been widely applied to the processing of MRI data in glioma research and has demonstrated substantial utility. NLP and transfer learning resources enabled the successful development of a replicable method for automating the systematic review article screening process, which has potential for shortening the time from discovery to clinical application in medicine.

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.

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.

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.

Role of circulating tumor cell detection in differentiating tumor recurrence from treatment necrosis of brain gliomas

Differentiating treatment necrosis from tumor recurrence poses a diagnostic conundrum for many clinicians in neuro-oncology. To investigate the potential role of circulating tumor cells (CTCs) detection in differentiating tumor recurrence and treatment necrosis in brain gliomas, we retrospectively analyzed the data of 22 consecutive patients with tumor totally removed and new enhancing mass lesion(s) showed on MRI after initial radiotherapy. The 22 patients were finally classified into tumor recurrence group (n = 10) and treatment necrosis group (n = 12), according to evidence from the clinical course (n = 11) and histological confirmation (n = 11). All 22 patients received CTCs detection, and DSC-MRP and 11C-MET-PET were performed on 20 patients (90.9%) and 17patients (77.3%) respectively. The data of the diagnosis efficacy to differentiate the two lesions by CTC detection, MPR and PET were analyzed by ROC analysis. The mean CTCs counts were significantly higher in the tumor recurrence group (6.10 ± 3.28) compared to the treatment necrosis group (1.08 ± 2.54, p < 0.001). The ROC curve showed that an optimized cell count threshold of 2 had 100% sensitivity and 91.2% specificity with AUC = 0.933 to declare tumor recurrence. The diagnostic efficacy of CTC detection was superior to rCBV of DSC-MRP and rSUV_max in MET-PET. Furthermore, we observed that CTCs detection could have a potential role in predicting tumor recurrence in one patient. Our research results preliminarily showed the potential value of CTC detection in differentiating treatment necrosis from tumor recurrence in brain gliomas, and is worthy of further confirmation with large samples involved.

Toward a standard pathological and molecular characterization of recurrent glioma in adults: a Response Assessment in Neuro-Oncology effort

Regardless of subtype, diffuse gliomas of adulthood are characterized by inexorable progression through treatment. Cancer recurrence in the context of therapy is by no means unique to gliomas. For many tumors residing outside the central nervous system (CNS), tissue-based analyses are routinely employed to document the molecular and cellular features of disease recurrence. Such interventions are inconsistently applied for gliomas, however, and lack rigorous standardization when they are. While many of the reasons underlying these discrepancies reflect pragmatic realities inherent to CNS disease, the suboptimal employment of histological and molecular assessment at recurrence nevertheless represents a missed opportunity to proactively guide patient management and increase knowledge. Herein, we address this quandary by pairing a succinct description of the histological, biological, and molecular characteristics of recurrent glioma with recommendations for how to better standardize and implement quality pathological assessment into patient management. We hope this review will prompt thoughtful revision of standard operating procedures to maximize the utility of glioma re-biopsy.

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.

Distinguishing Pseudoprogression From True Early Progression in Isocitrate Dehydrogenase Wild-Type Glioblastoma by Interrogating Clinical, Radiological, and Molecular Features

Background: Pseudoprogression (PsP) mimics true early progression (TeP) in conventional imaging, which poses a diagnostic challenge in glioblastoma (GBM) patients who undergo standard concurrent chemoradiation (CCRT). This study aimed to investigate whether perioperative markers could distinguish and predict PsP from TeP in de novo isocitrate dehydrogenase (IDH) wild-type GBM patients.

Methods: New or progressive gadolinium-enhancing lesions that emerged within 12 weeks after CCRT were defined as early progression. Lesions that remained stable or spontaneously regressed were classified as PsP, otherwise persistently enlarged as TeP. Clinical, radiological, and molecular information were collected for further analysis. Patients in the early progression subgroup were divided into derivation and validation sets (7:3, according to operation date).

Results: Among 234 consecutive cases enrolled in this retrospective study, the incidences of PsP, TeP, and neither patterns of progression (nP) were 26.1% (61/234), 37.6% (88/234), and 36.3% (85/234), respectively. In the early progression subgroup, univariate analysis demonstrated female (OR: 2.161, P = 0.026), gross total removal (GTR) of the tumor (OR: 6.571, P < 001), located in the frontal lobe (OR: 2.561, P = 0.008), non-subventricular zone (SVZ) infringement (OR: 10.937, P < 0.001), and methylated O-6-methylguanine-DNA methyltransferase (MGMT) promoter (mMGMTp) (OR: 9.737, P < 0.001) were correlated with PsP, while GTR, non-SVZ infringement, and mMGMTp were further validated in multivariate analysis. Integrating quantitative MGMTp methylation levels from pyrosequencing, GTR, and non-SVZ infringement showed the best discriminative ability in the random forest model for derivation and validation set (AUC: 0.937, 0.911, respectively). Furthermore, a nomogram could effectively evaluate the importance of those markers in developing PsP (C-index: 0.916) and had a well-fitted calibration curve.

Conclusion: Integrating those clinical, radiological, and molecular features provided a novel and robust method to distinguish PsP from TeP, which was crucial for subsequent clinical decision making, clinical trial enrollment, and prognostic assessment. By in-depth interrogation of perioperative markers, clinicians could distinguish PsP from TeP independent from advanced imaging.

Distinct imaging patterns of pseudoprogression in glioma patients following proton versus photon radiation therapy

PURPOSE

Criteria by the Radiologic Assessment in Neuro-Oncology (RANO) group outline the diagnosis of pseudoprogression (Ps) after photon therapy for gliomas based on timing and location. We noted that patients receiving proton therapy manifested radiographic changes that appear different than Ps after photon therapy, which could be interpreted as tumor progression. In this study, we retrospectively reviewed MR imaging after proton or photon radiation for gliomas. We propose criteria to characterize proton pseudoprogression (ProPs) as distinct from Ps seen after photons.

METHODS

Post-treatment MR imaging, clinical and pathological data of low grade glioma patients were reviewed. Overall, 57 patients receiving protons were reviewed for the presence of ProPs, and 43 patients receiving photons were reviewed for any equivalent imaging changes. Data collected included the location and timing of the new enhancement, tumor grade, molecular subtype, chemotherapy received, and clinical symptoms.

RESULTS

Fourteen patients (24.6%) had new enhancement following radiation therapy that was unique to treatment with protons. The mean time to development of the ProPs was 15.4 months (7-27 months). We established the following criteria to characterize ProPs: located at the distal end of the proton beam; resolves without tumor-directed therapy; and subjectively multifocal, patchy, and small (< 1 cm). In the group receiving photons, none had changes that met our criteria for ProPs.

CONCLUSION

Patients who receive protons have unique imaging changes after radiation therapy. ProPs could be mistaken for tumor progression, but typically resolves on follow up. Further studies are needed to understand the radiobiology and pathophysiology underlying these imaging changes.

Knockdown of CLN5 inhibits the tumorigenic properties of glioblastoma cells via the Akt/mTOR signaling pathway

Gliomas are highly malignant tumors with a rapid progression and poor prognosis. The present study investigated the cellular effects of CLN5-knockdown in the glioblastoma (GBM) U251 and U87MG cell lines. The Cell Counting Kit-8 and colony formation assays indicated that CLN5-knockdown inhibited the proliferation of GBM cells. Additionally, the results of the Transwell and scratch assays revealed that CLN5-knockdown significantly inhibited migration and invasion, and the flow cytometry analysis confirmed that apoptosis was promoted. Knockdown of CLN5 downregulated the expression levels of MMP-2, Bcl-2, cyclin D1, CDK4 and CDK6, and upregulated the expression levels of Bax and activated caspase-9. Additionally, it blocked GBM cells in the G1-phase and induced early apoptosis. Knockdown of CLN5 inhibited the activation of the Akt and mTOR signaling pathways in GBM by decreasing the levels of phosphorylated (p)-Akt and p-mTOR. The present data suggested that downregulation of CLN5 may be a potential treatment option for GBM. Knockdown of CLN5 inhibited the development of GBM via the inhibition of the Akt and mTOR signaling pathways.

Circulating Tumor Cells for Glioma

Liquid biopsy has entered clinical applications for several cancers, including metastatic breast, prostate, and colorectal cancer for CTC enumeration and NSCLC for EGFR mutations in ctDNA, and has improved the individualized treatment of many cancers, but relatively little progress has been made in validating circulating biomarkers for brain malignancies. So far, data on circulating tumor cells about glioma are limited, the application of circulating tumor cells as biomarker for glioma patients has only just begun. This article reviews the research status and application prospects of circulating tumor cells in gliomas. Several detection methods and research results of circulating tumor cells about clinical research in gliomas are briefly discussed. The wide application prospect of circulating tumor cells in glioma deserves further exploration, and the research on more sensitive and convenient detection methods is necessary.

Autologous adoptive immune-cell therapy elicited a durable response with enhanced immune reaction signatures in patients with recurrent glioblastoma: An open label, phase I/IIa trial

Glioblastoma multiforme (GBM) is an aggressive malignancy classified by the World Health Organization as a grade IV glioma. Despite the availability of aggressive standard therapies, most patients experience recurrence, for which there are currently no effective treatments. We aimed to conduct a phase I/IIa clinical trial to investigate the safety and efficacy of adoptive, ex-vivo-expanded, and activated natural killer cells and T lymphocytes from peripheral blood mononuclear cells of patients with recurrent GBM. This study was a single-arm, open-label, investigator-initiated trial on 14 patients recruited between 2013 and 2017. The immune cells were administered via intravenous injection 24 times at 2-week intervals after surgical resection or biopsy. The safety and clinical efficacy of this therapy was examined by assessing adverse events and comparing 2-year overall survival (OS). Transcriptomic analysis of tumor tissues was performed using NanoString to identify the mechanism of therapeutic efficacy. No grade 4 or 5 severe adverse events were observed. The most common treatment-related adverse events were grade 1 or 2 in severity. The most severe adverse event was grade 3 fever. Median OS was 22.5 months, and the median progression-free survival was 10 months. Five patients were alive for over 2 years and showed durable response with enhanced immune reaction transcriptomic signatures without clinical decline until the last follow-up after completion of the therapy. In conclusion, autologous adoptive immune-cell therapy was safe and showed durable response in patients with enhanced immune reaction signatures. This therapy may be effective for recurrent GBM patients with high immune response in their tumor microenvironments. Trial registration: The Korea Clinical Research Information Service database: KCT0003815, Registered 18 April 2019, retrospectively registered.

Modulation of Nogo receptor 1 expression orchestrates myelin-associated infiltration of glioblastoma

As the clinical failure of glioblastoma treatment is attributed by multiple components, including myelin-associated infiltration, assessment of the molecular mechanisms underlying such process and identification of the infiltrating cells have been the primary objectives in glioblastoma research. Here, we adopted radiogenomic analysis to screen for functionally relevant genes that orchestrate the process of glioma cell infiltration through myelin and promote glioblastoma aggressiveness. The receptor of the Nogo ligand (NgR1) was selected as the top candidate through Differentially Expressed Genes (DEG) and Gene Ontology (GO) enrichment analysis. Gain and loss of function studies on NgR1 elucidated its underlying molecular importance in suppressing myelin-associated infiltration in vitro and in vivo. The migratory ability of glioblastoma cells on myelin is reversibly modulated by NgR1 during differentiation and dedifferentiation process through deubiquitinating activity of USP1, which inhibits the degradation of ID1 to downregulate NgR1 expression. Furthermore, pimozide, a well-known antipsychotic drug, upregulates NgR1 by post-translational targeting of USP1, which sensitizes glioma stem cells to myelin inhibition and suppresses myelin-associated infiltration in vivo. In primary human glioblastoma, downregulation of NgR1 expression is associated with highly infiltrative characteristics and poor survival. Together, our findings reveal that loss of NgR1 drives myelin-associated infiltration of glioblastoma and suggest that novel therapeutic strategies aimed at reactivating expression of NgR1 will improve the clinical outcome of glioblastoma patients.

Collagen Type I α-1 Promotes Malignant Glioma Cell Proliferation and Is Associated with Glioma Prognosis

Collagen type I α-1 chain (COL1A1) is closely involved in the advancement of various tumors, yet the role of COL1A1 in the progression of glioma is not clear. Herein, we evaluated the effect of COL1A1 on glioma cell proliferation. The effect of COL1A1 on glioma cell proliferation was assessed through overexpression or knockdown of COL1A1. The CCK-8 and colony formation assays, as well as immunohistochemistry (IHC) were used to detect COL1A1 expression in different glioma grades. U-87MG as well as U-251MG cells were stably-inserted with lentivirus containing COL1A1 through transfection, we additionally used qRT-PCR as well as Western blot assay to validate their overexpression efficiencies. COL1A1 mRNA and protein levels were upregulated in the high-grade glioma (HGG) compared to the low-grade glioma (LGG). COL1A1 IHC score was remarkably higher in HGG than LGG. The staining index (SI) further showed that COL1A1 protein levels were higher in HGG than LGG. The Kaplan–Meier analysis showed that elevated COL1A1 mRNA levels were obviously correlated with lower overall survival (OS) and disease-free survival (DFS) for brain glioma patients. COL1A1 mRNA and protein levels were markedly upregulated in human glioma cell lines when compared with brain astrocyte cell lines. The high expression level of COL1A1 facilitated glioma cell proliferation. COL1A1 knockdown remarkably inhibited glioma cell proliferation. Thus, this research shows that COL1A1 promotes glioma cell proliferation and is closely related to glioma prognosis.