Advances in neuro-oncology imaging

Determining optimal clinical target volume margins in high-grade glioma based on microscopic tumor extension and magnetic resonance imaging

Introduction

In this study, we performed a consecutive macropathologic analysis to assess microscopic extension (ME) in high-grade glioma (HGG) to determine appropriate clinical target volume (CTV) margins for radiotherapy.

Materials and methods

The study included HGG patients with tumors located in non-functional areas, and supratotal resection was performed. The ME distance from the edge of the tumor to the microscopic tumor cells surrounding brain tissue was measured. Associations between the extent of ME and clinicopathological characteristics were evaluated by multivariate linear regression (MVLR) analysis. An ME predictive model was developed based on the MVLR model.

Results

Between June 2017 and July 2019, 652 pathologic slides obtained from 30 HGG patients were analyzed. The mean ME distance was 1.70 cm (range, 0.63 to 2.87 cm). The MVLR analysis identified that pathologic grade, subventricular zone (SVZ) contact and O⁶-methylguanine-DNA methyltransferase (MGMT) methylation, isocitrate dehydrogenase (IDH) mutation and 1p/19q co-deletion status were independent variables predicting ME (all P < 0.05). A multivariable prediction model was developed as follows: Y_ME = 0.672 + 0.513X_Grade + 0.380X_SVZ + 0.439X_MGMT + 0.320X_IDH + 0.333X_1p/19q. The R-square value of goodness of fit was 0.780. The receiver operating characteristic curve proved that the area under the curve was 0.964 (P < 0.001).

Conclusion

ME was heterogeneously distributed across different grades of gliomas according to the tumor location and molecular marker status, which indicated that CTV delineation should be individualized. The model could predict the ME of HGG, which may help clinicians determine the CTV for individual patients.

Trial registration The trial was registered with Chinese Clinical Trial Registry (ChiCTR2100046106). Registered 4 May 2021-Retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-021-01819-0.

Attenuated Microcirculation in Small Metastatic Tumors in Murine Liver

Metastatic cancer disease is the major cause of death in cancer patients. Because those small secondary tumors are clinically hardly detectable in their early stages, little is known about drug biodistribution and permeation into those metastatic tumors potentially contributing to insufficient clinical success against metastatic disease. Our recent studies indicated that breast cancer liver metastases may have compromised perfusion of intratumoral capillaries hindering the delivery of therapeutics for yet unknown reasons. To understand the microcirculation of small liver metastases, we have utilized computational simulations to study perfusion and oxygen concentration fields in and around the metastases smaller than 700 µm in size at the locations of portal vessels, central vein, and liver lobule acinus. Despite tumor vascularization, the results show that blood flow in those tumors can be substantially reduced indicating the presence of inadequate blood pressure gradients across tumors. A low blood pressure may contribute to the collapsed intratumoral capillary lumen limiting tumor perfusion that phenomenologically corroborates with our previously published in vivo studies. Tumors that are smaller than the liver lobule size and originating at different lobule locations may possess a different microcirculation environment and tumor perfusion. The acinus and portal vessel locations in the lobule were found to be the most beneficial to tumor growth based on tumor access to blood flow and intratumoral oxygen. These findings suggest that microcirculation states of small metastatic tumors can potentially contribute to physiological barriers preventing efficient delivery of therapeutic substances into small tumors.

On-Chip Replication of Extremely Early-Stage Tumor Behavior

Cancer is a multistep progressive disease that generally involves tumor growth, invasion, and metastasis. It is crucial to understand tumor progression for tumor diagnosis and therapy. However, tumor progression at an extremely early stage (EES) is barely demonstrated because EES tumors are too small to be detected by imaging. Herein, we, for the first time, replicated tumor progression at the EES on a microfluidic chip and uncovered the tumor behaviors affected by the tumor microenvironment. To mimic the progression of a single solid tumor at the EES, a HeLa cell spheroid was seeded and cultured on the chip, and a microvascular network was developed to integrate the microphysiological contexts around the tumor. We revealed not only the growth patterns and cell behaviors of tumor spheroids of different sizes under angiogenesis and fibroblast conditions but also the effect of tumor progression on peritumoral angiogenesis. We found that smaller tumors were more aggressive and that endotheliocytes and fibroblasts significantly accelerated both the proliferation and migration of tumor cells. In addition, we also first present the dynamic epithelial-mesenchymal transition process of tumor cells and the formation of vasculogenic mimicry at the EES. This work can provide insights for understanding tumor progression at the EES and offer new ideas for tumor therapy.

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.

Distinct Cerebrovascular Reactivity Patterns for Brain Radiation Necrosis

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

Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient's immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.

The role of 11C-methionine PET in patients with negative diffusion-weighted magnetic resonance imaging: correlation with histology and molecular biomarkers in operated gliomas

OBJECTIVE

To compare 11C-methionine (11C-METH) PET with diffusion-weighted MRI (DWI-MRI) diagnostic accuracy and prognostic value in patients with glioma candidate to neurosurgery.

METHODS

We collected and analyzed data from 124 consecutive patients (n = 124) investigated during preoperative work-up. Both visual and semiquantitative parameters were utilized for image analysis. The reference standard was based on histopathology. The median follow-up was 14.3 months.

RESULTS

Overall, 47 high-grade gliomas (HGG) and 77 low-grade gliomas (LGG) were diagnosed. On visual assessment, sensitivity and specificity for differentiating HGG from LGG were 80.8 and 59.7% for DWI-MRI, versus 95.7 and 41.5% for 11C-METH PET, respectively. On semiquantitative analysis, the sensitivity, specificity, and area under the curve were 78.7, 71.4, and 80.4% for SUVmax, 78.7, 70.1, and 81.1% for SUVratio, and 74.5, 61, and 76.7% for MTB (metabolic tumor burden), respectively. In patients with negative DWI-MRI and IDH-wild type, SUVmax and SUVratio were higher compared to IDH-mutated (P = 0.025 and P = 0.01, respectively). In LGG, patients with 1p/19q codeletion showed higher SUVmax (P = 0.044). In all patients with negative DWI-MRI, median PFS was longer for SUVmax <3.9 (median not reached vs 34.2 months, P = 0.004), SUVratio <2.3 (median not reached vs 21.5 months, P < 0.001), and MTB <3.1 (median not reached vs 45.7 months, P = 0.05). In LGG patients with negative DWI-MRI, only SUVratio <2.3 and MTB <3.1 were associated with longer PFS (P = 0.016 and P = 0.024, respectively).

CONCLUSION

C-METH PET was found highly sensitive for glioma differentiation and molecular characterization. In DWI-negative patients, PET parameters correlated with molecular profile were associated with clinical outcome.

Combined 18F-FET PET and diffusion kurtosis MRI in posttreatment glioblastoma: differentiation of true progression from treatment-related changes

Background

Radiological differentiation of tumor progression (TPR) from treatment-related changes (TRC) in pretreated glioblastoma is crucial. This study aimed to explore the diagnostic value of diffusion kurtosis MRI combined with information derived from O-(2-[¹⁸F]-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET for the differentiation of TPR from TRC in patients with pretreated glioblastoma.

Methods

Thirty-two patients with histomolecularly defined and pretreated glioblastoma suspected of having TPR were included in this retrospective study. Twenty-one patients were included in the TPR group, and 11 patients in the TRC group, as assessed by neuropathology or clinicoradiological follow-up. Three-dimensional (3D) regions of interest were generated based on increased ¹⁸F-FET uptake using a tumor-to-brain ratio of 1.6. Furthermore, diffusion MRI kurtosis maps were obtained from the same regions of interest using co-registered ¹⁸F-FET PET images, and advanced histogram analysis of diffusion kurtosis map parameters was applied to generated 3D regions of interest. Diagnostic accuracy was analyzed by receiver operating characteristic curve analysis and combinations of PET and MRI parameters using multivariate logistic regression.

Results

Parameters derived from diffusion MRI kurtosis maps show high diagnostic accuracy, up to 88%, for differentiating between TPR and TRC. Logistic regression revealed that the highest diagnostic accuracy of 94% (area under the curve, 0.97; sensitivity, 94%; specificity, 91%) was achieved by combining the maximum tumor-to-brain ratio of ¹⁸F-FET uptake and diffusion MRI kurtosis metrics.

Conclusions

The combined use of ¹⁸F-FET PET and MRI diffusion kurtosis maps appears to be a promising approach to improve the differentiation of TPR from TRC in pretreated glioblastoma and warrants further investigation.

Advanced Imaging Techniques for Radiotherapy Planning of Gliomas

The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.

A Critical Review of PET Tracers Used for Brain Tumor Imaging

The brain is a common site for metastases as well as primary tumors. Although evaluation of these malignancies with contrast-enhanced MR imaging defines current clinical practice, ¹⁸F-fluorodeoxyglucose (FDG)-PET has shown considerable utility in this area. In addition, many other tracers targeting various aspects of tumor biology have been developed and tested. This article discusses recent developments in PET imaging and the anticipated role of FDG and other tracers in the assessment of brain tumors.

Multi-scale optoacoustic molecular imaging of brain diseases

The ability to non-invasively visualize endogenous chromophores and exogenous probes and sensors across the entire rodent brain with the high spatial and temporal resolution has empowered optoacoustic imaging modalities with unprecedented capacities for interrogating the brain under physiological and diseased conditions. This has rapidly transformed optoacoustic microscopy (OAM) and multi-spectral optoacoustic tomography (MSOT) into emerging research tools to study animal models of brain diseases. In this review, we describe the principles of optoacoustic imaging and showcase recent technical advances that enable high-resolution real-time brain observations in preclinical models. In addition, advanced molecular probe designs allow for efficient visualization of pathophysiological processes playing a central role in a variety of neurodegenerative diseases, brain tumors, and stroke. We describe outstanding challenges in optoacoustic imaging methodologies and propose a future outlook.

Imaging challenges of immunotherapy and targeted therapy in patients with brain metastases: response, progression, and pseudoprogression

The advent of immunotherapy using immune checkpoint inhibitors (ICIs) and targeted therapy (TT) has dramatically improved the prognosis of various cancer types. However, following ICI therapy or TT-either alone (especially ICI) or in combination with radiotherapy-imaging findings on anatomical contrast-enhanced MRI can be unpredictable and highly variable, and are often difficult to interpret regarding treatment response and outcome. This review aims at summarizing the imaging challenges related to TT and ICI monotherapy as well as combined with radiotherapy in patients with brain metastases, and to give an overview on advanced imaging techniques which potentially overcome some of these imaging challenges. Currently, major evidence suggests that imaging parameters especially derived from amino acid PET, perfusion-/diffusion-weighted MRI, or MR spectroscopy may provide valuable additional information for the differentiation of treatment-induced changes from brain metastases recurrence and the evaluation of treatment response.

Evaluation of FET PET Radiomics Feature Repeatability in Glioma Patients

Simple Summary

Initial studies suggested the additional diagnostic value of amino acid positron emission tomography (PET) radiomics using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) in brain tumor patient management. However, to ensure the reliable performance of the generated FET PET radiomics models for clinical diagnostics, repeatability of radiomics features is essential. Hence, we assessed the impact of brain tumor volumes and key molecular alterations such as an isocitrate dehydrogenase (IDH) mutation on the repeatability of FET PET radiomics features in 50 newly diagnosed glioma patients. In a test–retest approach based on routinely acquired FET PET scans, we identified 297 repeatable features. The IDH genotype did not affect feature repeatability. Moreover, these robust features were able to differentiate patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust radiomics features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.

Abstract

Amino acid PET using the tracer O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) has attracted considerable interest in neurooncology. Furthermore, initial studies suggested the additional diagnostic value of FET PET radiomics in brain tumor patient management. However, the conclusiveness of radiomics models strongly depends on feature generalizability. We here evaluated the repeatability of feature-based FET PET radiomics. A test–retest analysis based on equivalent but statistically independent subsamples of FET PET images was performed in 50 newly diagnosed and histomolecularly characterized glioma patients. A total of 1,302 radiomics features were calculated from semi-automatically segmented tumor volumes-of-interest (VOIs). Furthermore, to investigate the influence of the spatial resolution of PET on repeatability, spherical VOIs of different sizes were positioned in the tumor and healthy brain tissue. Feature repeatability was assessed by calculating the intraclass correlation coefficient (ICC). To further investigate the influence of the isocitrate dehydrogenase (IDH) genotype on feature repeatability, a hierarchical cluster analysis was performed. For tumor VOIs, 73% of first-order features and 71% of features extracted from the gray level co-occurrence matrix showed high repeatability (ICC 95% confidence interval, 0.91–1.00). In the largest spherical tumor VOIs, 67% of features showed high repeatability, significantly decreasing towards smaller VOIs. The IDH genotype did not affect feature repeatability. Based on 297 repeatable features, two clusters were identified separating patients with IDH-wildtype glioma from those with an IDH mutation. Our results suggest that robust features can be obtained from routinely acquired FET PET scans, which are valuable for further standardization of radiomics analyses in neurooncology.

Imaging of Response to Radiosurgery and Immunotherapy in Brain Metastases: Quo Vadis?

Purpose of Review

This review presents an overview of how advanced imaging techniques may help to overcome shortcomings of anatomical MRI for response assessment in patients with brain metastases who are undergoing stereotactic radiosurgery, immunotherapy, or combinations thereof.

Recent Findings

Study results suggest that parameters derived from amino acid PET, diffusion- and perfusion-weighted MRI, MR spectroscopy, and newer MRI methods are particularly helpful for the evaluation of the response to radiosurgery or checkpoint inhibitor immunotherapy and provide valuable information for the differentiation of radiotherapy-induced changes such as radiation necrosis from brain metastases. The evaluation of these imaging modalities is also of great interest in the light of emerging high-throughput analysis methods such as radiomics, which allow the acquisition of additional data at a low cost.

Summary

Preliminary results are promising and should be further evaluated. Shortcomings are different levels of PET and MRI standardization, the number of patients enrolled in studies, and the monocentric and retrospective character of most studies.

[18F]-FDHT PET/CT as a tool for imaging androgen receptor expression in high-grade glioma

Background

G lioblastoma (GBM) is associated with poor overall survival. Recently, we showed that androgen receptor (AR) protein is overexpressed in 56% of GBM specimens and AR antagonists induced dose-dependent death in several GBM cell lines and significantly reduced tumor growth and prolonged the lifespan of mice implanted with human GBM. 16β-18F-fluoro-5α-dihydrotestosterone ([¹⁸F]-FDHT) is a positron emission tomography (PET) tracer used to detect AR expression in prostate and breast cancers. This study was aimed at exploring the ability of [¹⁸F]-FDHT-PET to detect AR expression in high-grade gliomas.

Methods

Twelve patients with suspected high-grade glioma underwent a regular workup and additional dynamic and static [¹⁸F]-FDHT-PET/CT. Visual and quantitative analyses of [¹⁸ F]-FDHT kinetics in the tumor and normal brain were performed. Mean and maximum (max) standardized uptake values (SUVs) were determined in selected volumes of interest. The patients had surgery or biopsy after PET/CT. AR protein was analyzed in the tumor samples by western blot. Fold change in AR expression was calculated by densitometry analysis. Correlation between imaging and AR protein samples was determined.

Results

In six of the 12 patients, [¹⁸ F]-FDHT uptake was significantly higher in the tumor than in the normal brain. These patients also had increased AR protein expression within the tumor. Pearson correlation coefficient analysis for the tumor-to-control normal brain uptake ratio in terms of SUV_mean versus AR protein expression was positive and significant (R = 0.84; P = .002).

Conclusion

[¹⁸ F]-FDHT-PET/CT could identify increased AR expression in high-grade glioma.

Feature-based PET/MRI radiomics in patients with brain tumors

Radiomics allows the extraction of quantitative features from medical images such as CT, MRI, or PET, thereby providing additional, potentially relevant diagnostic information for clinical decision-making. Because the computation of these features is performed highly automated on medical images acquired during routine follow-up, radiomics offers this information at low cost. Further, the radiomics features can be used alone or combined with other clinical or histomolecular parameters to generate predictive or prognostic mathematical models. These models can then be applied for various important diagnostic indications in neuro-oncology, for example, to noninvasively predict relevant biomarkers in glioma patients, to differentiate between treatment-related changes and local brain tumor relapse, or to predict treatment response. In recent years, amino acid PET has become an important diagnostic tool in patients with brain tumors. Therefore, the number of studies in patients with brain tumors investigating the potential of PET radiomics or combined PET/MRI radiomics is steadily increasing. This review summarizes current research regarding feature-based PET as well as combined PET/MRI radiomics in neuro-oncology.

Comparison of [18F]Fluoroethyltyrosine PET and Sodium MRI in Cerebral Gliomas: a Pilot Study

PURPOSE

Positron emission tomography (PET) using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) improves the diagnostics of cerebral gliomas compared with conventional magnetic resonance imaging (MRI). Sodium MRI is an evolving method to assess tumor metabolism. In this pilot study, we explored the relationship of [¹⁸F]FET-PET and sodium MRI in patients with cerebral gliomas in relation to the mutational status of the enzyme isocitrate dehydrogenase (IDH).

PROCEDURES

Ten patients with untreated cerebral gliomas and one patient with a recurrent glioblastoma (GBM) were investigated by dynamic [¹⁸F]FET-PET and sodium MRI using an enhanced simultaneous single-quantum- and triple-quantum-filtered imaging of ²³Na (SISTINA) sequence to estimate total (NaT), weighted non-restricted (NaNR, mainly extracellular), and restricted (NaR, mainly intracellular) sodium in tumors and normal brain tissue. [¹⁸F]FET uptake and sodium parameters in tumors with a different IDH mutational status were compared. After biopsy or resection, histology and the IDH mutational status were determined neuropathologically.

RESULTS

NaT (p = 0.05), tumor-to-brain ratios (TBR) of NaT (p = 0.02), NaNR (p = 0.003), and the ratio of NaT/NaR (p < 0.001) were significantly higher in IDH-mutated than in IDH-wild-type gliomas (n = 5 patients each) while NaR was significantly lower in IDH-mutated gliomas (p = 0.01). [¹⁸F]FET parameters (TBR, time-to-peak) were not predictive of IDH status in this small cohort of patients. There was no obvious relationship between sodium distribution and [¹⁸F]FET uptake. The patient with a recurrent GBM exhibited an additional radiation injury with strong abnormalities in sodium MRI.

CONCLUSIONS

Sodium MRI appears to be more strongly related to the IDH mutational status than are [¹⁸F]FET-PET parameters. A further evaluation of the combination of the two methods in a larger group of high- and low-grade gliomas seems promising.

[18F]FET PET Uptake Indicates High Tumor and Low Necrosis Content in Brain Metastasis

Simple Summary

Various types of cancers can lead to brain metastasis. Treatment strategies have improved substantially in the past decade, leading to longer survival in many cases, but also to new diagnostic challenges. Being able to locate those parts of a lesion suspicious for brain metastasis that contain the highest concentrations of viable tumor cells can be crucial, e.g., to obtain a precise diagnosis via targeted biopsies or to differentiate recurring tumor from dead tissue after treatment. Positron emission tomography (PET) imaging has the potential to provide this kind of information. However, studies relating PET findings to actual tissue properties are sparse. The aim of this study was to investigate the association of PET imaging with microscopic tissue properties in samples obtained neurosurgically from brain metastases. Our findings can improve the planning and yield of biopsies from brain metastases, and they may inform future studies aimed at improving the discrimination of recurring from dead tumor in treated brain metastases using PET.

Abstract

Amino acid positron emission tomography (PET) has been employed in the management of brain metastases. Yet, histopathological correlates of PET findings remain poorly understood. We investigated the relationship of O-(2-[¹⁸F]Fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET, magnetic resonance imaging (MRI), and histology in brain metastases. Fifteen patients undergoing brain metastasis resection were included prospectively. Using intraoperative navigation, 39 targeted biopsies were obtained from parts of the metastases that were either PET-positive or negative and MRI-positive or negative. Tumor and necrosis content, proliferation index, lymphocyte infiltration, and vascularization were determined histopathologically. [¹⁸F]FET PET had higher specificity than MRI (66% vs. 56%) and increased sensitivity for tumor from 73% to 93% when combined with MRI. Tumor content per sample increased with PET uptake (r_s = 0.3, p = 0.045), whereas necrosis content decreased (r_s = −0.4, p = 0.014). PET-positive samples had more tumor (median: 75%; interquartile range: 10–97%; p = 0.016) than PET-negative samples. The other investigated histological properties were not correlated with [¹⁸F]FET PET intensity. Tumors were heterogeneous at the levels of imaging and histology. [¹⁸F]FET PET can be a valuable tool in the management of brain metastases. In biopsies, one should aim for PET hotspots to increase the chance for retrieval of samples with high tumor cell concentrations. Multiple biopsies should be performed to account for intra-tumor heterogeneity. PET could be useful for differentiating treatment-related changes (e.g., radiation necrosis) from tumor recurrence.

Improved detection of diffuse glioma infiltration with imaging combinations: a diagnostic accuracy study

Background

Surgical resection and irradiation of diffuse glioma are guided by standard MRI: T2/fluid attenuated inversion recovery (FLAIR)–weighted MRI for non-enhancing and T1-weighted gadolinium-enhanced (T1G) MRI for enhancing gliomas. Amino acid PET has been suggested as the new standard. Imaging combinations may improve standard MRI and amino acid PET. The aim of the study was to determine the accuracy of imaging combinations to detect glioma infiltration.

Methods

We included 20 consecutive adults with newly diagnosed non-enhancing glioma (7 diffuse astrocytomas, isocitrate dehydrogenase [IDH] mutant; 1 oligodendroglioma, IDH mutant and 1p/19q codeleted; 1 glioblastoma IDH wildtype) or enhancing glioma (glioblastoma, 9 IDH wildtype and 2 IDH mutant). Standardized preoperative imaging (T1-, T2-, FLAIR-weighted, and T1G MRI, perfusion and diffusion MRI, MR spectroscopy and O-(2-[18F]-fluoroethyl)-L-tyrosine ([¹⁸F]FET) PET) was co-localized with multiregion stereotactic biopsies preceding resection. Tumor presence in the biopsies was assessed by 2 neuropathologists. Diagnostic accuracy was determined using receiver operating characteristic analysis.

Results

A total of 174 biopsies were obtained (63 from 9 non-enhancing and 111 from 11 enhancing gliomas), of which 129 contained tumor (50 from non-enhancing and 79 from enhancing gliomas). In enhancing gliomas, the combination of apparent diffusion coefficient (ADC) with [¹⁸F]FET PET (area under the curve [AUC], 95% CI: 0.89, 0.79‒0.99) detected tumor better than T1G MRI (0.56, 0.39‒0.72; P < 0.001) and [¹⁸F]FET PET (0.76, 0.66‒0.86; P = 0.001). In non-enhancing gliomas, no imaging combination detected tumor significantly better than standard MRI. FLAIR-weighted MRI had an AUC of 0.81 (0.65–0.98) compared with 0.69 (0.56–0.81; P = 0.019) for [¹⁸F]FET PET.

Conclusion

Combining ADC and [¹⁸F]FET PET detects glioma infiltration better than standard MRI and [¹⁸F]FET PET in enhancing gliomas, potentially enabling better guidance of local therapy.

A design strategy for D–A conjugated polymers for NIR-II fluorescence imaging

The development of bioimaging technology in recent years has shown that second near-infrared (NIR-II) fluorescence imaging (FI) is gradually replacing the traditional visible light and first near-infrared (NIR-I) FI.

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

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

Current landscape and future perspectives in preclinical MR and PET imaging of brain metastasis

Brain metastasis (BM) is a major cause of cancer patient morbidity. Clinical magnetic resonance imaging (MRI) and positron emission tomography (PET) represent important resources to assess tumor progression and treatment responses. In preclinical research, anatomical MRI and to some extent functional MRI have frequently been used to assess tumor progression. In contrast, PET has only to a limited extent been used in animal BM research. A considerable culprit is that results from most preclinical studies have shown little impact on the implementation of new treatment strategies in the clinic. This emphasizes the need for the development of robust, high-quality preclinical imaging strategies with potential for clinical translation. This review focuses on advanced preclinical MRI and PET imaging methods for BM, describing their applications in the context of what has been done in the clinic. The strengths and shortcomings of each technology are presented, and recommendations for future directions in the development of the individual imaging modalities are suggested. Finally, we highlight recent developments in quantitative MRI and PET, the use of radiomics and multimodal imaging, and the need for a standardization of imaging technologies and protocols between preclinical centers.

As Evidence-Based Tumorigenic Role of Epstein-Barr Virus miR-BART1-3p in Neurological Tumors

INTRODUCTION

Central nervous system tumors are a diverse group of tumors that account for 2% of all adult cancers and 17% of childhood malignancies. Several internal and external risk factors are involved in the development of this cancer such as viral infections. The aim of this study was to the determination of the EBV infection frequency and the expression level of miR-122 and miR-BART in CNS tumors samples.

METHODS

One hundred and thirty-eight  fresh tissue sample (106 case and 32 control) was collected from CNS specimens. The presence of Epstein-Barr virus (EBV) DNA was examined by PCR assay and the expression level of miR-122 and miR-BART were evaluated by using real-time PCR assay in CNS tissue samples.

RESULTS

EBV DNA was detected in 17% (18 of 106) of tumors tissue samples and 6.4% (2 of 32) of control samples. according to results, there was a significant relationship between the presence of EBV-DNA with CNS tumors. Additionally, the expression level of miR-122 was significantly downregulated in the EBV-positive sample compared to that of the EBV-negative sample. Also, the level of EBV-BART1-3p expression was significantly higher in EBV-positive tumors samples than EBV-positive normal samples.

CONCLUSION

The results of this study suggest that the EBV could change the condition of cancer cells by altering the expression of miR-122 and EBV-BART1-3p and maybe contribute to the development of cancer cells. However, the role of viral infections in CNS cancer requires further studies. <br />.

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.

Multiple positron emission tomography tracers for use in the classification of gliomas according to the 2016 World Health Organization criteria

Background

The molecular diagnosis of gliomas such as isocitrate dehydrogenase (IDH) status (wild-type [wt] or mutation [mut]) is especially important in the 2016 World Health Organization (WHO) classification. Positron emission tomography (PET) has afforded molecular and metabolic diagnostic imaging. The present study aimed to define the interrelationship between the 2016 WHO classification of gliomas and the integrated data from PET images using multiple tracers, including ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG), ¹¹C-methionine (¹¹C-MET), ¹⁸F-fluorothymidine (¹⁸F-FLT), and ¹⁸F-fluoromisonidazole (¹⁸F-FMISO).

Methods

This retrospective, single-center study comprised 113 patients with newly diagnosed glioma based on the 2016 WHO criteria. Patients were divided into 4 glioma subtypes (Mut, Codel, Wt, and glioblastoma multiforme [GBM]). Tumor standardized uptake value (SUV) divided by mean normal cortical SUV (tumor–normal tissue ratio [TNR]) was calculated for ¹⁸F-FDG, ¹¹C-MET, and ¹⁸F-FLT. Tumor–blood SUV ratio (TBR) was calculated for ¹⁸F-FMISO. To assess the diagnostic accuracy of PET tracers in distinguishing glioma subtypes, a comparative analysis of TNRs and TBR as well as the metabolic tumor volume (MTV) were calculated by Scheffe's multiple comparison procedure for each PET tracer following the Kruskal–Wallis test.

Results

The differences in mean ¹⁸F-FLT TNR and ¹⁸F-FMISO TBR were significant between GBM and other glioma subtypes (P < .001). Regarding the comparison between Gd-T1WI volumes and ¹⁸F-FLT MTVs or ¹⁸F-FMISO MTVs, we identified significant differences between Wt and Mut or Codel (P < .01).

Conclusion

Combined administration of 4 PET tracers might aid in the preoperative differential diagnosis of gliomas according to the 2016 WHO criteria.

Sequential implementation of DSC-MR perfusion and dynamic [18F]FET PET allows efficient differentiation of glioma progression from treatment-related changes

Purpose

Perfusion-weighted MRI (PWI) and O-(2-[¹⁸F]fluoroethyl-)-l-tyrosine ([¹⁸F]FET) PET are both applied to discriminate tumor progression (TP) from treatment-related changes (TRC) in patients with suspected recurrent glioma. While the combination of both methods has been reported to improve the diagnostic accuracy, the performance of a sequential implementation has not been further investigated. Therefore, we retrospectively analyzed the diagnostic value of consecutive PWI and [¹⁸F]FET PET.

Methods

We evaluated 104 patients with WHO grade II–IV glioma and suspected TP on conventional MRI using PWI and dynamic [¹⁸F]FET PET. Leakage corrected maximum relative cerebral blood volumes (rCBV_max) were obtained from dynamic susceptibility contrast PWI. Furthermore, we calculated static (i.e., maximum tumor to brain ratios; TBR_max) and dynamic [¹⁸F]FET PET parameters (i.e., Slope). Definitive diagnoses were based on histopathology (n = 42) or clinico-radiological follow-up (n = 62). The diagnostic performance of PWI and [¹⁸F]FET PET parameters to differentiate TP from TRC was evaluated by analyzing receiver operating characteristic and area under the curve (AUC).

Results

Across all patients, the differentiation of TP from TRC using rCBV_max or [¹⁸F]FET PET parameters was moderate (AUC = 0.69–0.75; p < 0.01). A rCBV_max cutoff > 2.85 had a positive predictive value for TP of 100%, enabling a correct TP diagnosis in 44 patients. In the remaining 60 patients, combined static and dynamic [¹⁸F]FET PET parameters (TBR_max, Slope) correctly discriminated TP and TRC in a significant 78% of patients, increasing the overall accuracy to 87%. A subgroup analysis of isocitrate dehydrogenase (IDH) mutant tumors indicated a superior performance of PWI to [¹⁸F]FET PET (AUC = 0.8/< 0.62, p < 0.01/≥ 0.3).

Conclusion

While marked hyperperfusion on PWI indicated TP, [¹⁸F]FET PET proved beneficial to discriminate TP from TRC when PWI remained inconclusive. Thus, our results highlight the clinical value of sequential use of PWI and [¹⁸F]FET PET, allowing an economical use of diagnostic methods. The impact of an IDH mutation needs further investigation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-020-05114-0.

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.

Hybrid PET-MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges

(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of ¹⁸F-fluorocholine (FCho) and ¹⁸fluoro-L-phenylalanine (FDOPA) PET–MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET–MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET–MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.

Distributed changes of the functional connectome in patients with glioblastoma

Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do not necessarily follow obvious anatomical patterns and the current understanding of this interrelation is limited. In this study, we used resting-state functional magnetic resonance imaging to evaluate changes in global functional connectivity patterns in 15 patients with glioblastoma. For six patients we followed longitudinal trajectories of their functional connectome and structural tumour evolution using bi-monthly follow-up scans throughout treatment and disease progression. In all patients, unilateral tumour lesions were associated with inter-hemispherically symmetric network alterations, and functional proximity of tumour location was stronger linked to distributed network deterioration than anatomical distance. In the longitudinal subcohort of six patients, we observed patterns of network alterations with initial transient deterioration followed by recovery at first follow-up, and local network deterioration to precede structural tumour recurrence by two months. In summary, the impact of focal glioblastoma lesions on the functional connectome is global and linked to functional proximity rather than anatomical distance to tumour regions. Our findings further suggest a relevance for functional network trajectories as a possible means supporting early detection of tumour recurrence.

Importance and Evidence of Extent of Resection in Glioblastoma

Maximal safe resection is an essential part of the multidisciplinary care of patients with glioblastoma. A growing body of data shows that gross total resection is an independent prognostic factor associated with improved clinical outcome. The relationship between extent of glioblastoma (GB) resection and clinical benefit depends critically on the balance between cytoreduction and avoiding neurologic morbidity. The definition of the extent of tumor resection, how this is best measured pre- and postoperatively, and its relation to volume of residual tumor is still discussed. We review the literature supporting extent of resection in GB, highlighting the importance of a standardized definition and measurement of extent of resection to allow greater collaboration in research projects and trials. Recent developments in neurosurgical techniques and technologies focused on maximizing extent of resection and safety are discussed.

Predicting Survival in Glioblastoma Patients Using Diffusion MR Imaging Metrics-A Systematic Review

Simple Summary

An accurate survival analysis is crucial for disease management in glioblastoma (GBM) patients. Due to the ability of the diffusion MRI techniques of providing a quantitative assessment of GBM tumours, an ever-growing number of studies aimed at investigating the role of diffusion MRI metrics in survival prediction of GBM patients. Since the role of diffusion MRI in prediction and evaluation of survival outcomes has not been fully addressed and results are often controversial or unsatisfactory, we performed this systematic review in order to collect, summarize and evaluate all studies evaluating the role of diffusion MRI metrics in predicting survival in GBM patients. We found that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Abstract

Despite advances in surgical and medical treatment of glioblastoma (GBM), the medium survival is about 15 months and varies significantly, with occasional longer survivors and individuals whose tumours show a significant response to therapy with respect to others. Diffusion MRI can provide a quantitative assessment of the intratumoral heterogeneity of GBM infiltration, which is of clinical significance for targeted surgery and therapy, and aimed at improving GBM patient survival. So, the aim of this systematic review is to assess the role of diffusion MRI metrics in predicting survival of patients with GBM. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, a systematic literature search was performed to identify original articles since 2010 that evaluated the association of diffusion MRI metrics with overall survival (OS) and progression-free survival (PFS). The quality of the included studies was evaluated using the QUIPS tool. A total of 52 articles were selected. The most examined metrics were associated with the standard Diffusion Weighted Imaging (DWI) (34 studies) and Diffusion Tensor Imaging (DTI) models (17 studies). Our findings showed that quantitative diffusion MRI metrics provide useful information for predicting survival outcomes in GBM patients, mainly in combination with other clinical and multimodality imaging parameters.

Relaxometry and quantification in sodium MRI of cerebral gliomas: A FET-PET and MRI small-scale study

Sodium MRI is a promising method for assessing the metabolic properties of brain tumours. In a recent study, a strong relationship between semi-quantitative abnormalities in sodium MRI and the mutational status of the isocitrate dehydrogenase enzyme (IDH) with untreated cerebral gliomas was observed. Here, sodium relaxometry in brain tumour tissue was investigated in relation to molecular markers in order to reveal quantitative sodium tissue parameters and the differences between healthy tissue and brain tumour. The previous semi-quantitative approach is extended by use of suitable relaxometry methods accompanied by numerical simulation to achieve detailed quantitative analysis of intra- and extracellular sodium concentration using an enhanced SISTINA sequence at 4 T. Using optimised techniques, biexponential sodium relaxation times in tumour (T*_2f , T*_2s ) and in healthy contralateral brain tissue (T*_2f,CL , T*_2s,CL ) were estimated in 10 patients, along with intracellular sodium molar fractions (χ, χ_CL ), volume fractions (η, η_CL ) and concentrations (ρ_in , ρ_in,CL ). The total sodium tissue concentrations (ρ_T , ρ_T,CL ) were also estimated. The ratios T*_2f /T*_2f,CL (P = .05), η/η_CL (P = .02) and χ/χ_CL (P = .02) were significantly lower in IDH mutated than in IDH wildtype gliomas (n = 4 and n = 5 patients, respectively). The Wilcoxon rank-sum test was used to compare sodium MRI parameters in patients with and without IDH mutation. Thus, quantitative analysis of relaxation rates, intra- and extracellular sodium concentrations, intracellular molar and volume fractions based on enhanced SISTINA confirmed a relationship between abnormalities in sodium parameters and the IDH mutational status in cerebral gliomas, hence catering for the potential to provide further insights into the status of the disease.

Twofold improved tumor-to-brain contrast using a novel T1 relaxation-enhanced steady-state (T1RESS) MRI technique

A technique that provides more accurate cancer detection would be of great value. Toward this end, we developed T1 relaxation-enhanced steady-state (T₁RESS), a novel magnetic resonance imaging (MRI) pulse sequence that enables the flexible modulation of T1 weighting and provides the unique feature that intravascular signals can be toggled on and off in contrast-enhanced scans. T₁RESS makes it possible to effectively use an MRI technique with improved signal-to-noise ratio efficiency for cancer imaging. In a proof-of-concept study, "dark blood" unbalanced T₁RESS provided a twofold improvement in tumor-to-brain contrast compared with standard techniques, whereas balanced T₁RESS greatly enhanced vascular detail. In conclusion, T₁RESS represents a new MRI technique with substantial potential value for cancer imaging, along with a broad range of other clinical applications.

Treatment Monitoring of Immunotherapy and Targeted Therapy Using 18F-FET PET in Patients with Melanoma and Lung Cancer Brain Metastases: Initial Experiences

We investigated the value of O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) PET for treatment monitoring of immune checkpoint inhibition (ICI) or targeted therapy (TT) alone or in combination with radiotherapy in patients with brain metastasis (BM) since contrast-enhanced MRI often remains inconclusive. Methods: We retrospectively identified 40 patients with 107 BMs secondary to melanoma (n = 29 with 75 BMs) or non-small cell lung cancer (n = 11 with 32 BMs) treated with ICI or TT who had ¹⁸F-FET PET (n = 60 scans) for treatment monitoring from 2015 to 2019. Most patients (n = 37; 92.5%) had radiotherapy during the course of the disease. In 27 patients, ¹⁸F-FET PET was used to differentiate treatment-related changes from BM relapse after ICI or TT. In 13 patients, ¹⁸F-FET PET was performed for response assessment to ICI or TT using baseline and follow-up scans (median time between scans, 4.2 mo). In all lesions, static and dynamic ¹⁸F-FET PET parameters were obtained (i.e., mean tumor-to-brain ratios [TBR], time-to-peak values). Diagnostic accuracies of PET parameters were evaluated by receiver-operating-characteristic analyses using the clinical follow-up or neuropathologic findings as a reference. Results: A TBR threshold of 1.95 differentiated BM relapse from treatment-related changes with an accuracy of 85% (P = 0.003). Metabolic responders to ICI or TT on ¹⁸F-FET PET had a significantly longer stable follow-up (threshold of TBR reduction relative to baseline, ≥10%; accuracy, 82%; P = 0.004). Furthermore, at follow-up, time to peak in metabolic responders increased significantly (P = 0.019). Conclusion: ¹⁸F-FET PET may add valuable information for treatment monitoring in BM patients treated with ICI or TT.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

11C- and 18F-labelled tryptophans as PET-tracers for imaging of altered tryptophan metabolism in age-associated disorders

The ageing of the world’s population is the result of increased life expectancy observed in almost all countries throughout the world. Consequently, a rising tide of ageing-associated disorders, like cancer and neurodegenerative diseases, represents one of the main global challenges of the 21st century. The ability of mankind to overcome these challenges is directly dependent on the capability to develop novel methods for therapy and diagnosis of age-associated diseases. One hallmark of age-related pathologies is an altered tryptophan metabolism. Numerous pathological processes including neurodegenerative and neurological diseases like epilepsy, Parkinson’s and Alzheimer’s diseases, cancer and diabetes exhibit marked changes in tryptophan metabolism. Visualization of key processes of tryptophan metabolic pathways, especially using positron emission tomography (PET) and related hybrid methods like PET/CT and PET/MRI, can be exploited to early detect the aforementioned disorders with considerable accuracy, allowing appropriate and timely treatment of patients. Here we review the published 11C- and 18F-labelled tryptophans with respect to the production and also preclinical and clinical evaluation as PET-tracers for visualization of different branches of tryptophan metabolism.

The bibliography includes 159 references.

Pseudoprogression and hyperprogression in lung cancer: a comprehensive review of literature

PURPOSE

Immune checkpoint inhibitors are associated with clinical benefit in lung cancer. However, response patterns to immunotherapy, including pseudoprogression and hyperprogression, are difficult to diagnose, and their mechanisms remain unclear. This review aimed to describe two response patterns observed in lung cancer, namely pseudoprogression and hyperprogression, including their epidemiology, diagnostic characteristics, and plausible mechanisms.

METHODS

We performed a comprehensive literature search in the PubMed database, using keywords "pseudoprogression", "hyperprogression", and "lung cancer", among others. The literature was examined for pseudoprogression and hyperprogression characteristics and plausible mechanisms.

RESULTS

Pseudoprogression manifests in multiple forms; however, the immune system-related response criteria and biopsy data are helpful to make accurate diagnosis. Serological biomarkers, such as neutrophil-to-lymphocyte ratio (NLR) and circulating tumor DNA (ctDNA), might help distinguish pseudoprogression from true progression. The incidence of hyperprogression ranges within 5-19.2%, depending on definition. The unique response pattern of rapid progression is observed not only with immunotherapy, but also with other treatment regimens. Molecular mutations and amplifications may result in hyperprogression; however, the exact mechanism remains unclear.

CONCLUSION

Atypical response patterns, such as pseudoprogression and hyperprogression, are increasingly common in clinical practice. Immune-related response criteria can help diagnose pseudoprogression. Molecular mechanisms of hyperprogression remain unclear. Biomarkers for pseudoprogression and hyperprogression are required.

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.

Brain Metastasis Recurrence Versus Radiation Necrosis: Evaluation and Treatment

Radiation necrosis (RN) occurs in 5% to 25% of patients with brain metastases treated with stereotactic radiosurgery. RN must be distinguished from recurrent tumor to determine appropriate treatment. Stereotactic biopsy remains the gold standard for identifying RN. Initial treatment of RN often involves management of edema using corticosteroids, antiangiogenic therapies, and hyperbaric oxygen therapy. For refractory symptoms, surgical resection can be considered. Minimally invasive stereotactic laser ablation has the benefit of providing tissue diagnosis and treating RN or recurrent tumor with similar efficacy. Laser ablation should be considered for lesions in need of intervention where the diagnosis requires tissue confirmation.

Photopenic defects on O-(2-[18F]-fluoroethyl)-L-tyrosine PET: clinical relevance in glioma patients

BACKGROUND

O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET has a sensitivity of more than 90% to detect gliomas. In the remaining small fraction of gliomas without increased tracer uptake, some tumors even show photopenic defects whose clinical significance is unclear.

METHODS

Glioma patients with a negative FET PET scan prior to neuropathological confirmation were identified retrospectively. Gliomas were rated visually as (i) having indifferent FET uptake or (ii) photopenic, if FET uptake was below background activity. FET uptake in the area of signal hyperintensity on the T2/fluid attenuated inversion recovery-weighted MRI was evaluated by mean standardized uptake value (SUV) and mean tumor-to-brain ratio (TBR). The progression-free survival (PFS) of photopenic gliomas was compared with that of gliomas with indifferent FET uptake.

RESULTS

Of 100 FET-negative gliomas, 40 cases with photopenic defects were identified. Fifteen of these 40 cases (38%) had World Health Organization (WHO) grades III and IV gliomas. FET uptake in photopenic gliomas was significantly decreased compared with both the healthy-appearing brain tissue (SUV, 0.89 ± 0.26 vs 1.08 ± 0.23; P < 0.001) and gliomas with indifferent FET uptake (TBR, 0.82 ± 0.09 vs 0.96 ± 0.13; P < 0.001). Irrespective of the applied treatment, isocitrate dehydrogenase (IDH)-mutated WHO grade II diffuse astrocytoma patients with indifferent FET uptake (n = 25) had a significantly longer PFS than patients with IDH-mutated diffuse astrocytomas (WHO grade II) with photopenic defects (n = 11) (51 vs 24 mo; P = 0.027). The multivariate survival analysis indicated that photopenic defects predict an unfavorable PFS (P = 0.009).

CONCLUSION

Photopenic gliomas in negative FET PET scans should be managed more actively, as they seem to have a higher risk of harboring a higher-grade glioma and an unfavorable outcome.

Glucose Loading Enhances the Value of 18F-FDG PET/CT for the Characterization and Delineation of Cerebral Gliomas

This study aimed to assess how to enhance the value of ¹⁸F-Fluorodeoxyglucose (FDG) PET/CTs for glioma grading and better delineation of the tumor boundary by glucose loading. In mouse models of brain tumor using U87MG cells, ¹⁸F-FDG-PET images were obtained after fasting and after glucose loading. There was a significant difference in the tumor-to-normal cortex-uptake ratio (TNR) between the fasting and glucose-loading scans. ¹⁴C-2-Deoxy-D-glucose (¹⁴C-DG) uptake was measured in vitro using U87MG, U373MG and primary neurons cultured with different concentrations of glucose. The tumor-to-neuron ratio of ¹⁴C-DG uptake increased with up to 10 mM of glucose. Finally, 10 low-grade and 17 high-grade glioma patients underwent fasting and glucose loading ¹⁸F-FDG PET/CT and the TNR was compared between scans. The effect of glucose loading was significant in high-grade but not in low-grade gliomas. The receiver operating characteristic curve analyses with a cut-off TNR of 0.81 showed a higher area under the curve after glucose loading than fasting for differentiating low-grade versus high-grade gliomas. In addition, the glucose loading PET/CT was more useful than the fasting PET/CT for the discrimination of oligodendrogliomas from IDH-wildtype glioblastomas. Glucose loading resulted in a greater reduction in ¹⁸F-FDG uptake in the normal cortex than in tumors, which increases the usefulness of ¹⁸F-FDG PET/CT for grading.

TSPO-PET and diffusion-weighted MRI for imaging a mouse model of infiltrative human glioma

BACKGROUND

Glioblastoma (GBM) is the most devastating brain tumor. Despite the use of multimodal treatments, most patients relapse, often due to the highly invasive nature of gliomas. However, the detection of glioma infiltration remains challenging. The aim of this study was to assess advanced PET and MRI techniques for visualizing biological activity and infiltration of the tumor.

METHODS

Using multimodality imaging, we investigated [18F]DPA-714, a radiotracer targeting the 18 kDa translocator protein (TSPO), [18F]FET PET, non-Gaussian diffusion MRI (apparent diffusion coefficient, kurtosis), and the S-index, a composite diffusion metric, to detect tumor infiltration in a human invasive glioma model. In vivo imaging findings were confirmed by autoradiography and immunofluorescence.

RESULTS

Increased tumor-to-contralateral [18F]DPA-714 uptake ratios (1.49 ± 0.11) were found starting 7 weeks after glioma cell implantation. TSPO-PET allowed visualization of glioma infiltration into the contralateral hemisphere 2 weeks earlier compared with the clinically relevant biomarker for biological glioma activity [18F]FET. Diffusion-weighted imaging (DWI), in particular kurtosis, was more sensitive than standard T2-weighted MRI to detect differences between the glioma-bearing and the contralateral hemisphere at 5 weeks. Immunofluorescence data reflect in vivo findings. Interestingly, labeling for tumoral and stromal TSPO indicates a predominant expression of TSPO by tumor cells.

CONCLUSION

These results suggest that advanced PET and MRI methods, such as [18F]DPA-714 and DWI, may be superior to standard imaging methods to visualize glioma growth and infiltration at an early stage.

State-of-the-art imaging for glioma surgery

Diffuse gliomas are infiltrative primary brain tumors with a poor prognosis despite multimodal treatment. Maximum safe resection is recommended whenever feasible. The extent of resection (EOR) is positively correlated with survival. Identification of glioma tissue during surgery is difficult due to its diffuse nature. Therefore, glioma resection is imaging-guided, making the choice for imaging technique an important aspect of glioma surgery. The current standard for resection guidance in non-enhancing gliomas is T2 weighted or T2w-fluid attenuation inversion recovery magnetic resonance imaging (MRI), and in enhancing gliomas T1-weighted MRI with a gadolinium-based contrast agent. Other MRI sequences, like magnetic resonance spectroscopy, imaging modalities, such as positron emission tomography, as well as intraoperative imaging techniques, including the use of fluorescence, are also available for the guidance of glioma resection. The neurosurgeon’s goal is to find the balance between maximizing the EOR and preserving brain functions since surgery-induced neurological deficits result in lower quality of life and shortened survival. This requires localization of important brain functions and white matter tracts to aid the pre-operative planning and surgical decision-making. Visualization of brain functions and white matter tracts is possible with functional MRI, diffusion tensor imaging, magnetoencephalography, and navigated transcranial magnetic stimulation. In this review, we discuss the current available imaging techniques for the guidance of glioma resection and the localization of brain functions and white matter tracts.

Radiomics in neuro-oncology: Basics, workflow, and applications

Over the last years, the amount, variety, and complexity of neuroimaging data acquired in patients with brain tumors for routine clinical purposes and the resulting number of imaging parameters have substantially increased. Consequently, a timely and cost-effective evaluation of imaging data is hardly feasible without the support of methods from the field of artificial intelligence (AI). AI can facilitate and shorten various time-consuming steps in the image processing workflow, e.g., tumor segmentation, thereby optimizing productivity. Besides, the automated and computer-based analysis of imaging data may help to increase data comparability as it is independent of the experience level of the evaluating clinician. Importantly, AI offers the potential to extract new features from the routinely acquired neuroimages of brain tumor patients. In combination with patient data such as survival, molecular markers, or genomics, mathematical models can be generated that allow, for example, the prediction of treatment response or prognosis, as well as the noninvasive assessment of molecular markers. The subdiscipline of AI dealing with the computation, identification, and extraction of image features, as well as the generation of prognostic or predictive mathematical models, is termed radiomics. This review article summarizes the basics, the current workflow, and methods used in radiomics with a focus on feature-based radiomics in neuro-oncology and provides selected examples of its clinical application.

Applications of radiomics and machine learning for radiotherapy of malignant brain tumors

Background

Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use of radiotherapy in patients with malignant brain tumors.

Methods

This study is based on comprehensive literature research on machine learning and radiomics analyses in neuroimaging and their potential application for radiotherapy in patients with malignant glioma or brain metastases.

Results

Feature-based radiomics and deep learning-based machine learning methods can be used to improve brain tumor diagnostics and automate various steps of radiotherapy planning. In glioma patients, important applications are the determination of WHO grade and molecular markers for integrated diagnosis in patients not eligible for biopsy or resection, automatic image segmentation for target volume planning, prediction of the location of tumor recurrence, and differentiation of pseudoprogression from actual tumor progression. In patients with brain metastases, radiomics is applied for additional detection of smaller brain metastases, accurate segmentation of multiple larger metastases, prediction of local response after radiosurgery, and differentiation of radiation injury from local brain metastasis relapse. Importantly, high diagnostic accuracies of 80–90% can be achieved by most approaches, despite a large variety in terms of applied imaging techniques and computational methods.

Conclusion

Clinical application of automated image analyses based on radiomics and artificial intelligence has a great potential for improving radiotherapy in patients with malignant brain tumors. However, a common problem associated with these techniques is the large variability and the lack of standardization of the methods applied.

Optimization of time frame binning for FDOPA uptake quantification in glioma

Introduction

3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (FDOPA) uptake quantification in glioma assessment can be distorted using a non-optimal time frame binning of time-activity curves (TAC). Under-sampling or over-sampling dynamic PET images induces significant variations on kinetic parameters quantification. We aimed to optimize temporal time frame binning for dynamic FDOPA PET imaging.

Methods

Fourteen patients with 33 tumoral TAC with biopsy-proven gliomas were analysed. The mean SUVmax tumor-to-brain ratio (TBRmax) were compared at 20 min and 35 min post-injection (p.i). Five different time frame samplings within 20 min were compared: 11x10sec-6x15sec-5x20sec-3x300sec; 8x15sec– 2x30sec– 2x60sec– 3x300sec; 6x20sec– 8x60sec– 2x300sec; 10x30sec– 3x300sec and 4x45sec– 3x90sec– 5x150sec. The reversible single-tissue compartment model with blood volume parameter (VB) was selected using the Akaike information criterion. K1 values extracted from 1024 noisy simulated TAC using Monte Carlo method from the 5 different time samplings were compared to a target K1 value as the objective, which is the average of the K1 values extracted from the 33 lesions using an imaging-derived input function for each patient.

Results

The mean TBRmax was significantly higher at 20 min p.i. than at 35 min p.i (respectively 1.4 +/- 0.8 and 1.2 +/- 0.6; p <0.001). The target K1 value was 0.161 mL/ccm/min. The 8x15sec– 2x30sec– 2x60sec– 3x300sec time sampling was the optimal time frame binning. K1 values extracted using this optimal time frame binning were significantly different with K1 values extracted from the other time frame samplings, except with K1 values obtained using the 11x10sec– 6x15sec –5x20sec-3x300sec time frame binning.

Conclusions

This optimal sampling schedule design (8x15sec– 2x30sec– 2x60sec– 3x300sec) could be used to minimize bias in quantification of FDOPA uptake in glioma using kinetic analysis.