Advances in neuro-oncology imaging

Unsupervised model for structure segmentation applied to brain computed tomography

This article presents an unsupervised method for segmenting brain computed tomography scans. The proposed methodology involves image feature extraction and application of similarity and continuity constraints to generate segmentation maps of the anatomical head structures. Specifically designed for real-world datasets, this approach applies a spatial continuity scoring function tailored to the desired number of structures. The primary objective is to assist medical experts in diagnosis by identifying regions with specific abnormalities. Results indicate a simplified and accessible solution, reducing computational effort, training time, and financial costs. Moreover, the method presents potential for expediting the interpretation of abnormal scans, thereby impacting clinical practice. This proposed approach might serve as a practical tool for segmenting brain computed tomography scans, and make a significant contribution to the analysis of medical images in both research and clinical settings.

Liquid biopsy for improving diagnosis and monitoring of CNS lymphomas: A RANO review

BACKGROUND

The utility of liquid biopsies is well documented in several extracranial and intracranial (brain/leptomeningeal metastases, gliomas) tumors.

METHODS

The RANO (Response Assessment in Neuro-Oncology) group has set up a multidisciplinary Task Force to critically review the role of blood and cerebrospinal fluid (CSF)-liquid biopsy in CNS lymphomas, with a main focus on primary central nervous system lymphomas (PCNSL).

RESULTS

Several clinical applications are suggested: diagnosis of PCNSL in critical settings (elderly or frail patients, deep locations, and steroid responsiveness), definition of minimal residual disease, early indication of tumor response or relapse following treatments, and prediction of outcome.

CONCLUSIONS

Thus far, no clinically validated circulating biomarkers for managing both primary and secondary CNS lymphomas exist. There is need of standardization of biofluid collection, choice of analytes, and type of technique to perform the molecular analysis. The various assays should be evaluated through well-organized central testing within clinical trials.

Multisequence MRI-based radiomics signature as potential biomarkers for differentiating KRAS mutations in non-small cell lung cancer with brain metastases

Background

Kirsten rat sarcoma virus (KRAS) has evolved from a genotype with predictive value to a therapeutic target recently. The study aimed to establish non-invasive radiomics models based on MRI to discriminate KRAS from epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) mutations in lung cancer patients with brain metastases (BM), then further explore the optimal sequence for prediction.

Methods

This retrospective study involved 317 patients (218 patients in training cohort and 99 patients in testing cohort) who had confirmed of KRAS, EGFR or ALK mutations. Radiomics features were separately extracted from T2WI, T2 fluid-attenuated inversion recovery (T2-FLAIR), diffusion weighted imaging (DWI) and contrast-enhanced T1-weighted imaging (T1-CE) sequences. The maximal information coefficient and recursive feature elimination method were used to select informative features. Then we built four radiomics models for differentiating KRAS from EGFR or ALK using random forest classifier. ROC curves were used to validate the capability of the models.

Results

The four radiomics models for discriminating KRAS from EGFR all worked well, especially DWI and T2WI models (AUCs: 0.942, 0.942 in training cohort, 0.949, 0.954 in testing cohort). When KRAS compared to ALK, DWI and T2-FLAIR models showed excellent performance in two cohorts (AUCs: 0.947, 0.917 in training cohort, 0.850, 0.824 in testing cohort).

Conclusions

Radiomics classifiers integrating MRI have potential to discriminate KRAS from EGFR or ALK, which are helpful to guide treatment and facilitate the discovery of new approaches capable of achieving this long-sought goal of cure in lung cancer patients with KRAS.

Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to a Single Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis

PURPOSE

Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O‑(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of a single modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV).

METHODS

In this single center study, we retrospectively identified patients with WHO grades II-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27 and RN in 10 cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation.

RESULTS

After application of inclusion and exclusion criteria, we included 37 patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. A classification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones.

CONCLUSION

A multiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.

Narrow interval dual phase 18F-FDG PET/CT: A practical approach for distinguishing tumor recurrence from radiation necrosis in brain metastasis

Purpose of our research is to demonstrate efficacy of narrow interval dual phase [18F]-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) imaging in distinguishing tumor recurrence (TR) from radiation necrosis (RN) in patients treated for brain metastases. 35 consecutive patients (22 female, 13 male) with various cancer subtypes, lesion size > 1.0 cm3, and suspected recurrence on brain magnetic resonance imaging (MRI) underwent narrow interval dual phase FDG-PET/CT (30 and 90 min after tracer injection). Clinical outcome was determined via sequential MRIs or pathology reports. Maximum standard uptake value (SUVmax) of lesion (L), gray matter (GM), and white matter (WM) was measured on early (1) and delayed (2) imaging. Analyzed variables include % change, late phase, and early phase for L uptake, L/GM uptake, and L/WM uptake. Statistical analysis (P < .01), receiver operator characteristic (ROC) curve and area under curve (AUC) cutoff values were obtained. Change in L/GM ratio of > -2% was 95% sensitive, 91% specific, and 93% accurate (P < .001, AUC = 0.99) in distinguishing TR from RN. Change in SUVmax of lesion alone was the second-best indicator (P < .001, AUC = 0.94) with an ROC cutoff > 30.5% yielding 86% sensitivity, 83% specificity, and 84% accuracy. Other variables (L alone or L/GM ratios in early or late phase, all L/WM ratios) were significantly less accurate. Utilizing narrow interval dual phase FDG-PET/CT in patients with brain metastasis treated with radiation therapy provides a practical approach to distinguish TR from RN. Narrow time interval allows for better patient comfort, greater efficiency of PET/CT scanner, and lower disruption of workflow.

Generalizable synthetic MRI with physics-informed convolutional networks

BACKGROUND

Magnetic resonance imaging (MRI) provides state-of-the-art image quality for neuroimaging, consisting of multiple separately acquired contrasts. Synthetic MRI aims to accelerate examinations by synthesizing any desirable contrast from a single acquisition.

PURPOSE

We developed a physics-informed deep learning-based method to synthesize multiple brain MRI contrasts from a single 5-min acquisition and investigate its ability to generalize to arbitrary contrasts.

METHODS

A dataset of 55 subjects acquired with a clinical MRI protocol and a 5-min transient-state sequence was used. The model, based on a generative adversarial network, maps data acquired from the five-minute scan to "effective" quantitative parameter maps (q*-maps), feeding the generated PD, T1, and T2 maps into a signal model to synthesize four clinical contrasts (proton density-weighted, T1-weighted, T2-weighted, and T2-weighted fluid-attenuated inversion recovery), from which losses are computed. The synthetic contrasts are compared to an end-to-end deep learning-based method proposed by literature. The generalizability of the proposed method is investigated for five volunteers by synthesizing three contrasts unseen during training and comparing these to ground truth acquisitions via qualitative assessment and contrast-to-noise ratio (CNR) assessment.

RESULTS

The physics-informed method matched the quality of the end-to-end method for the four standard contrasts, with structural similarity metrics above0.75 ± 0.08 $0.75\pm 0.08$ ( ± $\pm$ std), peak signal-to-noise ratios above22.4 ± 1.9 $22.4\pm 1.9$ , representing a portion of compact lesions comparable to standard MRI. Additionally, the physics-informed method enabled contrast adjustment, and similar signal contrast and comparable CNRs to the ground truth acquisitions for three sequences unseen during model training.

CONCLUSIONS

The study demonstrated the feasibility of physics-informed, deep learning-based synthetic MRI to generate high-quality contrasts and generalize to contrasts beyond the training data. This technology has the potential to accelerate neuroimaging protocols.

Detection of recurrent high-grade glioma using microstructure characteristics of distinct metabolic compartments in a multimodal and integrative 18F-FET PET/fast-DKI approach

OBJECTIVES

Differentiation between high-grade glioma (HGG) and post-treatment-related effects (PTRE) is challenging, but advanced imaging techniques were shown to provide benefit. We aim to investigate microstructure characteristics of metabolic compartments identified from amino acid PET and to evaluate the diagnostic potential of this multimodal and integrative O-(2-18F-fluoroethyl)-L-tyrosine-(FET)-PET and fast diffusion kurtosis imaging (DKI) approach for the detection of recurrence and IDH genotyping.

METHODS

Fifty-nine participants with neuropathologically confirmed recurrent HGG (n = 39) or PTRE (n = 20) were investigated using static 18F-FET PET and a fast-DKI variant. PET and advanced diffusion metrics of metabolically defined (80-100% and 60-75% areas of 18F-FET uptake) compartments were assessed. Comparative analysis was performed using Mann-Whitney U tests with Holm-Šídák multiple-comparison test and Wilcoxon signed-rank test. Receiver operating characteristic (ROC) curves, regression, and Spearman's correlation analysis were used for statistical evaluations.

RESULTS

Compared to PTRE, recurrent HGG presented increased 18F-FET uptake and diffusivity (MD60), but lower (relative) mean kurtosis tensor (rMKT60) and fractional anisotropy (FA60) (respectively p < .05). Diffusion metrics determined from the metabolic periphery showed improved diagnostic performance - most pronounced for FA60 (AUC = 0.86, p < .001), which presented similar benefit to 18F-FET PET (AUC = 0.86, p < .001) and was negatively correlated with amino acid uptake (rs =  - 0.46, p < .001). When PET and DKI metrics were evaluated in a multimodal biparametric approach, TBRmax + FA60 showed highest diagnostic accuracy (AUC = 0.93, p < .001), which improved the detection of relapse compared to PET alone (difference in AUC = 0.069, p = .04). FA60 and MD60 distinguished the IDH genotype in the post-treatment setting.

CONCLUSION

Detection of glioma recurrence benefits from a multimodal and integrative PET/DKI approach, which presented significant diagnostic advantage to the assessment based on PET alone.

CLINICAL RELEVANCE STATEMENT

A multimodal and integrative 18F-FET PET/fast-DKI approach for the non-invasive microstructural characterization of metabolic compartments provided improved diagnostic capability for differentiation between recurrent glioma and post-treatment-related changes, suggesting a role for the diagnostic workup of patients in post-treatment settings.

KEY POINTS

• Multimodal PET/MRI with integrative analysis of 18F-FET PET and fast-DKI presents clinical benefit for the assessment of CNS cancer, particularly for the detection of recurrent high-grade glioma. • Microstructure markers of the metabolic periphery yielded biologically pertinent estimates characterising the tumour microenvironment, and, thereby, presented improved diagnostic accuracy with similar accuracy to amino acid PET. • Combined 18F-FET PET/fast-DKI achieved the best diagnostic performance for detection of high-grade glioma relapse with significant benefit to the assessment based on PET alone.

[18]F-fluoroethyl-l-tyrosine positron emission tomography for radiotherapy target delineation: Results from a Radiation Oncology credentialing program

Background and purpose

The [18]F-fluoroethyl-l-tyrosine (FET) PET in Glioblastoma (FIG) study is an Australian prospective, multi-centre trial evaluating FET PET for newly diagnosed glioblastoma management. The Radiation Oncology credentialing program aimed to assess the feasibility in Radiation Oncologist (RO) derivation of standard-of-care target volumes (TVMR) and hybrid target volumes (TVMR+FET) incorporating pre-defined FET PET biological tumour volumes (BTVs).

Materials and methods

Central review and analysis of TVMR and TVMR+FET was undertaken across three benchmarking cases. BTVs were pre-defined by a sole nuclear medicine expert. Intraclass correlation coefficient (ICC) confidence intervals (CIs) evaluated volume agreement. RO contour spatial and boundary agreement were evaluated (Dice similarity coefficient [DSC], Jaccard index [JAC], overlap volume [OV], Hausdorff distance [HD] and mean absolute surface distance [MASD]). Dose plan generation (one case per site) was assessed.

Results

Data from 19 ROs across 10 trial sites (54 initial submissions, 8 resubmissions requested, 4 conditional passes) was assessed with an initial pass rate of 77.8 %; all resubmissions passed. TVMR+FET were significantly larger than TVMR (p < 0.001) for all cases. RO gross tumour volume (GTV) agreement was moderate-to-excellent for GTVMR (ICC = 0.910; 95 % CI, 0.708-0.997) and good-to-excellent for GTVMR+FET (ICC = 0.965; 95 % CI, 0.871-0.999). GTVMR+FET showed greater spatial overlap and boundary agreement compared to GTVMR. For the clinical target volume (CTV), CTVMR+FET showed lower average boundary agreement versus CTVMR (MASD: 1.73 mm vs. 1.61 mm, p = 0.042). All sites passed the planning exercise.

Conclusions

The credentialing program demonstrated feasibility in successful credentialing of 19 ROs across 10 sites, increasing national expertise in TVMR+FET delineation.

Assessment of Brain Tumour Perfusion Using Early-Phase 18F-FET PET: Comparison with Perfusion-Weighted MRI

PURPOSE

Morphological imaging using MRI is essential for brain tumour diagnostics. Dynamic susceptibility contrast (DSC) perfusion-weighted MRI (PWI), as well as amino acid PET, may provide additional information in ambiguous cases. Since PWI is often unavailable in patients referred for amino acid PET, we explored whether maps of relative cerebral blood volume (rCBV) in brain tumours can be extracted from the early phase of PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET).

PROCEDURE

Using a hybrid brain PET/MRI scanner, PWI and dynamic 18F-FET PET were performed in 33 patients with cerebral glioma and four patients with highly vascularized meningioma. The time interval from 0 to 2 min p.i. was selected to best reflect the blood pool phase in 18F-FET PET. For each patient, maps of MR-rCBV, early 18F-FET PET (0-2 min p.i.) and late 18F-FET PET (20-40 min p.i.) were generated and coregistered. Volumes of interest were placed on the tumour (VOI-TU) and normal-appearing brain (VOI-REF). The correlation between tumour-to-brain ratios (TBR) of the different parameters was analysed. In addition, three independent observers evaluated MR-rCBV and early 18F-FET maps (18F-FET-rCBV) for concordance in signal intensity, tumour extent and intratumoural distribution.

RESULTS

TBRs calculated from MR-rCBV and 18F-FET-rCBV showed a significant correlation (r = 0.89, p < 0.001), while there was no correlation between late 18F-FET PET and MR-rCBV (r = 0.24, p = 0.16) and 18F-FET-rCBV (r = 0.27, p = 0.11). Visual rating yielded widely agreeing findings or only minor differences between MR-rCBV maps and 18F-FET-rCBV maps in 93 % of the tumours (range of three independent raters 91-94%, kappa among raters 0.78-1.0).

CONCLUSION

Early 18F-FET maps (0-2 min p.i.) in gliomas provide similar information to MR-rCBV maps and may be helpful when PWI is not possible or available. Further studies in gliomas are needed to evaluate whether 18F-FET-rCBV provides the same clinical information as MR-rCBV.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Diagnostic Accuracy of MR Spectroscopic Imaging and 18F-FET PET for Identifying Glioma: A Biopsy-Controlled Hybrid PET/MRI Study

Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.

Visual and semi-quantitative analysis of 6-[18F]FDOPA PET/CT in patients with brain tumors and suspected tumor recurrence versus radionecrosis

INTRODUCTION

Amino acid PET is a tool recommended by the main neuroimaging societies in the differential diagnosis between radionecrosis (RNC) and umour recurrence (TR) in brain tumours, but its use in our country is still limited. The aim of this work is to present our experience with 6-[18F]FDOPA PET/CT (FDOPA) in brain tumours (primary and M1), comparing these results with other published results.

MATERIAL AND METHODS

Retrospective study of 62 patients with suspected tumour recurrence (TR): 42 brain metastases (M1) and 20 primary, who underwent FDOPA. Images were analysed visually and semi-quantitatively, obtaining SUVmax and SUVmaxlesion/SUVmaxstriatum (L/S) and SUVmaxlesion/SUVmaxcortex (L/C) ratios. The diagnostic validity of PET was analysed and the best performing cut-off points were calculated. PET results were compared with clinical-radiological follow-up and/or histopathology.

RESULTS

TR was identified in 49% of M1 and 76% of brain primaries. The best performing FDOPA interpretation was visual and semi-quantitative, with a sensitivity and specificity in primaries of 94% and 80% and in M1s of 96% and 72% respectively. The cut-off points with the best diagnostic performance were L/C1.44 in M1 and L/C1.55 in primaries. There are discrepant results with other published results.

CONCLUSION

FDOPA PET/CT is a useful tool in the differential diagnosis between recurrence and RNC in brain tumours. It is needed a standardization to contribute to homogenise FDOPA results a inter-centre level.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients

Background

In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks.

Methods

The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy. Cognitive performance was assessed by 10 tests in 5 cognitive domains at a median of 14 months after treatment initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to a cross-validated machine-learning model to identify predictive fiber connections (edges), critical cortical regions (nodes), and the networks underlying cognitive performance.

Results

Compared to healthy controls (n = 121), patients' cognitive scores were significantly lower in 9 cognitive tests. The models predicted the scores of 7/10 tests (median correlation coefficient, 0.47; range, 0.39-0.57) from 0.6% to 5.4% of the matrix entries; 84% of the predictive edges were between nodes of different networks. Critically involved cortical regions (≥10 adjacent edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥15 edges) included the default mode network's left temporal and bilateral posterior cingulate cortex.

Conclusions

These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.

Clinical Applications of Radiomics in Nuclear Medicine

Radiomics is an emerging field of artificial intelligence that focuses on the extraction and analysis of quantitative features such as intensity, shape, texture and spatial relationships from medical images. These features, often imperceptible to the human eye, can reveal complex patterns and biological insights. They can also be combined with clinical data to create predictive models using machine learning to improve disease characterization in nuclear medicine. This review article examines the current state of radiomics in nuclear medicine and shows its potential to improve patient care. Selected clinical applications for diseases such as cancer, neurodegenerative diseases, cardiovascular problems and thyroid diseases are examined. The article concludes with a brief classification in terms of future perspectives and strategies for linking research findings to clinical practice.

Dark Blood Contrast-Enhanced Brain MRI Using Echo-uT1 RESS

BACKGROUND

The widely used magnetization-prepared rapid gradient-echo (MPRAGE) sequence makes enhancing lesions and blood vessels appear bright after gadolinium administration. However, dark blood imaging using T1-weighted Sampling Perfection with Application optimized Contrast using different flip angle Evolution (T1 SPACE) can be advantageous since it improves the conspicuity of small metastases and leptomeningeal disease. As a potential alternative to T1 SPACE, we evaluated a new dark blood sequence called echo-uT1 RESS (unbalanced T1 Relaxation-Enhanced Steady-State).

PURPOSE

We compared the performance of echo-uT1 RESS with Dixon fid-uT1 RESS, MPRAGE, and T1 SPACE.

STUDY TYPE

Retrospective, IRB approved.

SUBJECTS/PHANTOM

Phantom to assess flow properties of echo-uT1 RESS. Twenty-one patients (14 female, age range 35-82 years) with primary and secondary brain tumors.

FIELD STRENGTH/SEQUENCES

3 Tesla/MPRAGE, T1 SPACE, Dixon fid-uT1 RESS, echo-uT1 RESS.

ASSESSMENT

Flow phantom signal vs. velocity as a function of flip angle and sequence. Qualitative image assessment on 4-point scale. Quantitative evaluation of tumor-to-brain contrast, apparent contrast-to-noise ratio (aCNR), and vessel-to-brain aCNR.

STATISTICAL TESTS

Friedman and Mann-Whitney U tests. A P value <0.05 was considered statistically significant.

RESULTS

In the phantom, echo-uT1 RESS showed greater flow-dependent signal loss than fid-uT1 RESS. In patients, blood vessels appeared bright with MPRAGE, gray with fid-uT1 RESS, and dark with T1 SPACE and echo-uT1 RESS. For MPRAGE, Dixon fid-uT1 RESS, echo-uT1 RESS, and T1 SPACE, respective tumor-to-brain contrast values were 0.6 ± 0.3, 1.3 ± 0.5, 1.0 ± 0.4, and 0.6 ± 0.4, while normalized aCNR values were 68.9 ± 50.9, 128.4 ± 59.2, 74.2 ± 42.1, and 99.4 ± 73.9.

DATA CONCLUSION

Volumetric dark blood contrast-enhanced brain MRI is feasible using echo-uT1 RESS. The dark blood effect was improved vs. fid-uT1 RESS, while both uT1 RESS versions provided better tumor-to-brain contrast than MPRAGE. Whereas T1 SPACE provided better tumor aSNR, echo-uT1 RESS provided better Weber contrast, lesion sharpness and a more consistent dark blood effect.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 1.

How Much is Enough? Impact of Efflux Transporters on Drug delivery Leading to Efficacy in the Treatment of Brain Tumors

The lack of effective chemotherapeutic agents for the treatment of brain tumors is a serious unmet medical need. This can be attributed, in part, to inadequate delivery through the blood-brain barrier (BBB) and the tumor-cell barrier, both of which have active efflux transporters that can restrict the transport of many potentially effective agents for both primary and metastatic brain tumors. This review briefly summarizes the components and function of the normal BBB with respect to drug penetration into the brain and the alterations in the BBB due to brain tumor that could influence drug delivery. Depending on what is rate-limiting a compound's distribution, the limited permeability across the BBB and the subsequent delivery into the tumor cell can be greatly influenced by efflux transporters and these are discussed in some detail. Given these complexities, it is necessary to quantify the extent of brain distribution of the active (unbound) drug to compare across compounds and to inform potential for use against brain tumors. In this regard, the metric, Kp,uu, a brain-to-plasma unbound partition coefficient, is examined and its current use is discussed. However, the extent of active drug delivery is not the only determinant of effective therapy. In addition to Kp,uu, drug potency is an important parameter that should be considered alongside drug delivery in drug discovery and development processes. In other words, to answer the question - How much is enough? - one must consider how much can be delivered with how much needs to be delivered.

Brain 18 F-FET in a Case of Acute Myeloid Leukemia

ABSTRACT

A 58-year-old woman, with a history of acute myeloid leukemia in complete response, was referred to the emergency department of our hospital for loss of consciousness. A brain MRI showed an intracranial mass suggestive for either primary brain tumor or brain metastasis. 18 F-FET PET/CT revealed increased uptake of the lesion. Metastasis from acute myeloid leukemia was diagnosed after brain biopsy. Whole-body 18 F-FDG PET/CT did not demonstrate other abnormal foci of 18 F-FDG accumulation, whereas brain lesion had an uptake slightly below the adjacent brain.

Parallel detection of multi-contrast MRI and Deuterium Metabolic Imaging (DMI) for time-efficient characterization of neurological diseases

Deuterium Metabolic Imaging (DMI) is a novel method that can complement traditional anatomical magnetic resonance imaging (MRI) of the brain. DMI relies on the MR detection of metabolites that become labeled with deuterium (2H) after administration of a deuterated substrate and can provide images with highly specific metabolic information. However, clinical adoption of DMI is complicated by its relatively long scan time. Here, we demonstrate a strategy to interleave DMI data acquisition with MRI that results in a comprehensive neuro-imaging protocol without adding scan time. The interleaved MRI-DMI routine includes four essential clinical MRI scan types, namely T1-weighted MP-RAGE, FLAIR, T2-weighted Imaging (T2W) and susceptibility weighted imaging (SWI), interwoven with DMI data acquisition. Phantom and in vivo human brain data show that MR image quality, DMI sensitivity, as well as information content are preserved in the MRI-DMI acquisition method. The interleaved MRI-DMI technology provides full flexibility to upgrade traditional MRI protocols with DMI, adding unique metabolic information to existing types of anatomical image contrast, without extra scan time.

Automated Brain Tumor Detection and Segmentation for Treatment Response Assessment Using Amino Acid PET

Evaluation of metabolic tumor volume (MTV) changes using amino acid PET has become an important tool for response assessment in brain tumor patients. MTV is usually determined by manual or semiautomatic delineation, which is laborious and may be prone to intra- and interobserver variability. The goal of our study was to develop a method for automated MTV segmentation and to evaluate its performance for response assessment in patients with gliomas. Methods: In total, 699 amino acid PET scans using the tracer O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) from 555 brain tumor patients at initial diagnosis or during follow-up were retrospectively evaluated (mainly glioma patients, 76%). 18F-FET PET MTVs were segmented semiautomatically by experienced readers. An artificial neural network (no new U-Net) was configured on 476 scans from 399 patients, and the network performance was evaluated on a test dataset including 223 scans from 156 patients. Surface and volumetric Dice similarity coefficients (DSCs) were used to evaluate segmentation quality. Finally, the network was applied to a recently published 18F-FET PET study on response assessment in glioblastoma patients treated with adjuvant temozolomide chemotherapy for a fully automated response assessment in comparison to an experienced physician. Results: In the test dataset, 92% of lesions with increased uptake (n = 189) and 85% of lesions with iso- or hypometabolic uptake (n = 33) were correctly identified (F1 score, 92%). Single lesions with a contiguous uptake had the highest DSC, followed by lesions with heterogeneous, noncontiguous uptake and multifocal lesions (surface DSC: 0.96, 0.93, and 0.81 respectively; volume DSC: 0.83, 0.77, and 0.67, respectively). Change in MTV, as detected by the automated segmentation, was a significant determinant of disease-free and overall survival, in agreement with the physician's assessment. Conclusion: Our deep learning-based 18F-FET PET segmentation allows reliable, robust, and fully automated evaluation of MTV in brain tumor patients and demonstrates clinical value for automated response assessment.

Fibroblast activation protein as a potential theranostic target in brain metastases of diverse solid tumours

Brain metastases are a very common and serious complication of oncological diseases. Despite the vast progress in multimodality treatment, brain metastases significantly decrease the quality of life and prognosis of patients. Therefore, identifying new targets in the microenvironment of brain metastases is desirable. Fibroblast activation protein (FAP) is a transmembrane serine protease typically expressed in tumour-associated stromal cells. Due to its characteristic presence in the tumour microenvironment, FAP represents an attractive theranostic target in oncology. However, there is little information on FAP expression in brain metastases. In this study, we quantified FAP expression in samples of brain metastases of various primary origin and characterised FAP-expressing cells. We have shown that FAP expression is significantly higher in brain metastases in comparison to non-tumorous brain tissues, both at the protein and enzymatic activity levels. FAP immunopositivity was localised in regions rich in collagen and containing blood vessels. We have further shown that FAP is predominantly confined to stromal cells expressing markers typical of cancer-associated fibroblasts (CAFs). We have also observed FAP immunopositivity on tumour cells in a portion of brain metastases, mainly originating from melanoma, lung, breast, and renal cancer, and sarcoma. There were no significant differences in the quantity of FAP protein, enzymatic activity, and FAP+ stromal cells among brain metastasis samples of various origins, suggesting that there is no association of FAP expression and/or presence of FAP+ stromal cells with the histological type of brain metastases. In summary, we are the first to establish the expression of FAP and characterise FAP-expressing cells in the microenvironment of brain metastases. The frequent upregulation of FAP and its presence on both stromal and tumour cells support the use of FAP as a promising theranostic target in brain metastases.

Immune Checkpoint Inhibitors in "Special" NSCLC Populations: A Viable Approach?

Over the last decade, the therapeutic scenario for advanced non-small-cell lung cancer (NSCLC) has undergone a major paradigm shift. Immune checkpoint inhibitors (ICIs) have shown a meaningful clinical and survival improvement in different settings of the disease. However, the real benefit of this therapeutic approach remains controversial in selected NSCLC subsets, such as those of the elderly with active brain metastases or oncogene-addicted mutations. This is mainly due to the exclusion or underrepresentation of these patient subpopulations in most pivotal phase III studies; this precludes the generalization of ICI efficacy in this context. Moreover, no predictive biomarkers of ICI response exist that can help with patient selection for this therapeutic approach. Here, we critically summarize the current state of ICI efficacy in the most common "special" NSCLC subpopulations.

Hybrid PET/MRI in Cerebral Glioma: Current Status and Perspectives

Advanced MRI methods and PET using radiolabelled amino acids provide valuable information, in addition to conventional MR imaging, for brain tumour diagnostics. These methods are particularly helpful in challenging situations such as the differentiation of malignant processes from benign lesions, the identification of non-enhancing glioma subregions, the differentiation of tumour progression from treatment-related changes, and the early assessment of responses to anticancer therapy. The debate over which of the methods is preferable in which situation is ongoing, and has been addressed in numerous studies. Currently, most radiology and nuclear medicine departments perform these examinations independently of each other, leading to multiple examinations for the patient. The advent of hybrid PET/MRI allowed a convergence of the methods, but to date simultaneous imaging has reached little relevance in clinical neuro-oncology. This is partly due to the limited availability of hybrid PET/MRI scanners, but is also due to the fact that PET is a second-line examination in brain tumours. PET is only required in equivocal situations, and the spatial co-registration of PET examinations of the brain to previous MRI is possible without disadvantage. A key factor for the benefit of PET/MRI in neuro-oncology is a multimodal approach that provides decisive improvements in the diagnostics of brain tumours compared with a single modality. This review focuses on studies investigating the diagnostic value of combined amino acid PET and 'advanced' MRI in patients with cerebral gliomas. Available studies suggest that the combination of amino acid PET and advanced MRI improves grading and the histomolecular characterisation of newly diagnosed tumours. Few data are available concerning the delineation of tumour extent. A clear additive diagnostic value of amino acid PET and advanced MRI can be achieved regarding the differentiation of tumour recurrence from treatment-related changes. Here, the PET-guided evaluation of advanced MR methods seems to be helpful. In summary, there is growing evidence that a multimodal approach can achieve decisive improvements in the diagnostics of cerebral gliomas, for which hybrid PET/MRI offers optimal conditions.

Peptides for trans-blood-brain barrier delivery

Trans-blood-brain barrier (BBB) delivery of therapeutic and diagnostic agents is a major challenge in the development of central nervous system (CNS) targeted radiopharmaceuticals. This review is an introduction to the use of peptides as delivery agents to transport cargos into the CNS. The most widely used BBB-penetrating peptides are reviewed here, with a particular emphasis on the broad range of cargos delivered into the CNS using these. Cell-penetrating peptides (CPPs) have been deployed as trans-BBB delivery agents for some time; new developments in the CPP field offer exciting opportunities for the design of next generation trans-BBB complexes. Many of the peptides highlighted here are ready to be combined with diagnostic and therapeutic radiopharmaceuticals to develop highly effective CNS-targeted agents.

Implantable Electrochemical Sensors for Brain Research

Implantable electrochemical sensors provide reliable tools for in vivo brain research. Recent advances in electrode surface design and high-precision fabrication of devices led to significant developments in selectivity, reversibility, quantitative detection, stability, and compatibility of other methods, which enabled electrochemical sensors to provide molecular-scale research tools for dissecting the mechanisms of the brain. In this Perspective, we summarize the contribution of these advances to brain research and provide an outlook on the development of the next generation of electrochemical sensors for the brain.

Maximum Emission Peak Over 1500 nm of Organic Assembly for Blood-Brain Barrier-Crossing NIR-IIb Phototheranostics of Orthotopic Glioblastoma

The development of blood-brain barrier (BBB)-crossing phototheranostic agents in second near-infrared window (NIR-II), especially in the range of 1500-1700 nm (NIR-IIb), affords great opportunities for glioblastoma (GBM) management. Herein, an organic assembly (denoted as LET-12) with the maximum absorption peak at 1400 nm and emission peak at 1512 nm with trailing over 1700 nm through the self-assembly of organic small molecule IR-1064 is designed and subsequently decorated with choline and acetylcholine analogs. The LET-12 can effectively cross BBB through the brain's choline-like receptors-mediated transcytosis and accumulated in tumor tissues, thus achieving fluorescence/photoacoustic (FL/PA) duplex imaging of orthotopic GBM with ≈3.0 mm depth and a superior tumor-to-normal tissue signal ratio (20.93 ± 0.59 for FL imaging and 32.63 ± 1.16 for PA imaging, respectively). Owing to its good photothermal conversion ability, the LET-12 also can serve as a photothermal conversion agent, achieving obvious tumor repression of orthotopic murine GBM model after once treatment. The findings indicate that the LET-12 holds great potential for BBB-crossing NIR-IIb phototheranostics of orthotopic GBM. This self-assembly strategy of organic small molecules opens a new avenue for the construction of NIR-IIb phototheranostics.

Advances in PET imaging of cancer

Molecular imaging has experienced enormous advancements in the areas of imaging technology, imaging probe and contrast development, and data quality, as well as machine learning-based data analysis. Positron emission tomography (PET) and its combination with computed tomography (CT) or magnetic resonance imaging (MRI) as a multimodality PET-CT or PET-MRI system offer a wealth of molecular, functional and morphological data with a single patient scan. Despite the recent technical advances and the availability of dozens of disease-specific contrast and imaging probes, only a few parameters, such as tumour size or the mean tracer uptake, are used for the evaluation of images in clinical practice. Multiparametric in vivo imaging data not only are highly quantitative but also can provide invaluable information about pathophysiology, receptor expression, metabolism, or morphological and functional features of tumours, such as pH, oxygenation or tissue density, as well as pharmacodynamic properties of drugs, to measure drug response with a contrast agent. It can further quantitatively map and spatially resolve the intertumoural and intratumoural heterogeneity, providing insights into tumour vulnerabilities for target-specific therapeutic interventions. Failure to exploit and integrate the full potential of such powerful imaging data may lead to a lost opportunity in which patients do not receive the best possible care. With the desire to implement personalized medicine in the cancer clinic, the full comprehensive diagnostic power of multiplexed imaging should be utilized.

Conventional and Advanced Magnetic Resonance Imaging Assessment of Non-Enhancing Peritumoral Area in Brain Tumor

The non-enhancing peritumoral area (NEPA) is defined as the hyperintense region in T2-weighted and fluid-attenuated inversion recovery (FLAIR) images surrounding a brain tumor. The NEPA corresponds to different pathological processes, including vasogenic edema and infiltrative edema. The analysis of the NEPA with conventional and advanced magnetic resonance imaging (MRI) was proposed in the differential diagnosis of solid brain tumors, showing higher accuracy than MRI evaluation of the enhancing part of the tumor. In particular, MRI assessment of the NEPA was demonstrated to be a promising tool for distinguishing high-grade gliomas from primary lymphoma and brain metastases. Additionally, the MRI characteristics of the NEPA were found to correlate with prognosis and treatment response. The purpose of this narrative review was to describe MRI features of the NEPA obtained with conventional and advanced MRI techniques to better understand their potential in identifying the different characteristics of high-grade gliomas, primary lymphoma and brain metastases and in predicting clinical outcome and response to surgery and chemo-irradiation. Diffusion and perfusion techniques, such as diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), dynamic susceptibility contrast-enhanced (DSC) perfusion imaging, dynamic contrast-enhanced (DCE) perfusion imaging, arterial spin labeling (ASL), spectroscopy and amide proton transfer (APT), were the advanced MRI procedures we reviewed.

Head-To-Head Comparison of PET and Perfusion Weighted MRI Techniques to Distinguish Treatment Related Abnormalities from Tumor Progression in Glioma

The post-treatment imaging surveillance of gliomas is challenged by distinguishing tumor progression (TP) from treatment-related abnormalities (TRA). Sophisticated imaging techniques, such as perfusion-weighted magnetic resonance imaging (MRI PWI) and positron-emission tomography (PET) with a variety of radiotracers, have been suggested as being more reliable than standard imaging for distinguishing TP from TRA. However, it remains unclear if any technique holds diagnostic superiority. This meta-analysis provides a head-to-head comparison of the diagnostic accuracy of the aforementioned imaging techniques. Systematic literature searches on the use of PWI and PET imaging techniques were carried out in PubMed, Embase, the Cochrane Library, ClinicalTrials.gov and the reference lists of relevant papers. After the extraction of data on imaging technique specifications and diagnostic accuracy, a meta-analysis was carried out. The quality of the included papers was assessed using the QUADAS-2 checklist. Nineteen articles, totaling 697 treated patients with glioma (431 males; mean age ± standard deviation 50.5 ± 5.1 years) were included. The investigated PWI techniques included dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE) and arterial spin labeling (ASL). The PET-tracers studied concerned [S-methyl-¹¹C]methionine, 2-deoxy-2-[¹⁸F]fluoro-D-glucose ([¹⁸F]FDG), O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) and 6-[¹⁸F]-fluoro-3,4-dihydroxy-L-phenylalanine ([¹⁸F]FDOPA). The meta-analysis of all data showed no diagnostic superior imaging technique. The included literature showed a low risk of bias. As no technique was found to be diagnostically superior, the local level of expertise is hypothesized to be the most important factor for diagnostically accurate results in post-treatment glioma patients regarding the distinction of TRA from TP.

Amino Acid PET in Neurooncology

For decades, several amino acid PET tracers have been used to optimize diagnostics in patients with brain tumors. In clinical routine, the most important clinical indications for amino acid PET in brain tumor patients are differentiation of neoplasm from nonneoplastic etiologies, delineation of tumor extent for further diagnostic and treatment planning (i.e., diagnostic biopsy, resection, or radiotherapy), differentiation of treatment-related changes such as pseudoprogression or radiation necrosis after radiation or chemoradiation from tumor progression at follow-up, and assessment of response to anticancer therapy, including prediction of patient outcome. This continuing education article addresses the diagnostic value of amino acid PET for patients with either glioblastoma or metastatic brain cancer.

ESTRO-EANO guideline on target delineation and radiotherapy details for glioblastoma

BACKGROUND AND PURPOSE

Target delineation in glioblastoma is still a matter of extensive research and debate. This guideline aims to update the existing joint European consensus on delineation of the clinical target volume (CTV) in adult glioblastoma patients.

MATERIAL AND METHODS

The ESTRO Guidelines Committee identified 14 European experts in close interaction with the ESTRO clinical committee and EANO who discussed and analysed the body of evidence concerning contemporary glioblastoma target delineation, then took part in a two-step modified Delphi process to address open questions.

RESULTS

Several key issues were identified and are discussed including i) pre-treatment steps and immobilisation, ii) target delineation and the use of standard and novel imaging techniques, and iii) technical aspects of treatment including planning techniques and fractionation. Based on the EORTC recommendation focusing on the resection cavity and residual enhancing regions on T1-sequences with the addition of a reduced 15 mm margin, special situations are presented with corresponding potential adaptations depending on the specific clinical situation.

CONCLUSIONS

The EORTC consensus recommends a single clinical target volume definition based on postoperative contrast-enhanced T1 abnormalities, using isotropic margins without the need to cone down. A PTV margin based on the individual mask system and IGRT procedures available is advised; this should usually be no greater than 3 mm when using IGRT.

The Role of Molecular Imaging in Patients with Brain Metastases: A Literature Review

Over the last several years, molecular imaging has gained a primary role in the evaluation of patients with brain metastases (BM). Therefore, the "Response Assessment in Neuro-Oncology" (RANO) group recommends amino acid radiotracers for the assessment of BM. Our review summarizes the current use of positron emission tomography (PET) radiotracers in patients with BM, ranging from present to future perspectives with new PET radiotracers, including the role of radiomics and potential theranostics approaches. A comprehensive search of PubMed results was conducted. All studies published in English up to and including December 2022 were reviewed. Current evidence confirms the important role of amino acid PET radiotracers for the delineation of BM extension, for the assessment of response to therapy, and particularly for the differentiation between tumor progression and radionecrosis. The newer radiotracers explore non-invasively different biological tumor processes, although more consistent findings in larger clinical trials are necessary to confirm preliminary results. Our review illustrates the role of molecular imaging in patients with BM. Along with magnetic resonance imaging (MRI), the gold standard for diagnosis of BM, PET is a useful complementary technique for processes that otherwise cannot be obtained from anatomical MRI alone.

A biocompatible polyurethane fluorescent emulsion with aggregation-induced emission for targeted tumor imaging

The applications of fluorescence imaging in tumor detection and assistance in tumor resection have become progressively more widespread. Biocompatible fluorescent nanoparticles with high sensitivity and selectivity are a challenge for biological fluorescence imaging. Ligand-mediated targeting of nanoparticles to tumors is an appealing tactic for improving imaging efficiency. Herein, tetraphenyl ethylene (TPE) and phenylboronic acid (PBA) were introduced into polyurethane to synthesize a PU-TPE-PBA (PTP) fluorescent emulsion with aggregation-induced emission (AIE) for targeted tumor imaging. The PTP emulsion with a size of less than 50 nm shows excellent stability and high fluorescence sensitivity (extremely low TPE concentrations of 0.31 μg mL^-1). Since PBA can selectively recognize and bind to sialic acid (SA) which is widely overexpressed in tumor cells, such PTP nanoparticles can be enriched in tumors and retained for longer periods due to enhanced permeability and retention (EPR) as well as active targeting effects. In addition, the PTP emulsion exhibits good biocompatibility and biosafety. Therefore, the novel PTP emulsion is promising for tumor cell imaging.

Improved Brain Tumor Conspicuity at 3 T Using Dark Blood, Fat-Suppressed, Dixon Unbalanced T1 Relaxation-Enhanced Steady-State MRI

OBJECTIVES

Contrast-enhanced magnetic resonance imaging (MRI) is the cornerstone for brain tumor diagnosis and treatment planning. We have developed a novel dual-echo volumetric dark blood pulse sequence called Dixon unbalanced T1 relaxation-enhanced steady-state (uT1RESS) that improves the visibility of contrast-enhancing lesions while suppressing the tissue signals from blood vessels and fat. The purpose of this study was to test the hypothesis that Dixon uT1RESS would significantly improve the conspicuity of brain tumors compared with magnetization-prepared rapid gradient echo (MPRAGE), as well as to determine potential limitations of the technique.

MATERIALS AND METHODS

This retrospective study was approved by the hospital institutional review board. Forty-seven adult patients undergoing an MRI scan for a brain tumor indication were included. Contrast-enhanced MRI of the brain was performed at 3 T using both MPRAGE and Dixon uT1RESS. To control for any impact of contrast agent washout during the scan procedure, Dixon uT1RESS was acquired in approximately half the subjects immediately after MPRAGE, and in the other half immediately before MPRAGE. Image quality, artifacts, and lesion detection were scored by 3 readers, whereas lesion apparent signal-to-noise ratio and lesion-to-background Weber contrast were calculated from region-of-interest measurements.

RESULTS

Image quality was not rated significantly different between MPRAGE and Dixon uT1RESS, whereas motion artifacts were slightly worse with Dixon uT1RESS. Comparing Dixon uT1RESS with MPRAGE, the respective values for mean lesion apparent signal-to-noise ratio were not significantly different (199.31 ± 99.05 vs 203.81 ± 110.23). Compared with MPRAGE, Dixon uT1RESS significantly increased the tumor-to-brain contrast (1.60 ± 1.18 vs 0.61 ± 0.47 when Dixon uT1RESS was acquired before MPRAGE and 1.94 ± 0.97 vs 0.82 ± 0.55 when Dixon uT1RESS was acquired after MPRAGE). In patients with metastatic disease, Dixon uT1RESS detected at least 1 enhancing brain lesion that was missed by MPRAGE on average in 24.7% of patients, whereas Dixon uT1RESS did not miss any lesions that were demonstrated by MPRAGE. Dixon uT1RESS better detected vascular and dural invasion in a small number of patients.

CONCLUSIONS

In conclusion, brain tumors were significantly more conspicuous at 3 T using Dixon uT1RESS compared with MPRAGE, with an approximately 2.5-fold improvement in lesion-to-background contrast irrespective of sequence order. It outperformed MPRAGE for the detection of brain metastases, dural or vascular involvement. These results suggest that Dixon uT1RESS could prove to be a useful adjunct or alternative to existing neuroimaging techniques for the postcontrast evaluation of intracranial tumors.

Revisiting PFA-mediated tissue fixation chemistry: FixEL enables trapping of small molecules in the brain to visualize their distribution changes

Various small molecules have been used as functional probes for tissue imaging in medical diagnosis and pharmaceutical drugs for disease treatment. The spatial distribution, target selectivity, and diffusion/excretion kinetics of small molecules in structurally complicated specimens are critical for function. However, robust methods for precisely evaluating these parameters in the brain have been limited. Herein, we report a new method termed "fixation-driven chemical cross-linking of exogenous ligands (FixEL)," which traps and images exogenously administered molecules of interest (MOIs) in complex tissues. This method relies on protein-MOI interactions and chemical cross-linking of amine-tethered MOI with paraformaldehyde used for perfusion fixation. FixEL is used to obtain images of the distribution of the small molecules, which addresses selective/nonselective binding to proteins, time-dependent localization changes, and diffusion/retention kinetics of MOIs such as the scaffold of PET tracer derivatives or drug-like small molecules.

[18F]FET-PET in children and adolescents with central nervous system tumors: does it support difficult clinical decision-making?

PURPOSE

Positron emission tomography (PET) with O-(2-[¹⁸F]fluoroethyl)-L-tyrosine ([¹⁸F]FET) is a well-established tool for non-invasive assessment of adult central nervous system (CNS) tumors. However, data on its diagnostic utility and impact on clinical management in children and adolescents are limited.

METHODS

Twenty-one children and young adults (13 males; mean age, 8.6 ± 5.2 years; range, 1-19 at initial diagnosis) with either newly diagnosed (n = 5) or pretreated (n = 16) CNS tumors were retrospectively analyzed. All patients had previously undergone neuro-oncological work-up including cranial magnetic resonance imaging. In all cases, [¹⁸F]FET-PET was indicated in a multidisciplinary team conference. The impact of PET imaging on clinical decision-making was assessed. Histopathology (n = 12) and/or clinical and imaging follow-up (n = 9) served as the standard of reference.

RESULTS

The addition of [¹⁸F]FET-PET to the available information had an impact on further patient management in 14 out of 21 subjects, with avoidance of invasive surgery or biopsy in four patients, biopsy guidance in four patients, change of further treatment in another five patients, and confirmation of diagnosis in one patient.

CONCLUSION

[¹⁸F]FET-PET may provide important additional information for treatment guidance in pediatric and adolescent patients with CNS tumors.

Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain

Glucose is the main energy source in the brain and its regulated uptake and utilization are important biomarkers of pathological brain function. Glucose Chemical Exchange Saturation Transfer (GlucoCEST) and its time-resolved version Dynamic Glucose-Enhanced MRI (DGE) are promising approaches to monitor glucose and detect tumors, since they are radioactivity-free, do not require ¹³C labeling and are is easily translatable to the clinics. The main principle of DGE is clear. However, what remains to be established is to which extent the signal reflects vascular, extracellular or intracellular glucose. To elucidate the compartmental contributions to the DGE signal, we coupled it with FRET-based fiber photometry of genetically encoded sensors, a technique that combines quantitative glucose readout with cellular specificity. The glucose sensor FLIIP was used with fiber photometry to measure astrocytic and neuronal glucose changes upon injection of D-glucose, 3OMG and L-glucose, in the anaesthetized murine brain. By correlating the kinetic profiles of the techniques, we demonstrate the presence of a vascular contribution to the signal, especially at early time points after injection. Furthermore, we show that, in the case of the commonly used contrast agent 3OMG, the DGE signal actually anticorrelates with the glucose concentration in neurons and astrocytes.

Clinical applications and prospects of PET imaging in patients with IDH-mutant gliomas

PET imaging using radiolabeled amino acids in addition to MRI has become a valuable diagnostic tool in the clinical management of patients with brain tumors. This review provides a comprehensive overview of PET studies in glioma patients with a mutation in the isocitrate dehydrogenase gene (IDH). A considerable fraction of these tumors typically show no contrast enhancement on MRI, especially when classified as grade 2 according to the World Health Organization classification of Central Nervous System tumors. Major diagnostic challenges in this situation are differential diagnosis, target definition for diagnostic biopsies, delineation of glioma extent for treatment planning, differentiation of treatment-related changes from tumor progression, and the evaluation of response to alkylating agents. The main focus of this review is the role of amino acid PET in this setting. Furthermore, in light of clinical trials using IDH inhibitors targeting the mutated IDH enzyme for treating patients with IDH-mutant gliomas, we also aim to give an outlook on PET probes specifically targeting the IDH mutation, which appear potentially helpful for response assessment.

Diagnostic Value of 18 F-FACBC PET/MRI in Brain Metastases

PURPOSE

The study aims to evaluate whether combined 18 F-FACBC PET/MRI could provide additional diagnostic information compared with MRI alone in brain metastases.

PATIENTS AND METHODS

Eighteen patients with newly diagnosed or suspected recurrence of brain metastases received dynamic 18 F-FACBC PET/MRI. Lesion detection was evaluated on PET and MRI scans in 2 groups depending on prior stereotactic radiosurgery (SRS group) or not (no-SRS group). SUVs, time-activity curves, and volumetric analyses of the lesions were performed.

RESULTS

In the no-SRS group, 29/29 brain lesions were defined as "MRI positive." With PET, 19/29 lesions were detected and had high tumor-to-background ratios (TBRs) (D max MR , ≥7 mm; SUV max , 1.2-8.4; TBR, 3.9-25.9), whereas 10/29 lesions were undetected (D max MR , ≤8 mm; SUV max , 0.3-1.2; TBR, 1.0-2.7). In the SRS group, 4/6 lesions were defined as "MRI positive," whereas 2/6 lesions were defined as "MRI negative" indicative of radiation necrosis. All 6 lesions were detected with PET (D max MR , ≥15 mm; SUV max , 1.4-4.2; TBR, 3.6-12.6). PET volumes correlated and were comparable in size with contrast-enhanced MRI volumes but were only partially congruent (mean DSC, 0.66). All time-activity curves had an early peak, followed by a plateau or a decreasing slope.

CONCLUSIONS

18 F-FACBC PET demonstrated uptake in brain metastases from cancer of different origins (lung, gastrointestinal tract, breast, thyroid, and malignant melanoma). However, 18 F-FACBC PET/MRI did not improve detection of brain metastases compared with MRI but might detect tumor tissue beyond contrast enhancement on MRI. 18 F-FACBC PET should be further evaluated in recurrent brain metastases.

Is it necessary for patients with potentially resectable esophageal squamous cell cancer to receive routine preoperative brain MRI/CT?

BACKGROUND

This study aimed to investigate the value and efficiency of routine brain MRI or CT in the preoperative workup for patients with potentially resectable (cT_1-4a N_0-3 ) thoracic esophageal squamous cell cancer (ESCC).

METHODS

This was a prospective cross-sectional clinical trial (ChiCTR1800020304). A total of 385 patients with potentially resectable (cT_1-4a N_0-3 ) thoracic ESCC diagnosed from October 2018 to August 2020 were included. Plain brain MRI or CT was performed preoperatively to detect brain metastases (BrM). The primary endpoint was BrM detected by imaging.

RESULTS

Of all 385 patients, the rate of positive brain MRI/CT findings was 1% (n = 4). BrM Patients received chemoradiotherapy, and the median OS was 6 months (95% CI: 4.303-7.697). All 381 remaining patients with initial negative brain MRI/CT diagnosis revealed no brain-associated symptoms within 6 months. The median follow-up for patients without BrM was 20 months (range, from 6 to 32). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of plain MRI or CT to detect BrM were all 100%.

CONCLUSIONS

Preoperative plain MRI or CT is an effective method to detect BrM for potentially resectable (cT_1-4a N_0-3 ) thoracic ESCC. However, due to the low incidence, the value of brain MRI/CT as a routinely preoperational examination in potentially resectable esophageal squamous cell cancer is rather limited. Therefore, preoperative brain MRI/CT should not be recommended as a routine preoperative examination for ESCC.

The role of [18F]fluorodopa positron emission tomography in grading of gliomas

PURPOSE

Gliomas are the most commonly occurring brain tumour in adults and there remains no cure for these tumours with treatment strategies being based on tumour grade. All treatment options aim to prolong survival, maintain quality of life and slow the inevitable progression from low-grade to high-grade. Despite imaging advancements, the only reliable method to grade a glioma is to perform a biopsy, and even this is fraught with errors associated with under grading. Positron emission tomography (PET) imaging with amino acid tracers such as [18F]fluorodopa (18F-FDOPA), [11C]methionine (11C-MET), [18F]fluoroethyltyrosine (18F-FET), and 18F-FDOPA are being increasingly used in the diagnosis and management of gliomas.

METHODS

In this review we discuss the literature available on the ability of 18F-FDOPA-PET to distinguish low- from high-grade in newly diagnosed gliomas.

RESULTS

In 2016 the Response Assessment in Neuro-Oncology (RANO) and European Association for Neuro-Oncology (EANO) published recommendations on the clinical use of PET imaging in gliomas. However, since these recommendations there have been a number of studies performed looking at whether 18F-FDOPA-PET can identify areas of high-grade transformation before the typical radiological features of transformation such as contrast enhancement are visible on standard magnetic resonance imaging (MRI).

CONCLUSION

Larger studies are needed to validate 18F-FDOPA-PET as a non-invasive marker of glioma grade and prediction of tumour molecular characteristics which could guide decisions surrounding surgical resection.

Use of multimodality imaging, histology, and treatment feasibility to characterize a transgenic Rag2-null rat model of glioblastoma

Many drugs that show potential in animal models of glioblastoma (GBM) fail to translate to the clinic, contributing to a paucity of new therapeutic options. In addition, animal model development often includes histologic assessment, but multiparametric/multimodality imaging is rarely included despite increasing utilization in patient cancer management. This study developed an intracranial recurrent, drug-resistant, human-derived glioblastoma tumor in Sprague-Dawley Rag2-Rag2 ^tm1Hera knockout rat and was characterized both histologically and using multiparametric/multimodality neuroimaging. Hybrid ¹⁸F-fluoroethyltyrosine positron emission tomography and magnetic resonance imaging, including chemical exchange saturation transfer (¹⁸F-FET PET/CEST MRI), was performed for full tumor viability determination and characterization. Histological analysis demonstrated human-like GBM features of the intracranially implanted tumor, with rapid tumor cell proliferation (Ki67 positivity: 30.5 ± 7.8%) and neovascular heterogeneity (von Willebrand factor VIII:1.8 to 5.0% positivity). Early serial MRI followed by simultaneous ¹⁸F-FET PET/CEST MRI demonstrated consistent, predictable tumor growth, with exponential tumor growth most evident between days 35 and 49 post-implantation. In a second, larger cohort of rats, ¹⁸F-FET PET/CEST MRI was performed in mature tumors (day 49 post-implantation) for biomarker determination, followed by evaluation of single and combination therapy as part of the model development and validation. The mean percentage of the injected dose per mL of ¹⁸F-FET PET correlated with the mean %CEST (r = 0.67, P < 0.05), but there was also a qualitative difference in hot spot location within the tumor, indicating complementary information regarding the tumor cell demand for amino acids and tumor intracellular mobile phase protein levels. Finally, the use of this glioblastoma animal model for therapy assessment was validated by its increased overall survival after treatment with combination therapy (temozolomide and idasanutlin) (P < 0.001). Our findings hold promise for a more accurate tumor viability determination and novel therapy assessment in vivo in a recently developed, reproducible, intracranial, PDX GBM.

An updated review on the diagnosis and assessment of post-treatment relapse in brain metastases using PET

INTRODUCTION

Brain metastases in patients with extracranial cancer are typically associated with increased morbidity and mortality. Stereotactic radiotherapy and immunotherapy using checkpoint inhibitors currently are essential in brain metastases treatment. Since conventional contrast-enhanced MRI alone cannot reliably differentiate between treatment-induced changes and brain metastasis relapse, several studies investigated the role of PET imaging and, more recently, radiomics, based on routinely acquired PET images, to overcome this clinically relevant challenge.

AREAS COVERED

The current literature on PET imaging, including radiomics, in patients with brain metastases, focusing on the diagnosis and assessment of post-treatment relapse, is summarized.

EXPERT OPINION

Available data suggest that imaging parameters, including radiomics features, mainly derived from amino acid PET, are helpful for diagnosis and assessment of post-treatment relapse in patients with brain metastases.

Lateral Heterostructured Vis-NIR Photodetectors with Multimodal Detection for Rapid and Precise Classification of Glioma

Precise diagnosis of the boundary and grade of tumors is especially important for surgical dissection. Recently, visible and near-infrared (Vis-NIR) absorption differences of tumors are demonstrated for a precise tumor diagnosis. Here, a template-assisted sequential printing strategy is investigated to construct lateral heterostructured Vis-NIR photodetectors, relying on the up-conversion nanoparticles (UCNPs)/perovskite arrays. Under the sequential printing process, the synergistic effect and co-confinement are demonstrated to induce the UCNPs to cover both sides of the perovskite microwire. The side-wrapped lateral heterogeneous UCNPs/perovskite structure exhibits more satisfactory responsiveness to Vis-NIR light than the common fully wrapped structure, due to sufficient visible-light-harvesting ability. The Vis-NIR photodetectors with R reaching 150 mA W^-1 at 980 nm and 1084 A W^-1 at 450 nm are employed for the rapid classification of glioma. The detection accuracy rate of 99.3% is achieved through a multimodal analysis covering the Vis-NIR light, which provides a reliable basis for glioma grade diagnosis. This work provides a concrete example for the application of photodetectors in tumor detection and surgical diagnosis.

11 C-Acetate PET/CT Detects Reactive Astrogliosis Helping Glioma Classification

PURPOSE

11 C-acetate ( 11 C-ACE) uptake on PET/CT was recently discovered to represent reactive astrocytes in the tumor microenvironment. This study aimed at evaluating the role of 11 C-ACE PET/CT as an imaging biomarker of reactive astrogliosis in characterizing different types of gliomas.

METHODS

In this prospective study, a total of 182 patients underwent 11 C-ACE PET/CT before surgery. The ratio of SUV max of a glioma to the SUV mean of the contralateral choroid plexus ( 11 C-ACE TCR) on PET/CT was calculated. 11 C-ACE TCRs were compared with the World Health Organization grades and isocitrate dehydrogenase 1 ( IDH1 ) mutation status. Grade 2 was considered low-grade tumor, and grades 3 and 4 were considered high-grade tumors.

RESULTS

The median 11 C-ACE TCR was significantly higher in IDH1 wild-type (wt) tumors (n = 91) than in IDH1 -mutant (mt) tumors (n = 91) (2.38 vs 1.30, P < 0.001). Of the 91 IDH1 -mt tumors, there were no differences in the median 11 C-ACE TCRs between oligodendrogliomas (ODs) and astrocytic tumors (1.40 vs 1.20, P > 0.05). In grading low- versus high-grade gliomas, the receiver operating characteristic curve analyses showed a higher area under the curve (0.951) in IDH1 -wt tumors than in IDH1 -mt tumors (0.783, P = 0.002). Grade 2 ODs were well differentiated from high-grade gliomas. The 11 C-ACE TCR of grade 3 ODs was significantly lower than that of IDH1 -wt glioblastomas.

CONCLUSIONS

High 11 C-ACE uptake is associated with high-grade IDH1 -wt tumors, thus facilitating differentiation from high-grade IDH1-mt and low-grade gliomas. In particular, low 11 C-ACE uptake in ODs is advantageous in overcoming the limitation of radiolabeled amino acid tracers.

Updates in IDH-Wildtype Glioblastoma

Glioblastoma is the most aggressive primary brain tumor with a poor prognosis. The 2021 WHO CNS5 classification has further stressed the importance of molecular signatures in diagnosis although therapeutic breakthroughs are still lacking. In this review article, updates on the current and novel therapies in IDH-wildtype GBM will be discussed.