Uptake and tracer kinetics of O-(2-(18)F-fluoroethyl)-L-tyrosine in meningiomas: preliminary results

11C-Methionine uptake in meningiomas after stereotactic radiotherapy

OBJECTIVE

11C-Methionine positron emission tomography (MET-PET) is used for stereotactic radiotherapy planning in meningioma patients. The role of MET-PET during subsequent follow-up (FU) is unclear. We analyzed the uptake of 11C-Methionine before and after stereotactic radiotherapy (SRT) in patients with a complex meningioma and investigated if there was a difference between patients with progressive disease (PD) and stable disease (SD) during FU.

METHODS

This retrospective study investigates 62 MET-PETs in 29 complex meningioma patients. Standardized uptake value (SUV)max and SUVpeak tumor-to-normal ratios (T/N-ratios) were calculated, comparing the tumor region with both the mirroring intracranial area and the right frontal gray matter. The difference in 11C-Methionine uptake pre- and post-SRT was analyzed, as well as the change in uptake between PD or SD.

RESULTS

Median (IQR) FU duration was 67 months (50.5-91.0). The uptake of 11C-Methionine in meningiomas remained increased after SRT. Neither a statistically significant difference between MET-PETs before and after SRT was encountered, nor a significant difference in one of the four T/N-ratios between patients with SD versus PD with median (IQR) SUVmax T/NR front 2.65 (2.13-3.68) vs 2.97 (1.55-3.54) [p = 0.66]; SUVmax T/Nmirror 2.92 (2.19-3.71) vs 2.95 (1.74-3.60) [p = 0.61]; SUVpeak T/NR front 2.35 (1.64-3.40) vs 2.25 (1.44-3.74) [p = 0.80]; SUVpeak T/Nmirror 2.38 (1.91-3.36) vs 2.35 (1.56-3.72) [p = 0.95].

CONCLUSIONS

Our data do not support use of MET-PET during FU of complex intracranial meningiomas after SRT. MET-PET could not differentiate between progressive or stable disease.

Prediction of Meningioma Grade Using Hematological Parameters

OBJECTIVE

Predicting the aggressiveness of meningiomas may influence the surgical strategy timing. Because of the paucity of robust markers, the systemic immune-inflammation (SII) index is a novel biomarker to be an independent predictor of poor prognosis in various cancers including gliomas. We aimed to investigate the value of SII as well as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) indices in predicting prognosis.

METHODS

Records including demographic, clinical, and laboratory data of patients operated on due to intracranial meningioma in 2017-2023 were retrospectively reviewed.

RESULTS

A total of 234 patients were included in this study. All of SII index, NLR, and PLR values at presentation were significantly higher in grade ≥2 meningiomas. A positive correlation was observed between SII index and Ki67 index (r=0.313; P<0.001); between NLR and Ki67 index (r=0.330; P<0.001); and between PLR and Ki67 index (r=0.223; P<0.01). SII index (optimal cutoff level >618), NLR (optimal cutoff level >3.53), and PLR (optimal cutoff level >121.2) showed significant predictive values.

CONCLUSIONS

This is the first study to assess the prognostic value of the SII index in patients with intracranial meningiomas. Increased SII index, NLR and PLR were correlated with higher grade and higher Ki-67 index. They also harbor the potential to screen patients that may need more aggressive treatments or more frequent follow-up examinations.

Meningioma grading based on positron emission tomography: A systematic review and meta-analysis

Introduction

Meningiomas are the most common central nervous system tumor in adults. Knowledge of the tumor grade can guide optimal treatment timing and shape personalized follow-up strategies. Positron emission tomography (PET) has been utilized for the metabolic assessment of various intracranial space-occupying lesions. Herewith, we set out to evaluate the diagnostic accuracy of PET for the noninvasive assessment of meningioma's grade.

Materials and methods

The Medline, Scopus and Cochrane databases were systematically searched in March 2022 for studies that evaluated the sensitivity and specificity of PET compared to the gold standard of histological diagnosis in the grading of meningiomas. Summary statistics will be calculated and scatter plots, summary curve from the HSROC model and posterior predictions by empirical Bayes estimates will be presented.

Results

Five studies consisting of 242 patients with a total of 196 low-grade (Grade 1) and 46 high grade (Grade 2/3) meningiomas were included in our analysis. Three of the included studies used ¹⁸F-FDG, one study used ¹⁸F-FLT and one used(Whiting et al., 2011) 18 F-FET as PET tracers. The pooled sensitivity was 76% (95% CI: 52%-91%) and the pooled specificity was 89% (95% CI: 83%-93%). The diagnostic odds ratio was 27.17 (95% CI: 9.22-80.06), the positive likelihood ratio was 7.18 (95% CI: 4.54-11.34) and the negative likelihood ratio was 0.26 (95% CI: 0.11-0.61).

Conclusion

PET is a promising and viable option as a noninvasive imaging tool to differentiate the meningioma grades. However, currently it cannot overtake the gold standard of histological grade confirmation. More studies are required for further validation and refinement of this imaging technique and assessment of other radiotracers as well.

Imaging Characteristics of Meningiomas

Contemporary neuroimaging of meningiomas has largely relied on computed tomography, and more recently magnetic resonance imaging. While these modalities are frequently used in nearly all clinical settings where meningiomas are treated for the routine diagnosis and follow-up of these tumors, advances in neuroimaging have provided novel opportunities for prognostication and treatment planning (including both surgical planning and radiotherapy planning). These include perfusion MRIs, and positron emission tomography (PET) imaging modalities. Here we will summarize the contemporary uses for neuroimaging in meningiomas, and future applications of novel, cutting edge imaging techniques that may be routinely implemented in the future to enable more precise treatment of these challenging tumors.

Molecular determinants of outcomes in meningiomas

Meningiomas are the most common intracranial primary tumor in adults. Surgery is the predominant therapeutic modality for symptomatic meningiomas. Although the majority of meningiomas are benign, there exists a subset of meningiomas that are clinically aggressive. Recent advances in genetics and epigenetics have uncovered molecular alterations that drive tumor meningioma biology with prognostic and therapeutic implications. In this review, we will discuss the advances on molecular determinants of therapeutic response in meningiomas to date and discuss findings of targeted therapies in meningiomas.

Use of advanced neuroimaging and artificial intelligence in meningiomas

Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion‐weighted imaging, diffusion‐weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular‐genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma.

Cellular and Molecular Imaging with SPECT and PET in Brain Tumors

This review highlights the 2 major molecular imaging modalities that are used in clinics, namely single-photon emission computed tomography (SPECT) and positron emission tomography (PET), and their added value in management of patients with brain tumors. There are a variety of SPECT and PET radiotracers that can allow imaging of different molecular processes. Those radiotracers target specific molecular features of tumors, resulting in improved specificity of these agents. Potential applications include staging of brain tumors and evaluating post-therapeutic changes.

Use of PET Imaging in Neuro-Oncological Surgery

Simple Summary

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

Abstract

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

Prediction of Meningioma WHO Grade Using PET Findings: A Systematic Review and Meta-Analysis

BACKGROUND AND PURPOSE

World Health Organization (WHO) grading of meningiomas reflects recurrence rate and prognosis. Positron emission tomography (PET) investigates metabolic activity, allowing for distinction between low- and high-grade tumors. As preoperative suspicion for malignant meningioma will influence surgical strategy in terms of timing, extent of resection, and risks taken to achieve a total resection, we systematically reviewed the literature on PET-imaging in meningiomas and relate these findings to histopathological analysis.

METHODS

Searches in PubMed, EMBASE, and The Cochrane Library, from inception to September 2019, included studies of patients who had undergone surgery for a histologically verified intracranial meningioma, with a PET-scan prior to surgery and description of (semi)quantitative PET values for meningiomas from two different WHO groups. Studies comparing more than 1 patient per WHO group were included in the meta-analysis.

RESULTS

Twenty-two studies (432 patients) were included. 18fluor-fluorodesoxyglucose (18F-FDG) PET was mostly described to differentiate benign from malignant meningiomas. Pooled data showed differences in mean (95% CI) Standardized Uptake Value (SUV) for WHO II/III compared to WHO I of 2.51 (1.36, 3.66), and in tumor-to-normal (T/N) ratio (T/N ratio) for WHO II/III versus WHO I of .42 (.12, .73).

CONCLUSIONS

We found that SUV and T/N ratio in 18F-FDG PET may be useful to noninvasively differentiate benign from malignant meningiomas. T/N ratio seems to have a high specificity for the detection of high-grade meningiomas. Other PET tracers were studied too infrequently to draw definitive conclusions. Before treatment strategies can be adapted based on 18F-FDG PET, prospective studies in larger cohorts are warranted to validate the optimal T/N ratio cutoff point.

ADC values of benign and high grade meningiomas and associations with tumor cellularity and proliferation - A systematic review and meta-analysis

INTRODUCTION

The aim of the present systematic review and meta-analysis was to compare the reported ADC values in different meningiomas and to analyze associations between ADC and cell count and proliferation activity in this tumor entity.

METHOD

MEDLINE library and SCOPUS database were screened for papers investigating ADC values of meningiomas up November 2019. The first primary endpoint of the systematic review was the reported ADC mean value of the meningioma groups. The second primary endpoint was the correlation coefficient between ADC values and proliferation index Ki 67 and cellularity.

RESULTS

For the discrimination analysis between benign and high grade meningioma 17 studies were suitable. There were 766 grade I tumors and 289 high grade meningiomas. The calculated mean ADC value of the benign grade I tumors was 0.93 × 10^-3mm²/s [95%-Confidence interval 0.84;1.03] and the mean value of the high-grade tumors was 0.77 × 10^-3mm²/s [95%-Confidence interval 0.73-0.80]. The pooled correlation coefficient between ADC and the proliferation index Ki 67 was r = -0.36 [95% CI -0.43; -0.28]. The pooled correlation coefficient between ADC and cellularity was r = -0.43 [95% CI -0.61; - 0.26].

CONCLUSION

No validated ADC threshold can be recommended for distinguishing benign from high grade meningiomas. Only a moderate inverse correlation was identified between ADC values and tumor microstructure in meningiomas and, therefore, ADC might not accurately enough to predict proliferation potential and cellularity in this entity.

Magnetic resonance imaging-based 3-dimensional fractal dimension and lacunarity analyses may predict the meningioma grade

OBJECTIVE

To assess whether 3-dimensional (3D) fractal dimension (FD) and lacunarity features from MRI can predict the meningioma grade.

METHODS

This retrospective study included 131 patients with meningiomas (98 low-grade, 33 high-grade) who underwent preoperative MRI with post-contrast T1-weighted imaging. The 3D FD and lacunarity parameters from the enhancing portion of the tumor were extracted by box-counting algorithms. Inter-rater reliability was assessed with the intraclass correlation coefficient (ICC). Additionally, conventional imaging features such as location, heterogeneous enhancement, capsular enhancement, and necrosis were assessed. Independent clinical and imaging risk factors for meningioma grade were investigated using multivariable logistic regression. The discriminative value of the prediction model with and without fractal features was evaluated. The relationship of fractal parameters with the mitosis count and Ki-67 labeling index was also assessed.

RESULTS

The inter-reader reliability was excellent, with ICCs of 0.99 for FD and 0.97 for lacunarity. High-grade meningiomas had higher FD (p < 0.001) and higher lacunarity (p = 0.007) than low-grade meningiomas. In the multivariable logistic regression, the diagnostic performance of the model with clinical and conventional imaging features increased with 3D fractal features for predicting the meningioma grade, with AUCs of 0.78 and 0.84, respectively. The 3D FD showed significant correlations with both mitosis count and Ki-67 labeling index, and lacunarity showed a significant correlation with the Ki-67 labeling index (all p values < 0.05).

CONCLUSION

The 3D FD and lacunarity are higher in high-grade meningiomas and fractal analysis may be a useful imaging biomarker for predicting the meningioma grade.

KEY POINTS

• Fractal dimension (FD) and lacunarity are the two parameters used in fractal analysis to describe the complexity of a subject and may aid in predicting meningioma grade. • High-grade meningiomas had a higher fractal dimension and higher lacunarity than low-grade meningiomas, suggesting higher complexity and higher rotational variance. • The discriminative value of the predictive model using clinical and conventional imaging features improved when combined with 3D fractal features for predicting the meningioma grade.

In vivo imaging of cell proliferation in meningioma using 3'-deoxy-3'-[18F]fluorothymidine PET/MRI

PURPOSE

Positron emission tomography (PET) with 3'-deoxy-3'-[¹⁸F]fluorothymidine ([¹⁸F]FLT) provides a noninvasive assessment of tumour proliferation in vivo and could be a valuable imaging modality for assessing malignancy in meningiomas. We investigated a range of static and dynamic [¹⁸F]FLT metrics by correlating the findings with cellular biomarkers of proliferation and angiogenesis.

METHODS

Seventeen prospectively recruited adult patients with intracranial meningiomas underwent a 60-min dynamic [¹⁸F]FLT PET following surgery. Maximum and mean standardized uptake values (SUV_max, SUV_mean) with and without normalization to healthy brain tissue and blood radioactivity obtained from 40 to 60 min summed dynamic images (PET_40-60) and ~ 60-min blood samples were calculated. Kinetic modelling using a two-tissue reversible compartmental model with a fractioned blood volume (V_B) was performed to determine the total distribution volume (V_T). Expressions of proliferation and angiogenesis with key parameters including Ki-67 index, phosphohistone-H3 (phh3), MKI67, thymidine kinase 1 (TK1), proliferating cell nuclear antigen (PCNA), Kirsten RAt Sarcoma viral oncogene homolog (KRAS), TIMP metallopeptidase inhibitor 3 (TIMP3), and vascular endothelial growth factor A (VEGFA) were determined by immunohistochemistry and/or quantitative polymerase chain reaction.

RESULTS

Immunohistochemistry revealed 13 World Health Organization (WHO) grade I and four WHO grade II meningiomas. SUV_max and SUV_mean normalized to blood radioactivity from PET_40-60 and blood sampling, and V_T were able to significantly differentiate between WHO grades with the best results for maximum and mean tumour-to-whole-blood ratios (sensitivity 100%, specificity 94-95%, accuracy 99%; P = 0.003). Static [¹⁸F]FLT metrics were significantly correlated with proliferative biomarkers, especially Ki-67 index, phh3, and TK1, while no correlations were found with VEGFA or V_B. Using Ki-67 index with a threshold > 4%, the majority of [¹⁸F]FLT metrics showed a high ability to identify aggressive meningiomas with SUV_mean demonstrating the best performance (sensitivity 80%, specificity 81%, accuracy 80%; P = 0.024).

CONCLUSION

[¹⁸F]FLT PET could be a useful imaging modality for assessing cellular proliferation in meningiomas.

Theragnostic Use of Radiolabelled Dota-Peptides in Meningioma: From Clinical Demand to Future Applications

Meningiomas account for approximately 30% of all new diagnoses of intracranial masses. The 2016 World Health Organization's (WHO) classification currently represents the clinical standard for meningioma's grading and prognostic stratification. However, watchful waiting is frequently the chosen treatment option, although this means the absence of a certain histological diagnosis. Consequently, MRI (or less frequently CT) brain imaging currently represents the unique available tool to define diagnosis, grading, and treatment planning in many cases. Nonetheless, these neuroimaging modalities show some limitations, particularly in the evaluation of skull base lesions. The emerging evidence supporting the use of radiolabelled somatostatin receptor analogues (such as dota-peptides) to provide molecular imaging of meningiomas might at least partially overcome these limitations. Moreover, their potential therapeutic usage might enrich the current clinical offering for these patients. Starting from the strengths and weaknesses of structural and functional neuroimaging in meningiomas, in the present article we systematically reviewed the published studies regarding the use of radiolabelled dota-peptides in surgery and radiotherapy planning, in the restaging of treated patients, as well as in peptide-receptor radionuclide therapy of meningioma.

Uptake and Tracer Kinetic of O-(2-(18)F-fluoroethyl)-L-Tyrosine in Meningioma

F-fluoroethyltyrosine (FET) is a well-established PET tracer for the imaging of cerebral gliomas. Recent studies reported interest in meningiomas. A study published by Cornelius et al concludes that FET PET may provide additional information for noninvasive grading of meningiomas. Indeed, the combination of tumor background ratio with a cutoff value of 2.3 associated with time activity curve pattern slightly improved the differentiation of high-grade from low-grade meningiomas (accuracy, 92%; P = 0.001). We present the case of a 75-year-old man that underlined the need to confirm the performance of these tools (curve pattern, tumor background ratios) to characterize meningiomas.

Diagnostic challenges in meningioma

Advances in molecular profiling and the application of advanced imaging techniques are currently refreshing diagnostic considerations in meningioma patients. Not only technical refinements but also sophisticated histopathological and molecular studies have the potential to overcome some of the challenges during meningioma management. Exact tumor delineation, assessment of tumor growth, and pathophysiological parameters were recently addressed by "advanced" MRI and PET. In the field of neuropathology, high-throughput sequencing and DNA methylation analysis of meningioma tissue has greatly advanced the knowledge of molecular aberrations in meningioma patients. These techniques allow for more reliable prediction of the biological behavior and clinical course of meningiomas and subsequently have the potential to guide individualized meningioma therapy. However, higher costs and longer duration of full molecular work-up compared with histological assessment may delay the implementation into clinical routine.This review highlights the diagnostic challenges of meningiomas from both the neuroimaging as well as the neuropathological side and presents the latest scientific achievements and studies potentially helping in overcoming these challenges. It complements the recently proposed European Association of Neuro-Oncology guidelines on treatment and diagnosis of meningiomas by integrating data on nonstandard imaging and molecular assessments most likely impacting the future.

11C-Methionine Positron Emission Tomography/Computed Tomography Versus 18F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in Evaluation of Residual or Recurrent World Health Organization Grades II and III Meningioma After Treatment

OBJECTIVE

The aim of this study was to determine the assessment of positron emission tomography-computed tomography using C-methionine (MET PET/CT) for World Health Organization (WHO) grades II and III meningiomas; MET PET/CT was compared with PET/CT using F-fluorodeoxy glucose (FDG PET/CT).

METHODS

This study was performed in 17 cases with residual and/or recurrent WHO grades II and III meningiomas. Two neuroradiologists reviewed both PET/CT scans. For agreement, the κ coefficient was measured. Difference in tumor-to-normal brain uptake ratios (T/N ratios) between 2 PET/CT scans was analyzed. Correlation between the maximum tumor size and T/N ratio in PET/CT was studied.

RESULTS

For agreement by both reviewers, the κ coefficient was 0.51 (P < 0.05). The T/N ratio was significantly higher for MET PET/CT (3.24 ± 1.36) than for FDG PET/CT (0.93 ± 0.44) (P < 0.01). C-methionine ratio significantly correlated with tumor size (y = 8.1x + 16.3, n = 22, P < 0.05), but FDG ratio did not CONCLUSIONS: C-methionine PET/CT has superior potential for imaging of WHO grades II and III meningiomas with residual or recurrent tumors compared with FDG PET/CT.

PET imaging in patients with meningioma-report of the RANO/PET Group

Meningiomas are the most frequent nonglial primary brain tumors and represent about 30% of brain tumors. Usually, diagnosis and treatment planning are based on neuroimaging using mainly MRI or, rarely, CT. Most common treatment options are neurosurgical resection and radiotherapy (eg, radiosurgery, external fractionated radiotherapy). For follow-up after treatment, a structural imaging technique such as MRI or CT is used. However, these structural imaging modalities have limitations, particularly in terms of tumor delineation as well as diagnosis of posttherapeutic reactive changes. Molecular imaging techniques such as PET can characterize specific metabolic and cellular features which may provide clinically relevant information beyond that obtained from structural MR or CT imaging alone. Currently, the use of PET in meningioma patients is steadily increasing. In the present article, we provide recommendations for the use of PET imaging in the clinical management of meningiomas based on evidence generated from studies being validated by histology or clinical course.

Comparison of five cluster validity indices performance in brain [18 F]FET-PET image segmentation using k-means

PURPOSE

Dynamic [¹⁸ F]fluoro-ethyl-L-tyrosine positron emission tomography ([¹⁸ F]FET-PET) is used to identify tumor lesions for radiotherapy treatment planning, to differentiate glioma recurrence from radiation necrosis and to classify gliomas grading. To segment different regions in the brain k-means cluster analysis can be used. The main disadvantage of k-means is that the number of clusters must be pre-defined. In this study, we therefore compared different cluster validity indices for automated and reproducible determination of the optimal number of clusters based on the dynamic PET data.

METHODS

The k-means algorithm was applied to dynamic [¹⁸ F]FET-PET images of 8 patients. Akaike information criterion (AIC), WB, I, modified Dunn's and Silhouette indices were compared on their ability to determine the optimal number of clusters based on requirements for an adequate cluster validity index. To check the reproducibility of k-means, the coefficients of variation CVs of the objective function values OFVs (sum of squared Euclidean distances within each cluster) were calculated using 100 random centroid initialization replications RCI₁₀₀ for 2 to 50 clusters. k-means was performed independently on three neighboring slices containing tumor for each patient to investigate the stability of the optimal number of clusters within them. To check the independence of the validity indices on the number of voxels, cluster analysis was applied after duplication of a slice selected from each patient. CVs of index values were calculated at the optimal number of clusters using RCI₁₀₀ to investigate the reproducibility of the validity indices. To check if the indices have a single extremum, visual inspection was performed on the replication with minimum OFV from RCI₁₀₀ .

RESULTS

The maximum CV of OFVs was 2.7 × 10^-2 from all patients. The optimal number of clusters given by modified Dunn's and Silhouette indices was 2 or 3 leading to a very poor segmentation. WB and I indices suggested in median 5, [range 4-6] and 4, [range 3-6] clusters, respectively. For WB, I, modified Dunn's and Silhouette validity indices the suggested optimal number of clusters was not affected by the number of the voxels. The maximum coefficient of variation of WB, I, modified Dunn's, and Silhouette validity indices were 3 × 10^-2 , 1, 2 × 10^-1 and 3 × 10^-3 , respectively. WB-index showed a single global maximum, whereas the other indices showed also local extrema.

CONCLUSION

From the investigated cluster validity indices, the WB-index is best suited for automated determination of the optimal number of clusters for [¹⁸ F]FET-PET brain images for the investigated image reconstruction algorithm and the used scanner: it yields meaningful results allowing better differentiation of tissues with higher number of clusters, it is simple, reproducible and has an unique global minimum.

68Gallium-DOTATATE PET in meningioma: A reliable predictor of tumor growth rate?

BACKGROUND

DOTATATE-based radionuclides have added new options in the diagnosis and treatment of meningiomas; however, a reliable predictor of tumor growth has still not been established.

METHODS

We analyzed 64 meningiomas imaged with (68)Ga-DOTATATE PET. Tumor growth rates were calculated by volumetric analysis of sequential MRI scans. Maximums of standardized uptake values (SUVmax) were correlated with tumor growth and covariates.

RESULTS

World Health Organization (WHO) grades I and II meningiomas showed a correlation of SUVmax and tumor growth rate (meningiomas limited to the intracranial compartment: r = 0.757, P < .001, and transosseous growing meningiomas: r = 0.819, P = .024). SUVmax was significantly higher and the slope of the linear regression significantly steeper in transosseous compared with intracranial meningiomas (both P < .001). The association remained significant in multivariate analysis, and the prediction of tumor growth rate was independent of WHO grade. Anaplastic meningiomas showed no significant correlation of SUVmax and tumor growth.

CONCLUSIONS

(68)Ga-DOTATATE PET is a reliable predictor of tumor growth in WHO grades I and II meningiomas and provides additional information to conventional cross-sectional imaging modalities. Hence, (68)Ga-DOTATATE PET can assist in selecting the time point for treatment initiation. Furthermore, meningiomas with fast tumor growth and transosseous expansion elicit the highest DOTATATE binding; therefore, they might be especially suited for DOTATATE-based therapy.

Use of Diffusion Weighted Imaging in Differentiating Between Maligant and Benign Meningiomas. A Multicenter Analysis

BACKGROUND

Meningioma is the most frequent intracranial tumor and is often an incidental finding on imaging. Some imaging-based scores were suggested for differentiating low- and high-grade meningiomas. The purpose of this work was to compare diffusion-weighted imaging findings of different meningiomas in a large multicenter study by using apparent diffusion coefficient (ADC) values for predicting tumor grade and proliferation potential.

METHODS

Data from 7 radiologic departments were acquired retrospectively. Overall, 389 patients were collected. All meningiomas were investigated by magnetic resonance imaging (1.5-T scanner) by using diffusion-weighted imaging (b values of 0 and 1000 s/mm(2)). The comparison of ADC values was performed by Mann-Whitney U test.

RESULTS

World Health Organization grade I was diagnosed in 271 cases (69.7%), grade II in 103 (26.5%), and grade III in 15 patients (3.9%). Grade I meningiomas showed statistically significant higher ADC values (1.05 ± 0.39 × 10(-3) mm(2)s(-1)) in comparison with grade II (0.77 ± 0.15 × 10(-3) mm(2)s(-1); P = 0.001) and grade III tumors (0.79 ± 0.21 × 10(-3) mm(2)s(-1); P = 0.01). An ADC value of <0.85 × 10(-3) mm(2)s(-1) was determined as the threshold in differentiating between grade I and grade II/III meningiomas (sensitivity, 72.9%; specificity, 73.1%; accuracy, 73.0%). Ki67 was associated with ADC (r = -0.63, P < 0.001). The optimal threshold for the ADC was (less than) 0.85 × 10(-3) mm(2)s(-1) for detecting tumors with high proliferation potential (Ki67 ≥5%).

CONCLUSIONS

The estimated threshold ADC value of 0.85 can differentiate grade I meningioma from grade II and III tumors. The same ADC value is helpful for detecting tumors with high proliferation potential.

From the clinician's point of view - What is the status quo of positron emission tomography in patients with brain tumors?

The most common type of primary brain tumor is malignant glioma. Despite intensive therapeutic efforts, the majority of these neoplasms remain incurable. Imaging techniques are important for initial tumor detection and comprise indispensable tools for monitoring treatment. Structural imaging using contrast-enhanced MRI is the method of choice for brain tumor surveillance, but its capacity to differentiate tumor from nonspecific tissue changes can be limited, particularly with posttreatment gliomas. Metabolic imaging using positron-emission-tomography (PET) can provide relevant additional information, which may allow for better assessment of tumor burden in ambiguous cases. Specific PET tracers have addressed numerous molecular targets in the last decades, but only a few have achieved relevance in routine clinical practice. At present, PET studies using radiolabeled amino acids appear to improve clinical decision-making as these tracers can offer better delineation of tumor extent as well as improved targeting of biopsies, surgical interventions, and radiation therapy. Amino acid PET imaging also appears useful for distinguishing glioma recurrence or progression from postradiation treatment effects, particularly radiation necrosis and pseudoprogression, and provides information on histological grading and patient prognosis. In the last decade, the tracers O-(2-[(18)F]fluoroethyl)-L-tyrosine (FET) and 3,4-dihydroxy-6-[(18)F]-fluoro-L-phenylalanine (FDOPA) have been increasingly used for these indications. This review article focuses on these tracers and summarizes their recent applications for patients with brain tumors. Current uses of tracers other than FET and FDOPA are also discussed, and the most frequent practical questions regarding PET brain tumor imaging are reviewed.

Molecular imaging correlates of tryptophan metabolism via the kynurenine pathway in human meningiomas

BACKGROUND

Increased tryptophan metabolism via the kynurenine pathway (KP) is a key mechanism of tumoral immune suppression in gliomas. However, details of tryptophan metabolism in meningiomas have not been elucidated. In this study, we evaluated in vivo tryptophan metabolism in meningiomas and compared it with gliomas using α-[(11)C]-methyl-L-tryptophan (AMT)-PET. We also explored expression patterns of KP enzymes in resected meningiomas.

METHODS

Forty-seven patients with MRI-detected meningioma (n = 16) and glioma (n = 31) underwent presurgical AMT-PET scanning. Tumoral AMT uptake and tracer kinetic parameters (including K and k3' evaluating unidirectional uptake and trapping, respectively) were measured, correlated with meningioma grade, and compared between meningiomas and gliomas. Patterns of KP enzyme expression were assessed by immunohistochemistry in all meningiomas.

RESULTS

Meningioma grade showed a positive correlation with AMT k3' tumor/cortex ratio (r = 0.75, P = .003), and this PET parameter distinguished grade I from grade II/III meningiomas with 92% accuracy. Kinetic AMT parameters could differentiate meningiomas from both low-grade gliomas (97% accuracy by k3' ratios) and high-grade gliomas (83% accuracy by K ratios). Among 3 initial KP enzymes (indoleamine 2,3-dioxygenase 1/2, and tryptophan 2,3-dioxygenase 2 [TDO2]), TDO2 showed the strongest immunostaining, particularly in grade I meningiomas. TDO2 also showed a strong negative correlation with AMT k3' ratios (P = .001).

CONCLUSIONS

PET imaging of tryptophan metabolism can provide quantitative imaging markers for differentiating grade I from grade II/III meningiomas. TDO2 may be an important driver of in vivo tryptophan metabolism in these tumors. These results can have implications for pharmacological targeting of the KP in meningiomas.