Volumetry of [(11)C]-methionine PET uptake and MRI contrast enhancement in patients with recurrent glioblastoma multiforme

Current Status and Future Perspective in Glioma Invasion Research

Glioblastoma (GBM) is the most malignant brain tumor in adults and shows an extremely poor prognosis, with a median survival of 15 months [...].

Qualitative MR features to identify non-enhancing tumors within glioblastoma's T2-FLAIR hyperintense lesions

PURPOSE

To identify qualitative MRI features of non-(contrast)-enhancing tumor (nCET) in glioblastoma's T2-FLAIR hyperintense lesion.

METHODS

Thirty-three histologically confirmed glioblastoma patients whose T1-, T2- and contrast-enhanced T1-weighted MRI and 11C-methionine positron emission tomography (Met-PET) were available were included in this study. Met-PET was utilized as a surrogate for tumor burden. Imaging features for identifying nCET were searched by qualitative examination of 156 targets. A new scoring system to identify nCET was established and validated by two independent observers.

RESULTS

Three imaging features were found helpful for identifying nCET; "Bulky gray matter involvement", "Around the rim of contrast-enhancement (Around-rim)," and "High-intensity on T1WI and low-intensity on T2WI (HighT1LowT2)" resulting in an nCET score = 2 × Bulky gray matter involvement - 2 × Around-rim + HighT1LowT2 + 2. The nCET score's classification performances of two independent observers measured by AUC were 0.78 and 0.80, with sensitivities and specificities using a threshold of four being 0.443 and 0.771, and 0.916 and 0.768, respectively. The weighted kappa coefficient for the nCET score was 0.946.

CONCLUSION

The current investigation demonstrated that qualitative assessments of glioblastoma's MRI might help identify nCET in T2/FLAIR high-intensity lesions. The novel nCET score is expected to aid in expanding treatment targets within the T2/FLAIR high-intensity lesions.

Initial Experience of 18 F-FET PET-MR Image Fusion for Evaluation of Recurrent Primary Brain Tumors

Background  An accurate monitoring technique is crucial in brain tumors to choose the best treatment approach after surgery and/or chemoradiation. Radiological assessment of brain tumors is widely based on the magnetic resonance imaging (MRI) modality in this regard; however, MRI criteria are unable to precisely differentiate tumoral tissue from treatment-related changes. This study was conducted to evaluate whether fused MRI and O-(2- 18 F-fluoroethyl)-L-tyrosine ( 18 F-FET) positron emission tomography (PET) can improve the diagnostic accuracy of the practitioners to discriminate treatment-related changes from true recurrence of brain tumor. Methods  We retrospectively analyzed 18 F-FET PET/computed tomography (CT) of 11 patients with histopathologically proven brain tumors that were suspicious for recurrence changes after 3 to 4 months of surgery. All the patients underwent MRI and 18 F-FET PET/CT. As a third assessment, fused 18 F-FET PET/MRI was also acquired. Finally, the diagnostic accuracy of the applied modalities was compared. Results  Eleven patients aged 27 to 73 years with a mean age of 47 ± 13 years were enrolled. According to the results, 9/11 cases (82%) showed positive MRI and 6 cases (55%) showed positive PET/CT and PET/MRI. Tumoral recurrence was observed in six patients (55%) in the follow-up period. Based on the follow-up results, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 64, 85, 25, 67, and 50%, respectively, for MRI alone and 91, 85, 100, 100, and 80%, respectively, for both PET/CT and PET/MRI. Conclusion  This study found that 18 F-FET PET-MR image fusion in the management of brain tumors might improve recurrence detection; however, further well-designed studies are needed to verify these preliminary data.

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.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Role of Molecular Imaging with PET/MR Imaging in the Diagnosis and Management of Brain Tumors

Gliomas are the most common primary brain tumors. Hybrid PET/MR imaging has revolutionized brain tumor imaging, allowing for noninvasive, simultaneous assessment of morphologic, functional, metabolic, and molecular parameters within the brain. Molecular information obtained from PET imaging may aid in the detection, classification, prognostication, and therapeutic decision making for gliomas. ¹⁸F-fluorodeoxyglucose (FDG) has been widely used in the setting of brain tumor imaging, and multiple techniques may be employed to optimize this methodology. More recently, a number of non-¹⁸F-FDG-PET radiotracers have been applied toward brain tumor imaging and are used in clinical practice.

Prediction and Visualization of Non-Enhancing Tumor in Glioblastoma via T1w/T2w-Ratio Map

One of the challenges in glioblastoma (GBM) imaging is to visualize non-enhancing tumor (NET) lesions. The ratio of T1- and T2-weighted images (rT1/T2) is reported as a helpful imaging surrogate of microstructures of the brain. This research study investigated the possibility of using rT1/T2 as a surrogate for the T1- and T2-relaxation time of GBM to visualize NET effectively. The data of thirty-four histologically confirmed GBM patients whose T1-, T2- and contrast-enhanced T1-weighted MRI and ¹¹C-methionine positron emission tomography (Met-PET) were available were collected for analysis. Two of them also underwent MR relaxometry with rT1/T2 reconstructed for all cases. Met-PET was used as ground truth with T2-FLAIR hyperintense lesion, with >1.5 in tumor-to-normal tissue ratio being NET. rT1/T2 values were compared with MR relaxometry and Met-PET. rT1/T2 values significantly correlated with both T1- and T2-relaxation times in a logarithmic manner (p < 0.05 for both cases). The distributions of rT1/T2 from Met-PET high and low T2-FLAIR hyperintense lesions were different and a novel metric named Likeliness of Methionine PET high (LMPH) deriving from rT1/T2 was statistically significant for detecting Met-PET high T2-FLAIR hyperintense lesions (mean AUC = 0.556 ± 0.117; p = 0.01). In conclusion, this research study supported the hypothesis that rT1/T2 could be a promising imaging marker for NET identification.

Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries

Background

While there are innumerable machine learning (ML) research algorithms used for segmentation of gliomas, there is yet to be a US FDA cleared product. The aim of this study is to explore the systemic limitations of research algorithms that have prevented translation from concept to product by a review of the current research literature.

Methods

We performed a systematic literature review on 4 databases. Of 11 727 articles, 58 articles met the inclusion criteria and were used for data extraction and screening using TRIPOD.

Results

We found that while many articles were published on ML-based glioma segmentation and report high accuracy results, there were substantial limitations in the methods and results portions of the papers that result in difficulty reproducing the methods and translation into clinical practice.

Conclusions

In addition, we identified that more than a third of the articles used the same publicly available BRaTS and TCIA datasets and are responsible for the majority of patient data on which ML algorithms were trained, which leads to limited generalizability and potential for overfitting and bias.

Prediction of Glioma Stemlike Cell Infiltration in the Non-Contrast-Enhancing Area by Quantitative Measurement of Lactate on Magnetic Resonance Spectroscopy in Glioblastoma

BACKGROUND

We previously reported that glioma stemlike cells (GSCs) exist in the area of the tumor periphery showing no gadolinium enhancement on magnetic resonance imaging. In the present work, we analyzed glucose metabolism to investigate whether lactate could be predictive of tumor invasiveness and of use in detection of the tumor invasion area in glioblastoma multiforme (GBM).

METHODS

The expression of lactate dehydrogenase A (LDH-A) and pyruvate dehydrogenase (PDH) was investigated in 20 patients. In GSC lines, LDH-A and PDH expression also was examined in parallel to assessments of mitochondrial respiration. We then investigated the relationship between lactate/creatine ratios in the tumor periphery measured by magnetic resonance spectroscopy, using learning-compression-model algorithms and phenotypes of GBMs.

RESULTS

In 20 GBMs, high-invasive GBM expressed LDH-A at significantly higher expression than did low-invasive GBM, whereas low-invasive GBM showed significantly higher expression of PDH than did high-invasive GBM. The highly invasive GSC line showed higher expression of LDH-A and lower expression of PDH compared with low-invasive GSC lines. The highly invasive GSC line also showed the lowest consumption of oxygen and the lowest production of adenosine triphosphate. Lactate levels, as measured by magnetic resonance spectroscopy, showed a significant positive correlation with LDH-A transcript levels, permitting classification of the GBMs into high-invasive and low-invasive phenotypes based on a cutoff value of 0.66 in the lactate/creatine ratio.

CONCLUSIONS

In the tumor periphery area of the highly invasive GBM, aerobic glycolysis was the predominant pathway for glucose metabolism, resulting in the accumulation of lactate. The level of lactate may facilitate prediction of the tumor-infiltrating area on GBM.

A Critical Review of PET Tracers Used for Brain Tumor Imaging

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

Preoperative Texture Analysis Using 11C-Methionine Positron Emission Tomography Predicts Survival after Surgery for Glioma

BACKGROUND

Positron emission tomography with ¹¹C-methionine (MET) is well established in the diagnostic work-up of malignant brain tumors. Texture analysis is a novel technique for extracting information regarding relationships among surrounding voxels, in order to quantify their inhomogeneity. This study evaluated whether the texture analysis of MET uptake has prognostic value for patients with glioma.

METHODS

We retrospectively analyzed adults with glioma who had undergone preoperative metabolic imaging at a single center. Tumors were delineated using a threshold of 1.3-fold of the mean standardized uptake value for the contralateral cortex, and then processed to calculate the texture features in glioma.

RESULTS

The study included 42 patients (median age: 56 years). The World Health Organization classifications were grade II (7 patients), grade III (17 patients), and grade IV (18 patients). Sixteen (16.1%) all-cause deaths were recorded during the median follow-up of 18.8 months. The univariate analyses revealed that overall survival (OS) was associated with age (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.01-1.08, p = 0.0093), tumor grade (HR 3.64, 95% CI 1.63-9.63, p = 0.0010), genetic status (p < 0.0001), low gray-level run emphasis (LGRE, calculated from the gray-level run-length matrix) (HR 2.30 × 10¹¹, 95% CI 737.11-4.23 × 10¹⁹, p = 0.0096), and correlation (calculated from the gray-level co-occurrence matrix) (HR 5.17, 95% CI 1.07-20.93, p = 0.041). The multivariate analyses revealed OS was independently associated with LGRE and correlation. The survival curves were also significantly different (both log-rank p < 0.05).

CONCLUSION

Textural features obtained using preoperative MET positron emission tomography may compliment the semi-quantitative assessment for prognostication in glioma cases.

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

Simple Summary

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

Abstract

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

Non-FDG PET/CT

The major applications for molecular imaging with PET in clinical practice concern cancer imaging. Undoubtedly, 18F-FDG represents the backbone of nuclear oncology as it remains so far the most widely employed positron emitter compound. The acquired knowledge on cancer features, however, allowed the recognition in the last decades of multiple metabolic or pathogenic pathways within the cancer cells, which stimulated the development of novel radiopharmaceuticals. An endless list of PET tracers, substantially covering all hallmarks of cancer, has entered clinical routine or is being investigated in diagnostic trials. Some of them guard significant clinical applications, whereas others mostly bear a huge potential. This chapter summarizes a selected list of non-FDG PET tracers, described based on their introduction into and impact on clinical practice.

[Positron emission tomography with 11C-methionine in primary brain tumor diagnosis]

OBJECTIVE

To investigate the variations in ¹¹C-methionine uptake in the intact brain tissue and in glial brain tumors of different types.

MATERIAL AND METHODS

Forty patients (21 men, 19 women) with gliomas, Grade I-IV, underwent ¹¹C-methionine PET-CT and contrast-enhanced MRI. Standardized uptake value (SUV), tumor-to-normal (T/N) ratios and tumor volume were analyzed.

RESULTS

The high inter-subject variability was detected in the intact brain tissue (SUV in the frontal lobe (FL) varies from 0.47 to 1.73). Amino acid metabolism was more active in women than in men (FL SUV 1.32±0.22 and 1.05±0.24, respectively). T/N ratio better differentiates gliomas by the degree of anaplasia compared to SUV. Gliomas of Grade III (T/N=2.64±0.98) were significantly different (p<0.05) from those of Grade IV (T/N=3.83±0.75). The lowest level of methionine uptake was detected in diffuse astrocytomas (T/N=1.52±0.57), which was lower than with anaplastic astrocytomas (T/N=2.34±0.77, p<0.05).

CONCLUSIONS

¹¹C-methionine PET-CT was informative in the high/low degree of malignancy differentiation (T/N 1.66±0.71 for Grade I-II and 3.18±1.06 for Grade III-IV, p<0.05). The method was also useful in separating astrocytomas of Grade II and III. The considerable variation of SUV in the intact brain tissue as well as the difference in uptake between selected areas of the brain were revealed.

A Nomogram Modeling 11C-MET PET/CT and Clinical Features in Glioma Helps Predict IDH Mutation

Purpose: We developed a ¹¹C-Methionine positron emission tomography/computed tomography (¹¹C-MET PET/CT)-based nomogram model that uses easy-accessible imaging and clinical features to achieve reliable non-invasive isocitrate dehydrogenase (IDH)-mutant prediction with strong clinical translational capability.

Methods: One hundred and ten patients with pathologically proven glioma who underwent pretreatment ¹¹C-MET PET/CT were retrospectively reviewed. IDH genotype was determined by IDH1 R132H immunohistochemistry staining. Maximum, mean and peak tumor-to-normal brain tissue (TNRmax, TNRmean, TNRpeak), metabolic tumor volume (MTV), total lesion methionine uptake (TLMU), and standard deviation of SUV (SUV_SD) of the lesions on MET PET images were obtained via a dedicated workstation (Siemens. syngo.via). Univariate and multivariate logistic regression models were used to identify the predictive factors for IDH mutation. Nomogram and calibration plots were further performed.

Results: In the entire population, TNRmean, TNRmax, TNRpeak, and SUV_SD of IDH-mutant glioma patients were significantly lower than these values of IDH wildtype. Receiver operating characteristic (ROC) analysis suggested SUV_SD had the best performance for IDH-mutant discrimination (AUC = 0.731, cut-off ≤ 0.29, p < 0.001). All pairs of the ¹¹C-MET PET metrics showed linear associations by Pearson correlation coefficients between 0.228 and 0.986. Multivariate analyses demonstrated that SUV_SD (>0.29 vs. ≤ 0.29 OR: 0.053, p = 0.010), dichotomized brain midline structure involvement (no vs. yes OR: 26.52, p = 0.000) and age (≤ 45 vs. >45 years OR: 3.23, p = 0.023), were associated with a higher incidence of IDH mutation. The nomogram modeling showed good discrimination, with a C-statistics of 0.866 (95% CI: 0.796–0.937) and was well-calibrated.

Conclusions:¹¹C-Methionine PET/CT imaging features (SUV_SD and the involvement of brain midline structure) can be conveniently used to facilitate the pre-operative prediction of IDH genotype. The nomogram model based on ¹¹C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.

11C-Methionine Integrated PET/MRI-Based Texture Analysis Features May Have a Potential Ability to Distinguish Oligodendroglioma (IDH-Mutant and 1p/19q-Codeleted) From Varied Gliomas

RATIONALE AND OBJECTIVES

Different histology and gene status of gliomas results in different natural history, treatment, and prognosis in different subgroups. Low-grade gliomas (LGGs) with isocitrate dehydrogenase (IDH) mutant and 1p/19q-codeleted are kind of gliomas with the most favorable outcome, reflecting operational strategy. Less invasive method for prediction of pathological type-even gene status-is desired.

MATERIALS AND METHODS

This study investigates the potential ability of methionine-positron emission tomography (MET-PET) to determine LGGs with IDH-mutant and 1p/19q-codeleted through a retrospective review of information of 70 glioma patients. Patients underwent preoperative MET-PET, followed by operation and histopathological analysis including Immunohistochemistry and polymerase chain reaction analysis for IDH-mutant and fluorescence capillary electrophoresis analysis for 1p/19q codeletion. Texture analysis was performed for further data mining. The t-test and receiver operating characteristic curve analysis were conducted for statistical analysis.

RESULTS

In the whole cohort analysis, SUVmax, SUVmean and texture features (SD and median) of oligodendroglioma, IDH-mutant and 1p/19q-codeleted patients were lower than these values of other patients. In WHO grade II subgroup analysis, no statistical difference of conventional features was observed between groups. Texture analysis displayed higher diffEntropy, diffVariance, and entropy in oligodendroglioma, IDH-mutant and 1p/19q-codeleted patients. Receiver operating characteristic analysis suggested AUCs of some conventional features and texture features ranged from 0.722 to 0.892 that are effective for diagnosis, determining LGGs with IDH-mutant and 1p/19q-codeleted in this cohort and WHO II grade glioma subgroup analysis respectively.

CONCLUSION

¹¹C-Methionine integrated PET/MRI based texture analysis and conventional features may be a promising noninvasive predictor for differentiating the varied gliomas.

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

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

Met-PET uptake index for total tumor resection: identification of 11C-methionine uptake index as a goal for total tumor resection including infiltrating tumor cells in glioblastoma

Glioblastoma multiforme (GBM) is largely due to glioma stem cells (GSCs) that escape from total resection of gadolinium (Gd)-enhanced tumor on MRI. The aim of this study is to identify the imaging requirements for maximum resection of GBM with infiltrating GSCs. We investigated the relationship of tumor imaging volume between MRI and ¹¹C-methionine (Met)-PET and also the relationship between Met uptake index and tumor activity. In ten patients, tumor-to-contralateral normal brain tissue ratio (TNR) was calculated to evaluate metabolic activity of Met uptake areas which were divided into five subareas by the degrees of TNR. In each GBM, tumor tissue was obtained from subareas showing the positive Met uptake. Immunohistochemistry was performed to examine the tumor proliferative activity and existence of GSCs. In all patients, the volume of Met uptake area at TNR ≦ 1.4 was larger than that of the Gd-enhanced area. The Met uptake area at TNR 1.4 beyond the Gd-enhanced tumor was much wider in high invasiveness-type GBMs than in those of low invasiveness type, and survival was much shorter in the former than the latter types. Immunohistochemistry revealed the existence of GSCs in the area showing Met uptake at TNR 1.4 and no Gd enhancement. Areas at TNR > 1.4 included active tumor cells with relatively high Ki-67 labeling index. In addition, it was demonstrated that GSCs could exist beyond the border of Gd-enhanced tumor. Therefore, to obtain maximum resection of GBMs, including infiltrating GSCs, aggressive surgical excision that includes the Met-positive area at TNR 1.4 should be considered.

Simultaneous FET-PET and contrast-enhanced MRI based on hybrid PET/MR improves delineation of tumor spatial biodistribution in gliomas: a biopsy validation study

Purpose

Glioma treatment planning requires precise tumor delineation, which is typically performed with contrast-enhanced (CE) MRI. However, CE MRI fails to reflect the entire extent of glioma. O-(2-¹⁸F-fluoroethyl)-L-tyrosine (¹⁸F-FET) PET may detect tumor volumes missed by CE MRI. We investigated the clinical value of simultaneous FET-PET and CE MRI in delineating tumor extent before treatment planning. Guided stereotactic biopsy was used to validate the findings.

Methods

Conventional MRI and ¹⁸F-FET PET were performed simultaneously on a hybrid PET/MR in 33 patients with histopathologically confirmed glioma. Tumor volumes were quantified using a tumor-to-brain ratio ≥ 1.6 (V_PET) and a visual threshold (V_CE). We visually assessed abnormal areas on FLAIR images and calculated Dice’s coefficient (DSC), overlap volume (OV), discrepancy-PET, and discrepancy-CE. Additionally, several stereotactic biopsy samples were taken from “matched” or “mismatched” FET-PET and CE MRI regions.

Results

Among 31 patients (93.94%), FET-PET delineated significantly larger tumor volumes than CE MRI (77.84 ± 51.74 cm³ vs. 34.59 ± 27.07 cm³, P < 0.05). Of the 21 biopsy samples obtained from regions with increased FET uptake, all were histopathologically confirmed as glioma tissue or tumor infiltration, whereas only 13 showed enhancement on CE MRI. Among all patients, the spatial similarity between V_PET and V_CE was low (average DSC 0.56 ± 0.22), while the overlap was high (average OV 0.95 ± 0.08). The discrepancy-CE and discrepancy-PET were lower than 10% in 28 and 0 patients, respectively. Eleven patients showed V_PET partially beyond abnormal signal areas on FLAIR images.

Conclusion

The metabolically active biodistribution of gliomas delineated with FET-PET significantly exceeds tumor volume on CE MRI, and histopathology confirms these findings. Our preliminary results indicate that combining the anatomic and molecular information obtained from conventional MRI and FET-PET would reveal a more accurate glioma extent, which is critical for individualized treatment planning.

Electronic supplementary material

The online version of this article (10.1007/s00259-019-04656-2) contains supplementary material, which is available to authorized users.

11C-methionine-PET for differentiating recurrent brain tumor from radiation necrosis: radiomics approach with random forest classifier

Differentiating recurrent brain tumor from radiation necrosis is often difficult. This study aims to investigate the efficacy of 11C-methionine (MET)-PET radiomics for distinguishing recurrent brain tumor from radiation necrosis, as compared with conventional tumor-to-normal cortex (T/N) ratio evaluation. We enrolled 41 patients with metastatic brain tumor or glioma treated using radiation therapy who underwent MET-PET. The area with a standardized uptake value > 1.3 times that of the normal brain cortex was contoured. Forty-two PET features were extracted and used in a random forest classifier and the diagnostic performance was evaluated using a 10-fold cross-validation scheme. Gini index was measured to identify relevant PET parameters for classification. The reference standard was surgical histopathological analysis or more than 6 months of follow-up with MRI. Forty-four lesions were used for the analysis. Thirty-three and 11 lesions were confirmed as recurrent brain tumor and radiation necrosis, respectively. Radiomics and T/N ratio evaluation showed sensitivities of 90.1% and 60.6%, and specificities of 93.9% and 72.7% with areas under the curve of 0.98 and 0.73, respectively. Gray level co-occurrence matrix dissimilarity was the most pertinent feature for diagnosis. MET-PET radiomics yielded excellent outcome for differentiating recurrent brain tumor from radiation necrosis, which outperformed T/N ratio evaluation.

Current status of PET imaging in neuro-oncology

Over the past decades, a variety of PET tracers have been used for the evaluation of patients with brain tumors. For clinical routine, the most important clinical indications for PET imaging in patients with brain tumors are the identification of neoplastic tissue including the delineation of tumor extent for the further diagnostic and therapeutic management (ie, biopsy, resection, or radiotherapy planning), the assessment of response to a certain anticancer therapy including its (predictive) effect on the patients’ outcome and the differentiation of treatment-related changes (eg, pseudoprogression and radiation necrosis) from tumor progression at follow-up. To serve medical professionals of all disciplines involved in the diagnosis and care of patients with brain tumors, this review summarizes the value of PET imaging for the latter-mentioned 3 clinically relevant indications in patients with glioma, meningioma, and brain metastases.

Combined Amino Acid Positron Emission Tomography and Advanced Magnetic Resonance Imaging in Glioma Patients

Imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) provide valuable information about brain tumor patients. Particularly amino acid PET, advanced MRI techniques, and combinations thereof are of great interest for the non-invasive assessment of biological characteristics in patients with primary or secondary brain cancer. A methodological innovation that potentially advances research in patients with brain tumors is the increasing availability of hybrid PET/MRI systems, which enables the simultaneous acquisition of both imaging modalities. Furthermore, the advent of ultra-high field MRI scanners operating at magnetic field strengths of 7 T or more will allow further development of metabolic MR imaging at higher resolution. This review focuses on the combination of amino acid PET with MR spectroscopic imaging, perfusion- and diffusion-weighted imaging, as well as chemical exchange saturation transfer in patients with high-grade gliomas, especially glioblastomas.

Joint EANM/EANO/RANO practice guidelines/SNMMI procedure standards for imaging of gliomas using PET with radiolabelled amino acids and [18F]FDG: version 1.0

These joint practice guidelines, or procedure standards, were developed collaboratively by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the working group for Response Assessment in Neurooncology with PET (PET-RANO). Brain PET imaging is being increasingly used to supplement MRI in the clinical management of glioma. The aim of these standards/guidelines is to assist nuclear medicine practitioners in recommending, performing, interpreting and reporting the results of brain PET imaging in patients with glioma to achieve a high-quality imaging standard for PET using FDG and the radiolabelled amino acids MET, FET and FDOPA. This will help promote the appropriate use of PET imaging and contribute to evidence-based medicine that may improve the diagnostic impact of this technique in neurooncological practice. The present document replaces a former version of the guidelines published in 2006 (Vander Borght et al. Eur J Nucl Med Mol Imaging. 33:1374–80, 2006), and supplements a recent evidence-based recommendation by the PET-RANO working group and EANO on the clinical use of PET imaging in patients with glioma (Albert et al. Neuro Oncol. 18:1199–208, 2016). The information provided should be taken in the context of local conditions and regulations.

FET PET reveals considerable spatial differences in tumour burden compared to conventional MRI in newly diagnosed glioblastoma

PURPOSE

Areas of contrast enhancement (CE) on MRI are usually the target for resection or radiotherapy target volume definition in glioblastomas. However, the solid tumour mass may extend beyond areas of CE. Amino acid PET can detect parts of the tumour that show no CE. We systematically investigated tumour volumes delineated by amino acid PET and MRI in patients with newly diagnosed, untreated glioblastoma.

METHODS

Preoperatively, 50 patients with neuropathologically confirmed glioblastoma underwent O-(2-[¹⁸F]-fluoroethyl)-L-tyrosine (FET) PET, and fluid-attenuated inversion recovery (FLAIR) and contrast-enhanced MRI. Areas of CE were manually segmented. FET PET tumour volumes were segmented using a tumour-to-brain ratio of ≥1.6. The percentage overlap volumes, and Dice and Jaccard spatial similarity coefficients (DSC, JSC) were calculated. FLAIR images were evaluated visually.

RESULTS

In 43 patients (86%), the FET tumour volume was significantly larger than the CE volume (21.5 ± 14.3 mL vs. 9.4 ± 11.3 mL; P < 0.001). Forty patients (80%) showed both increased uptake of FET and CE. In these 40 patients, the spatial similarity between FET uptake and CE was low (mean DSC 0.39 ± 0.21, mean JSC 0.26 ± 0.16). Ten patients (20%) showed no CE, and one of these patients showed no FET uptake. In five patients (10%), increased FET uptake was present outside areas of FLAIR hyperintensity.

CONCLUSION

Our results show that the metabolically active tumour volume delineated by FET PET is significantly larger than tumour volume delineated by CE. Furthermore, the results strongly suggest that the information derived from both imaging modalities should be integrated into the management of patients with newly diagnosed glioblastoma.

Modified fractal analysis of methionine positron emission tomography images for predicting prognosis in newly diagnosed patients with glioma

OBJECTIVE

To assess intratumoural metabolic heterogeneity using modified fractal analysis and to determine its prognostic significance in patients with glioma.

PATIENTS AND METHODS

A total of 57 patients with newly diagnosed glioma who underwent methionine PET-computed tomography between August 2012 and January 2017 were enrolled. The requirement for informed consent was waived for this retrospective study. Tumour-to-normal tissue ratio, metabolic tumour volume, total lesion methionine uptake and modified fractal dimension (m-FD) were calculated for each tumour using methionine PET-computed tomography. Associations between these indices and tumour grade and overall survival were analysed.

RESULTS

Overall, eight patients had grade II, 20 had grade III and 29 had grade IV tumours. The tumour-to-normal tissue ratios of grade III and grade IV tumours were significantly greater than that of grade II tumours. The metabolic tumour volume and total lesion methionine uptake of grade III tumours were significantly greater than those of grade II and grade IV tumours. The m-FD of grade IV tumours was significantly greater than those of grade II and grade III tumours. A total of 47 patients were followed up, and their prognoses were evaluated. Only the m-FD was significantly associated with a poor prognosis (P<0.05). Multivariate analyses identified age (>58 years) (hazard ratio: 5.73; 95.0% confidence interval: 1.4-29.9; P=0.015) and the m-FD (>0.87) (hazard ratio: 4.80; 95.0% confidence interval: 1.12-32.9; P=0.033) as independent prognostic factors for overall survival.

CONCLUSION

Intratumoural metabolic heterogeneity is a useful imaging biomarker in patients with glioma.

Significance of Glioma Stem-Like Cells in the Tumor Periphery That Express High Levels of CD44 in Tumor Invasion, Early Progression, and Poor Prognosis in Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive malignant brain tumor and a subpopulation of glioma stem-like cells (GSCs) is likely responsible for the invariable recurrence following maximum resection and chemoradiotherapy. As most GSCs that are located in the perivascular and perinecrotic niches should be removed during tumor resection, it is very important to know where surviving GSCs are localized. Here, we investigated the existence and functions of GSCs in the tumor periphery, which is considered to constitute the invasion niche for GSCs in GBM, by analyzing expression of stem cell markers and stem cell-related molecules and measuring particular activities of cultured GSCs. In addition, the relationship between GSCs expressing particular stem cell markers and pathological features on MRI and prognosis in GBM patients was analyzed. We showed that GSCs that express high levels of CD44 are present in the tumor periphery. We also found that vascular endothelial growth factor (VEGF) is characteristically expressed at a high level in the tumor periphery. Cultured GSCs obtained from the tumor periphery were highly invasive and have enhanced migration phenotype, both of which were markedly inhibited by CD44 knockdown. Higher expression of CD44 in the tumor periphery than in the core was correlated with a highly invasive feature on MRI and was associated with early tumor progression and worse survival, whereas lower expression of CD44 in the tumor periphery corresponded to low invasion and was associated with longer survival. The low invasion type on MRI tended to show high levels of VEGF expression in the tumor periphery, thus presenting the tumor with high proliferative activity. These results imply the significance of GSCs with high levels of CD44 expression in the tumor periphery compared to the core, not only in tumor invasion but also rapid tumor progression and short survival in patients with GBM.

Correlation of Dynamic O-(2-[18F]Fluoroethyl)-L-Tyrosine Positron Emission Tomography, Conventional Magnetic Resonance Imaging, and Whole-Brain Histopathology in a Pretreated Glioblastoma: A Postmortem Study

OBJECTIVE

Amino acid positron emission tomography (PET) using O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET) provides important additional information on the extent of viable tumor tissue of glioblastoma compared with magnetic resonance imaging (MRI). Especially after radiochemotherapy, progression of contrast enhancement in MRI is equivocal and may represent either tumor progression or treatment-related changes. Here, the first case comparing postmortem whole-brain histology of a patient with pretreated glioblastoma with dynamic in vivo FET PET and MRI is presented.

METHODS

A 61-year-old patient with glioblastoma initially underwent partial tumor resection and died 11 weeks after completion of chemoradiation with concurrent temozolomide. Three days before the patient died, a follow-up FET PET and MRI scan indicated tumor progression. Autopsy was performed 48 hours after death. After formalin fixation, a 7-cm bihemispherical segment of the brain containing the entire tumor mass was cut into 3500 consecutive 20μm coronal sections. Representative sections were stained with hematoxylin and eosin stain, cresyl violet, and glial fibrillary acidic protein immunohistochemistry. An experienced neuropathologist identified areas of dense and diffuse neoplastic infiltration, astrogliosis, and necrosis. In vivo FET PET, MRI datasets, and postmortem histology were co-registered and compared by 3 experienced physicians.

RESULTS

Increased uptake of FET in the area of equivocal contrast enhancement on MRI correlated very well with dense infiltration by vital tumor cells and showed tracer kinetics typical for malignant gliomas. An area of predominantly reactive astrogliosis showed only moderate uptake of FET and tracer kinetics usually observed in benign lesions.

CONCLUSIONS

This case report impressively documents the correct imaging of a progressive glioblastoma by FET PET.

Radiomics derived from amino-acid PET and conventional MRI in patients with high-grade gliomas

Radiomics is a technique that uses high-throughput computing to extract quantitative features from tomographic medical images such as MRI and PET that usually are beyond visual perception. Importantly, the radiomics approach can be performed using neuroimages that have already been acquired during the routine follow-up of the patients allowing an additional data evaluation at low cost. In Neuro-Oncology, these features can potentially be used for differential diagnosis of newly diagnosed cerebral lesions suggestive for brain tumors or for the prediction of response to a neurooncological treatment option. Furthermore, especially in the light of the recent update of the World Health Organization classification of brain tumors, radiomics also has the potential to non-invasively assess important prognostic and predictive molecular markers such as a mutation in the isocitrate dehydrogenase gene or a 1p/19q codeletion which are not accessible by conventional visual interpretation of MRI or PET findings. This review summarizes the current status of the rapidly evolving field of radiomics with a special focus on patients with high-grade gliomas.

Multimodal Imaging of Patients With Gliomas Confirms 11C-MET PET as a Complementary Marker to MRI for Noninvasive Tumor Grading and Intraindividual Follow-Up After Therapy

The value of combined L-( methyl-[¹¹C]) methionine positron-emitting tomography (MET-PET) and magnetic resonance imaging (MRI) with regard to tumor extent, entity prediction, and therapy effects in clinical routine in patients with suspicion of a brain tumor was investigated. In n = 65 patients with histologically verified brain lesions n = 70 MET-PET and MRI (T1-weighted gadolinium-enhanced [T1w-Gd] and fluid-attenuated inversion recovery or T2-weighted [FLAIR/T2w]) examinations were performed. The computer software "visualization and analysis framework volume rendering engine (Voreen)" was used for analysis of extent and intersection of tumor compartments. Binary logistic regression models were developed to differentiate between World Health Organization (WHO) tumor types/grades. Tumor sizes as defined by thresholding based on tumor-to-background ratios were significantly different as determined by MET-PET (21.6 ± 36.8 cm³), T1w-Gd-MRI (3.9 ± 7.8 cm³), and FLAIR/T2-MRI (64.8 ± 60.4 cm³; P < .001). The MET-PET visualized tumor activity where MRI parameters were negative: PET positive tumor volume without Gd enhancement was 19.8 ± 35.0 cm³ and without changes in FLAIR/T2 10.3 ± 25.7 cm³. FLAIR/T2-MRI visualized greatest tumor extent with differences to MET-PET being greater in posttherapy (64.6 ± 62.7 cm³) than in newly diagnosed patients (20.5 ± 52.6 cm³). The binary logistic regression model differentiated between WHO tumor types (fibrillary astrocytoma II n = 10 from other gliomas n = 16) with an accuracy of 80.8% in patients at primary diagnosis. Combined PET and MRI improve the evaluation of tumor activity, extent, type/grade prediction, and therapy-induced changes in patients with glioma and serve information highly relevant for diagnosis and management.

11C-MET PET/MRI for detection of recurrent glioma

INTRODUCTION

Radiological assessment of brain tumors is widely based on the Radiology Assessment of Neuro-Oncology (RANO) criteria that consider non-specific T1 and T2 weighted images. Limitation of the RANO criteria is that they do not include metabolic imaging techniques that have been reported to be helpful to differentiate treatment related changes from true tumor progression. In the current study, we assessed if the combined use of MRI and PET with hybrid ¹¹C-MET PET/MRI can improve diagnostic accuracy and diagnostic confidence of the readers to differentiate treatment related changes from true progression in recurrent glioma.

METHODS

Fifty consecutive patients with histopathologically proven glioma were prospectively enrolled for a hybrid ¹¹C-MET PET/MRI to differentiate recurrent glioma from treatment induced changes. Sole MRI data were analyzed based on RANO. Sole PET data and in a third evaluation hybrid ¹¹C-MET-PET/MRI data were assessed for metabolic respectively metabolic and morphologic glioma recurrence. Diagnostic performance and diagnostic confidence of the reader were calculated for the different modalities, and the McNemar test and Mann-Whitney U Test were applied for statistical analysis.

RESULTS

Hybrid ¹¹C-MET PET/MRI was successfully performed in all 50 patients. Glioma recurrence was diagnosed in 35 of the 50 patients (70%). Sensitivity and specificity were calculated for MRI (86.11% and 71.43%), for ¹¹C-MET PET (96.77% and 73.68%), and for hybrid ¹¹C-MET-PET/MRI (97.14% and 93.33%). For diagnostic accuracy hybrid ¹¹C-MET-PET/MRI (96%) showed significantly higher values than MRI alone (82%), whereas no significant difference was found for 11C-MET PET (88%). Furthermore, by rating on a five-point Likert scale significantly higher scores were found for diagnostic confidence when comparing ¹¹C-MET PET/MRI (4.26 ± 0,777) to either PET alone (3.44 ± 0.705) or MRI alone (3.56 ± 0.733).

CONCLUSION

This feasibility study showed that hybrid PET/MRI might strengthen RANO classification by adding metabolic information to conventional MRI information. Future studies should evaluate the clinical utility of the combined use of ¹¹C-MET PET/MRI in larger patient cohorts.

Optimization of diagnostic performance for differentiation of recurrence from radiation necrosis in patients with metastatic brain tumors using tumor volume-corrected 11C-methionine uptake

Background

Tumor to normal tissue ratio (T/N ratio) on ¹¹C-methionine (¹¹C-MET) positron emission tomography/computed tomography (PET/CT) is affected by variable factors. We investigated whether T/N ratio cutoff values corrected according to metabolic tumor volume (MTV) could improve the diagnostic performance of ¹¹C-MET PET/CT for diagnosis of recurrence in patients with metastatic brain tumor.

Forty-eight patients with metastatic brain tumors underwent ¹¹C-MET PET/CT for differential diagnosis between recurrence and radiation necrosis after gamma knife radiosurgery (GKR). Both T/N ratio and MTV were estimated in each lesion on ¹¹C-MET PET/CT. The lesions were classified into three groups based on MTV criteria (≤ 0.5 cm³; > 0.5, ≤ 4.0 cm³; and > 4.0 cm³). The optimal cutoff values of the T/N ratio from receiver operating characteristic (ROC) curve were determined in each group (MTV-corrected) as well as total lesions (non-corrected). Finally, diagnostic performance of ¹¹C-MET PET/CT was compared with the MTV-corrected cutoff values.

Results

Among 77 lesions, 51 were diagnosed with recurrence. The mean T/N ratio was 2.25 (± 1.12) for recurrent lesions and 1.44 (± 0.22) for radiation necrosis (P < 0.001). T/N ratio of 1.61 (non-corrected) provided the best sensitivity, specificity, and diagnostic accuracy (70.6, 80.8, and 74.0%, respectively). Using the MTV criteria, optimal cutoff values of the T/N ratios in each group were 1.23 (MTV ≤ 0.5 cm³), 1.54 (0.5 cm³ < MTV ≤ 4.0 cm³), and 1.85 (MTV > 4.0 cm³). In small-sized lesions (MTV ≤ 0.5 cm³), MTV-corrected cutoff values (1.23) could maintain favorable diagnostic performance with sensitivity, specificity, and diagnostic accuracy (70.0, 80.0, and 73.3%, respectively), compared to non-corrected cutoff values.

Conclusions

MTV-corrected cutoff values of T/N ratio could maintain the diagnostic performance of ¹¹C-MET PET/CT in small sized, metastatic brain tumors. We expect our results to contribute to reproducible and standardized interpretation of ¹¹C-MET PET/CT.

Neurologic Applications of PET/MR Imaging

PET/MR imaging benefits neurologic clinical care and research by providing spatially and temporally matched anatomic MR imaging, advanced MR physiologic imaging, and metabolic PET imaging. MR imaging sequences and PET tracers can be modified to target physiology specific to a neurologic disease process, with applications in neurooncology, epilepsy, dementia, cerebrovascular disease, and psychiatric and neurologic research. Simultaneous PET/MR imaging provides efficient acquisition of multiple temporally matched datasets, and opportunities for motion correction and improved anatomic assignment of PET data. Current challenges include optimizing MR imaging-based attenuation correction and necessity for dual expertise in PET and MR imaging.

Optical-sectioning microscopy of protoporphyrin IX fluorescence in human gliomas: standardization and quantitative comparison with histology

Systemic delivery of 5-aminolevulinic acid leads to enhanced fluorescence image contrast in many tumors due to the increased accumulation of protoporphyrin IX (PpIX), a fluorescent porphyrin that is associated with tumor burden and proliferation. The value of PpIX-guided resection of malignant gliomas has been demonstrated in prospective randomized clinical studies in which a twofold greater extent of resection and improved progression-free survival have been observed. In low-grade gliomas and at the diffuse infiltrative margins of all gliomas, PpIX fluorescence is often too weak to be detected with current low-resolution surgical microscopes that are used in operating rooms. However, it has been demonstrated that high-resolution optical-sectioning microscopes are capable of detecting the sparse and punctate accumulations of PpIX that are undetectable via conventional low-power surgical fluorescence microscopes. To standardize the performance of high-resolution optical-sectioning devices for future clinical use, we have developed an imaging phantom and methods to ensure that the imaging of PpIX-expressing brain tissues can be performed reproducibly. Ex vivo imaging studies with a dual-axis confocal microscope demonstrate that these methods enable the acquisition of images from unsectioned human brain tissues that quantitatively and consistently correlate with images of histologically processed tissue sections.

An automated voxel-based method for calculating the reference value for a brain tumour metabolic index using 18F-FDG-PET and 11C-methionine PET

Objective

The tumour-to-normal ratio (T/N) is a representative index reflecting brain tumour activity by ¹⁸F-fluorodeoxyglucose (FDG) and ¹¹C-methionine (MET) PET. We proposed a new automated method of calculating the normal reference value (N-value) for use as the denomination of T/N. This method uses voxel-based analysis of FDG- and MET-PET images. We compared the results of this method with those of the standard region-of-interest (ROI) method.

Methods

Data sets were obtained from 32 patients with newly diagnosed glioma and 13 patients with recurrent brain tumour. Our methods were as follows: (1) FDG-PET and MET-PET images were co-registered. (2) The areas where the FDG uptake was higher than a set threshold were selected. (3) For the corresponding areas of MET-PET images, mode and mean voxel values were calculated as tentative MET N-values. (4) Applying the same coordinates to FDG-PET, the voxel values were averaged and used as tentative FDG N-values. (5) The threshold of FDG-PET and whether to use the mode or the mean voxel values were computationally optimized using learning data sets. (6) Applying the optimal threshold and either the mode or mean, N-values of FDG and MET were finally determined.

Results

N-values determined by our automated method showed excellent agreement with those determined by a manual ROI method (ICC(2,1) > 0.78). These values were significantly correlated with mean manual N-values (p < 0.001).

Conclusions

Our new method shows sufficiently good agreement with the standard method and can provide a more objective metabolic index.

Electronic supplementary material

The online version of this article (doi:10.1007/s12149-017-1153-8) contains supplementary material, which is available to authorized users.

Molecular imaging of 1p/19q deletion in oligodendroglial tumours with 11C-methionine positron emission tomography

OBJECTIVE

Chromosome 1p/19q deletion is an established prognostic and predictive marker in the WHO grade III oligodendroglial tumours (OT). To estimate the genetic status preoperatively, the authors investigated the correlation between the uptake of (11)C-methionine in positron emission tomography (PET) and the 1p/19q status in grades II and III OT.

METHODS

We retrospectively reviewed 144 patients with gliomas who received (11)C-methionine PET. 66 cases with grades II-III oligodendrogliomas or oligoastrocytomas underwent fluorescence in situ hybridisation to determine the 1p/19q status. The tissue uptake of (11)C-methionine was expressed as the ratio of the maximum standardised uptake value (SUVmax) in tumour areas to the mean SUV (SUVmean) in the contralateral normal brain (tumour-to-normal tissue (T/N) ratio).

RESULTS

The T/N ratio in (11)C-methionine PET was significantly higher in grade III OT than in grade II tumours. The mean T/N ratio of the grade II tumours without 1p/19q deletion was significantly higher than that of the grade II tumours with 1p/19q deletion (mean 2.67 vs 1.94, respectively; p=0.0457). In grade III tumours, the mean T/N ratio of the tumours without 1p/19q deletion was also significantly higher than that of the tumours with 1p/19q deletion (mean 4.83 vs 3.49, respectively; p=0.0261). The rate of IDH1 mutation was lower and the rate of contrast enhancement on MRIs was higher in the 1p/19q non-deleted OT than those with 1p/19q deletion, which may contribute to the high T/N ratio.

CONCLUSIONS

Among suspected OT, (11)C-methionine PET may help us preoperatively discriminate tumours with and without 1p/19q deletion.

Relapse patterns after radiochemotherapy of glioblastoma with FET PET-guided boost irradiation and simulation to optimize radiation target volume

Background

O-(2-18 F-fluoroethyl)-L-tyrosine-(FET)-PET may be helpful to improve the definition of radiation target volumes in glioblastomas compared with MRI. We analyzed the relapse patterns in FET-PET after a FET- and MRI-based integrated-boost intensity-modulated radiotherapy (IMRT) of glioblastomas to perform an optimized target volume definition.

Methods

A relapse pattern analysis was performed in 13 glioblastoma patients treated with radiochemotherapy within a prospective phase-II-study between 2008 and 2009. Radiotherapy was performed as an integrated-boost intensity-modulated radiotherapy (IB-IMRT). The prescribed dose was 72 Gy for the boost target volume, based on baseline FET-PET (FET-1) and 60 Gy for the MRI-based (MRI-1) standard target volume. The single doses were 2.4 and 2.0 Gy, respectively. Location and volume of recurrent tumors in FET-2 and MRI-2 were analyzed related to initial tumor, detected in baseline FET-1. Variable target volumes were created theoretically based on FET-1 to optimally cover recurrent tumor.

Results

The tumor volume overlap in FET and MRI was poor both at baseline (median 12 %; range 0–32) and at time of recurrence (13 %; 0–100). Recurrent tumor volume in FET-2 was localized to 39 % (12–91) in the initial tumor volume (FET-1). Over the time a shrinking (mean 12 (5–26) ml) and shifting (mean 6 (1–10 mm) of the resection cavity was seen. A simulated target volume based on active tumor in FET-1 with an additional safety margin of 7 mm around the FET-1 volume covered recurrent FET tumor volume (FET-2) significantly better than a corresponding target volume based on contrast enhancement in MRI-1 with a same safety margin of 7 mm (100 % (54–100) versus 85 % (0–100); p < 0.01). A simulated planning target volume (PTV), based on FET-1 and additional 7 mm margin plus 5 mm margin for setup-uncertainties was significantly smaller than the conventional, MR-based PTV applied in this study (median 160 (112–297) ml versus 231 (117–386) ml, p < 0.001).

Conclusions

In this small study recurrent tumor volume in FET-PET (FET-2) overlapped only to one third with the boost target volume, based on FET-1. The shrinking and shifting of the resection cavity may have an influence considering the limited overlap of initial and relapse tumor volume. A simulated target volume, based on FET-1 with 7 mm margin covered 100 % of relapse volume in median and led to a significantly reduced PTV, compared to MRI-based PTVs. This approach may achieve similar therapeutic efficacy but lower side effects offering a broader window to intensify concomitant systemic treatment focusing distant failures.

Response Assessment in Neuro-Oncology working group and European Association for Neuro-Oncology recommendations for the clinical use of PET imaging in gliomas

This guideline provides recommendations for the use of PET imaging in gliomas. The review examines established clinical benefit in glioma patients of PET using glucose ((18)F-FDG) and amino acid tracers ((11)C-MET, (18)F-FET, and (18)F-FDOPA). An increasing number of studies have been published on PET imaging in the setting of diagnosis, biopsy, and resection as well radiotherapy planning, treatment monitoring, and response assessment. Recommendations are based on evidence generated from studies which validated PET findings by histology or clinical course. This guideline emphasizes the clinical value of PET imaging with superiority of amino acid PET over glucose PET and provides a framework for the use of PET to assist in the management of patients with gliomas.

(18)F-Fluoroethyl-l-Thyrosine Positron Emission Tomography to Delineate Tumor Residuals After Glioblastoma Resection: A Comparison with Standard Postoperative Magnetic Resonance Imaging

OBJECTIVE

Complete resection of contrast-enhancing tumor is an important prognostic factor in glioblastoma therapy. The current clinical standard for control of resection is magnetic resonance imaging (MRI). (18)F-Fluoroethyl-l-thyrosine (FET) is a positron emission tomography (PET) radiopharmaceutical applicable for widespread use because of its long half-life radionuclide. We assessed the sensitivity of postoperative MRI versus FET-PET to detect residual tumor and the impact of the time interval between resection and FET-PET.

METHODS

MRI and FET-PET were performed preoperatively and postoperatively in 62 patients undergoing 63 operations. FET-PET was performed in 43 cases within 72 hours after resection and in 20 cases >72 hours after resection. Detection and measurement of volume of residual tumors were compared. Correlations between residual tumor detection and timing of PET after resection and recurrence were examined.

RESULTS

Complete resection was confirmed by both imaging modalities in 44% of cases, and residual tumor was detected consistently in 37% of cases. FET-PET detected residual tumor in 14% of cases in which MRI showed no residual tumor. MRI showed residual tumors in 5% of cases that were not identified by PET. Average PET-based residual tumor volume was higher than MRI-based volume (3.99 cm(3) vs. 1.59 cm(3)). Detection of and difference in volume of residual tumor were not correlated with timing of PET after resection or recurrence status.

CONCLUSIONS

Postoperative FET-PET revealed residual tumor with higher sensitivity than MRI and showed larger tumor volumes. In this series, performing PET >72 hours after resection did not influence the results of PET. We recommend FET-PET as a helpful adjunct in addition to MRI for postoperative assessment of residual tumor.

The influence of intraoperative resection control modalities on survival following gross total resection of glioblastoma

The purpose of the present study is to analyze the impact of intraoperative resection control modalities on overall survival (OS) and progression-free survival (PFS) following gross total resection (GTR) of glioblastoma. We analyzed data of 76 glioblastoma patients (30f, mean age 57.4 ± 11.6 years) operated at our institution between 2009 and 2012. Patients were only included if GTR was achieved as judged by early postoperative high-field MRI. Intraoperative technical resection control modalities comprised intraoperative ultrasound (ioUS, n = 48), intraoperative low-field MRI (ioMRI, n = 22), and a control group without either modality (n = 11). The primary endpoint of our study was OS, and the secondary endpoint was PFS-both analyzed in Kaplan-Meier plots and Cox proportional hazards models. Median OS in all 76 glioblastoma patients after GTR was 20.4 months (95 % confidence interval (CI) 18.5-29.0)-median OS in patients where GTR was achieved using ioUS was prolonged (21.9 months) compared to those without ioUS usage (18.8 months). A multiple Cox model adjusting for age, preop Karnofsky performance status, tumor volume, and the use of 5-aminolevulinic acid showed a beneficial effect of ioUS use, and the estimated hazard ratio was 0.63 (95 % CI 0.31-1.2, p = 0.18) in favor of ioUS, however not reaching statistical significance. A similar effect was found for PFS (hazard ratio 0.59, p = 0.072). GTR of glioblastoma performed with ioUS guidance was associated with prolonged OS and PFS. IoUS should be compared to other resection control devices in larger patient cohorts.

Hypoxia imaging in gliomas with 18F-fluoromisonidazole PET: toward clinical translation

There is significant interest in the development of improved image-guided therapy for neuro-oncology applications. Glioblastomas (GBM) in particular present a considerable challenge because of their pervasive nature, propensity for recurrence, and resistance to conventional therapies. MRI is routinely used as a guide for planning treatment strategies. However, this imaging modality is not able to provide images that clearly delineate tumor boundaries and affords only indirect information about key tumor pathophysiology. With the emergence of PET imaging with new oncology radiotracers, mapping of tumor infiltration and other important molecular events such as hypoxia is now feasible within the clinical setting. In particular, the importance of imaging hypoxia levels within the tumoral microenvironment is gathering interest, as hypoxia is known to play a central role in glioma pathogenesis and resistance to treatment. One of the hypoxia radiotracers known for its clinical utility is (18)F-fluoromisodazole ((18)F-FMISO). In this review, we highlight the typical causes of treatment failure in gliomas that may be linked to hypoxia and outline current methods for the detection of hypoxia. We also provide an overview of the growing body of studies focusing on the clinical translation of (18)F-FMISO PET imaging, strengthening the argument for the use of (18)F-FMISO hypoxia imaging to help optimize and guide treatment strategies for patients with glioblastoma.

Direct Parametric Reconstruction Using Anatomical Regularization for Simultaneous PET/MRI Data

Pharmacokinetic analysis of dynamic positron emission tomography (PET) imaging data maps the measured time activity curves to a set of model-specific pharmacokinetic parameters. Voxel-based parameter estimation via curve fitting is conventionally performed indirectly on a sequence of independently reconstructed PET images, leading to high variance and bias in the parametric images. We propose a direct parametric reconstruction algorithm with raw projection data as input that leverages high-resolution anatomical information simultaneously obtained from magnetic resonance (MR) imaging in a PET/MRI scanner for regularization. The reconstruction problem is formulated in a flexible Bayesian framework with Gaussian Markov Random field modeling of activity, parameters, or both simultaneously. MR information is incorporated through a Bowsher-like prior function. Optimization transfer using an expectation-maximization surrogate and a new Bowsher-like penalty surrogate is applied to obtain a voxel-separable algorithm that interleaves a reconstruction with a fitting step. An analytical input function model is used. The algorithm is evaluated on simulated [(18)F]FDG and clinical [(18)F]FET brain data acquired with a Biograph mMR. The results indicate that direct and simultaneously regularized parametric reconstruction increases image quality. Anatomical regularization leads to higher contrast than conventional distance-weighted regularization.

11C-MET PET/CT and advanced MRI in the evaluation of tumor recurrence in high-grade gliomas

OBJECTIVES

The purpose of this study was to evaluate the performance of l-[methyl-()11C]methionine (11C-MET) PET/CT and MRI (with the inclusion of advanced imaging techniques, namely, MR spectroscopy and MR perfusion) in the assessment of tumor recurrence in high-grade gliomas.

PATIENTS AND METHODS

Twenty-nine patients with high-grade gliomas who underwent surgical resection, external beam radiation therapy, and standard regimens of chemotherapy were subjected to MRI (conventional, MR perfusion, and MR spectroscopy) and 11C-MET PET/CT scans. A definitive diagnosis was made based on histopathology and/or long-term clinical and radiological follow-up. Several indices were obtained for lesion characterization, namely, SUVmean, SUVmax, and mean lesion-to-normal tissue on PET/CT, as well as relative cerebral blood volume and choline-to-creatine ratio on MRI.

RESULTS

Histological examination revealed viable tumor cells in 19 cases, whereas the remaining 10 were deemed to be negative based on histology (3 cases) or long-term follow-up (7 cases). All the quantitative indices mentioned previously tended to be higher in patients with tumor recurrence/residual. The sensitivity, specificity, and accuracy of 11C-MET PET/CT in identifying tumor recurrence/residual were 94.7%, 80%, and 89.6%, respectively, whereas that of MRI were 84.2%, 90%, and 86.2%, respectively.

CONCLUSIONS

Both 11C-MET PET/CT and MRI (with the inclusion of advanced MRI techniques) demonstrated a high diagnostic performance in the identification of tumor residual/recurrence in high-grade gliomas posttherapy. Although 11C-MET PET/CT seemed to be more sensitive, whereas advanced MRI seemed more specific, there was no statistically significant difference in the diagnostic performance of either modality in the present study. Further studies with a larger group of patients are warranted.

Prognostic Value of Metabolic Tumor Volume on (11)C-Methionine PET in Predicting Progression-Free Survival in High-Grade Glioma

PURPOSE

C-11 methionine (MET) PET is commonly used for diagnosing high-grade glioma (HGG). Recently, volumetric analysis has been widely applied to oncologic PET imaging. In this study, we investigated the prognostic value of metabolic tumor volume (MTV) on MET PET in HGG.

METHODS

A total of 30 patients with anaplastic astrocytoma (n = 12) and glioblastoma multiforme (n = 18) who underwent MET PET before treatment (surgery followed by chemo-radiotherapy) were retrospectively enrolled. Maximal tumor-to-normal brain ratio (TNRmax, maximum tumor activity divided by mean of normal tissue) and MTV (volume of tumor tissue that shows uptake >1.3-fold of mean uptake in normal tissue) were measured on MET PET. Adult patients were classified into two subgroups according to Radiation Therapy Oncology Group Recursive Partitioning Analysis (RTOG RPA) classification. Prognostic values of TNRmax, MTV and clinicopathologic factors were evaluated with regard to progression-free survival (PFS).

RESULTS

Median PFS of all patients was 7.9 months (range 1.0-53.8 months). In univariate analysis, MTV (cutoff 35 cm(3)) was a significant prognostic factor for PFS (P = 0.01), whereas TNRmax (cutoff 3.3) and RTOG RPA class were not (P = 0.80 and 0.61, respectively). Treatment of surgical resection exhibited a borderline significance (P = 0.06). In multivariate analysis, MTV was the only independent prognostic factor for PFS (P = 0.03).

CONCLUSION

MTV on MET PET is a significant and independent prognostic factor for PFS in HGG patients, whereas TNRmax is not. Thus, performing volumetric analysis of MET PET is recommended in HGG for better prognostication.