Accuracy of 11C-choline positron emission tomography in differentiating glioma recurrence from radiation necrosis: A systematic review and meta-analysis

Umbrella review and network meta-analysis of diagnostic imaging test accuracy studies in Differentiating between brain tumor progression versus pseudoprogression and radionecrosis

PURPOSE

In this study we gathered and analyzed the available evidence regarding 17 different imaging modalities and performed network meta-analysis to find the most effective modality for the differentiation between brain tumor recurrence and post-treatment radiation effects.

METHODS

We conducted a comprehensive systematic search on PubMed and Embase. The quality of eligible studies was assessed using the Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) instrument. For each meta-analysis, we recalculated the effect size, sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio from the individual study data provided in the original meta-analysis using a random-effects model. Imaging technique comparisons were then assessed using NMA. Ranking was assessed using the multidimensional scaling approach and by visually assessing surface under the cumulative ranking curves.

RESULTS

We identified 32 eligible studies. High confidence in the results was found in only one of them, with a substantial heterogeneity and small study effect in 21% and 9% of included meta-analysis respectively. Comparisons between MRS Cho/NAA, Cho/Cr, DWI, and DSC were most studied. Our analysis showed MRS (Cho/NAA) and 18F-DOPA PET displayed the highest sensitivity and negative likelihood ratios. 18-FET PET was ranked highest among the 17 studied techniques with statistical significance. APT MRI was the only non-nuclear imaging modality to rank higher than DSC, with statistical insignificance, however.

CONCLUSION

The evidence regarding which imaging modality is best for the differentiation between radiation necrosis and post-treatment radiation effects is still inconclusive. Using NMA, our analysis ranked FET PET to be the best for such a task based on the available evidence. APT MRI showed promising results as a non-nuclear alternative.

Advances in the application of neuroinflammatory molecular imaging in brain malignancies

The prevalence of brain cancer has been increasing in recent decades, posing significant healthcare challenges. The introduction of immunotherapies has brought forth notable diagnostic imaging challenges for brain tumors. The tumor microenvironment undergoes substantial changes in induced immunosuppression and immune responses following the development of primary brain tumor and brain metastasis, affecting the progression and metastasis of brain tumors. Consequently, effective and accurate neuroimaging techniques are necessary for clinical practice and monitoring. However, patients with brain tumors might experience radiation-induced necrosis or other neuroinflammation. Currently, positron emission tomography and various magnetic resonance imaging techniques play a crucial role in diagnosing and evaluating brain tumors. Nevertheless, differentiating between brain tumors and necrotic lesions or inflamed tissues remains a significant challenge in the clinical diagnosis of the advancements in immunotherapeutics and precision oncology have underscored the importance of clinically applicable imaging measures for diagnosing and monitoring neuroinflammation. This review summarizes recent advances in neuroimaging methods aimed at enhancing the specificity of brain tumor diagnosis and evaluating inflamed lesions.

Differentiating radiation necrosis from tumor recurrence: a systematic review and diagnostic meta-analysis comparing imaging modalities

PURPSOSE

Cerebral radiation necrosis (RN) is often a delayed phenomenon occurring several months to years after the completion of radiation treatment. Differentiating RN from tumor recurrence presents a diagnostic challenge on standard MRI. To date, no evidence-based guidelines exist regarding imaging modalities best suited for this purpose. We aim to review the current literature and perform a diagnostic meta-analysis comparing various imaging modalities that have been studied to differentiate tumor recurrence and RN.

METHODS

A systematic search adherent to PRISMA guidelines was performed using Scopus, PubMed/MEDLINE, and Embase. Pooled sensitivities and specificities were determined using a random-effects or fixed-effects proportional meta-analysis based on heterogeneity. Using diagnostic odds ratios, a diagnostic frequentist random-effects network meta-analysis was performed, and studies were ranked using P-score hierarchical ranking.

RESULTS

The analysis included 127 studies with a total of 220 imaging datasets, including the following imaging modalities: MRI (n = 10), MR Spectroscopy (MRS) (n = 28), dynamic contrast-enhanced MRI (n = 7), dynamic susceptibility contrast MRI (n = 36), MR arterial spin labeling (n = 5), diffusion-weighted imaging (n = 13), diffusion tensor imaging (DTI) (n = 2), PET (n = 89), and single photon emission computed tomography (SPECT) (n = 30). MRS had the highest pooled sensitivity (90.7%). DTI had the highest pooled specificity (90.5%). Our hierarchical ranking ranked SPECT and MRS as most preferable, and MRI was ranked as least preferable.

CONCLUSION

These findings suggest SPECT and MRS carry greater utility than standard MRI in distinguishing RN from tumor recurrence.

The Role of PET Imaging in the Differential Diagnosis between Radiation Necrosis and Recurrent Disease in Irradiated Adult-Type Diffuse Gliomas: A Systematic Review

Adult-type diffuse gliomas are treated with a multimodality treatment approach that includes radiotherapy both in the primary setting, and in the case of progressive or recurrent disease. Radiation necrosis represents a major complication of radiotherapy. Recurrent disease and treatment-related changes are often indistinguishable using conventional imaging methods. The present systematic review aims at assessing the diagnostic role of PET imaging using different radiopharmaceuticals in differentiating radiation necrosis and disease relapse in irradiated adult-type diffuse gliomas. We conducted a comprehensive literature search using the PubMed/MEDLINE and EMBASE databases for original research studies of interest. In total, 436 articles were assessed for eligibility. Ten original papers, published between 2014 and 2022, were selected. Four articles focused on [¹⁸F]FDG, seven on amino acid tracers ([¹⁸F]FET n = 3 and [¹¹C]MET n = 4), one on [¹¹C]CHO, and one on [⁶⁸Ga]Ga-PSMA. Visual assessment, semi-quantitative methods, and radiomics were applied for image analysis. Furthermore, 2/10 papers were comparative studies investigating different radiopharmaceuticals. The present review, the first one on the topic in light of the new 2021 CNS WHO classification, highlighted the usefulness of PET imaging in distinguishing radiation necrosis and tumour recurrence, but revealed high heterogeneity among studies.

Early Recurrence Detection of Glioma Using 18 F-Fluorocholine PET/CT : GliReDe Pilot Study

OBJECTIVE

The aim of this study was to analyze the usefulness of 18 F-fluorocholine PET/CT in the early diagnosis of tumor recurrence, increasing the diagnosis confidence of MRI.

METHODS

Patients with a previous gross total resection of glioma and the first suspicious or doubtful for recurrence MRI were prospectively included and subjected to 18 F-fluorocholine PET/CT. An independent and combined assessment of 18 F-fluorocholine PET/CT and multimodal MRI was performed classifying the studies as positive or negative for tumor recurrence. Final diagnosis (recurrence or not) was obtained by histological confirmation or clinical and imaging follow-up. The relation of SUV max and tumor-to-background ratio with progression, the diagnostic performance of imaging techniques, and their concordance (κ Cohen) were analyzed.

RESULTS

Twenty-four studies on 21 patients were assessed. Recurrence was diagnosed in 20 cases. PET/CT was positive in 23 cases (3 false positive), whereas MRI was positive in 15 cases (1 false positive). MRI was false negative in 6 cases. There was no false negative on 18 F-fluorocholine PET/CT. Accuracy of PET/CT versus MRI was 87.5% and 70.8%, respectively. The combined evaluation of both techniques did not show any advantage with respect to PET/CT results alone. The concordance between both imaging techniques was low (κ = 0.135; P = 0.375). SUV max and tumor-to-background ratio were related to recurrence (areas under the curve of 0.844 [ P = 0.033] and 0.869 [ P = 0.022], respectively).

CONCLUSIONS

18 F-fluorocholine PET/CT was helpful for increasing the diagnostic confidence in the cases of MRI doubtful for recurrence in order to avoid a delayed diagnosis.

Imaging Findings of 18F-Choline and 18F-DOPA PET/MRI in a Case of Glioblastoma Multiforme Pseudoprogression: Correlation with Clinical Outcome

We describe the case of 74-year-old-male, previously treated with fronto-parietal craniotomy due to primary glioblastoma multiforme (GBM), followed by concurrent radiation therapy (RT) and temozolomide (TMZ) chemotherapy. Magnetic resonance imaging (MRI) of the brain, at 1 month after completing RT + TMZ, depicted partial response. Three months later, the patient was submitted to a further brain MRI, that resulted doubtful for therapy induced changes (i.e., pseudoprogression). The patient, who had been previously treated with prostatectomy for prostate cancer (PC), underwent a positron emission tomography/computed tomography (PET/CT) scan with 18F-choline for PC biochemical recurrence. 18F-choline whole body PET/CT resulted negative for PC relapse, while segmental brain PET, co-registered with MRI, demonstrated increased tracer uptake corresponding to tumor boundaries. In order to solve differential diagnosis between pseudoprogression and GBM recurrence, brain PET/CT with 18F-L-dihydroxy-phenil-alanine (18F-DOPA) was subsequently performed: fused axial PET/MRI images showed increased 18F-DOPA incorporation in the peri-tumoral edema, but not in tumor boundaries, consistent with the suspicion of GBM pseudoprogression, as then confirmed by clinical and radiological follow-up.

Tracers progress for positron emission tomography imaging of glial-related disease

Glial cells play an essential part in the neuron system. They can not only serve as structural blocks in the human brain but also participate in many biological processes. Extensive studies have shown that astrocytes and microglia play an important role in neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, as well as glioma, epilepsy, ischemic stroke, and infections. Positron emission tomography is a functional imaging technique providing molecular-level information before anatomic changes are visible and has been widely used in many above-mentioned diseases. In this review, we focus on the positron emission tomography tracers used in pathologies related to glial cells, such as glioma, Alzheimer's disease, and neuroinflammation.

Diagnosis of Glioblastoma by Immuno-Positron Emission Tomography

Simple Summary

Neuroimaging has transformed the way brain tumors are diagnosed and treated. Although different non-invasive modalities provide very helpful information, in some situations, they present a limited value. By merging the specificity of antibodies with the resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET), “Immuno-PET” allows us to conduct the non-invasive diagnosis and monitoring of patients over time using antibody-based probes as an in vivo, integrated, quantifiable, 3D, full-body “immunohistochemistry”, like a “virtual biopsy”. This review provides and focuses on immuno-PET applications and future perspectives of this promising imaging approach for glioblastoma.

Abstract

Neuroimaging has transformed neuro-oncology and the way that glioblastoma is diagnosed and treated. Magnetic Resonance Imaging (MRI) is the most widely used non-invasive technique in the primary diagnosis of glioblastoma. Although MRI provides very powerful anatomical information, it has proven to be of limited value for diagnosing glioblastomas in some situations. The final diagnosis requires a brain biopsy that may not depict the high intratumoral heterogeneity present in this tumor type. The revolution in “cancer-omics” is transforming the molecular classification of gliomas. However, many of the clinically relevant alterations revealed by these studies have not yet been integrated into the clinical management of patients, in part due to the lack of non-invasive biomarker-based imaging tools. An innovative option for biomarker identification in vivo is termed “immunotargeted imaging”. By merging the high target specificity of antibodies with the high spatial resolution, sensitivity, and quantitative capabilities of positron emission tomography (PET), “Immuno-PET” allows us to conduct the non-invasive diagnosis and monitoring of patients over time using antibody-based probes as an in vivo, integrated, quantifiable, 3D, full-body “immunohistochemistry” in patients. This review provides the state of the art of immuno-PET applications and future perspectives on this imaging approach for glioblastoma.

Neuroinflammation and immunoregulation in glioblastoma and brain metastases: Recent developments in imaging approaches

Brain tumors and brain metastases induce changes in brain tissue remodeling that lead to immunosuppression and trigger an inflammatory response within the tumor microenvironment. These immune and inflammatory changes can influence invasion and metastasis. Other neuroinflammatory and necrotic lesions may occur in patients with brain cancer or brain metastases as sequelae from treatment with radiotherapy. Glioblastoma (GBM) is the most aggressive primary malignant brain cancer in adults. Imaging methods such as positron emission tomography (PET) and different magnetic resonance imaging (MRI) techniques are highly valuable for the diagnosis and therapeutic evaluation of GBM and other malignant brain tumors. However, differentiating between tumor tissue and inflamed brain tissue with imaging protocols remains a challenge. Here, we review recent advances in imaging methods that have helped to improve the specificity of primary tumor diagnosis versus evaluation of inflamed and necrotic brain lesions. We also comment on advances in differentiating metastasis from neuroinflammation processes. Recent advances include the radiosynthesis of ¹⁸ F-FIMP, an L-type amino acid transporter 1 (LAT1)-specific PET probe that allows clearer differentiation between tumor tissue and inflammation compared to previous probes, and the combination of different advanced imaging protocols with the inclusion of radiomics and machine learning algorithms.

Multimodal imaging in the differential diagnosis of glioma recurrence from treatment-related effects: A protocol for systematic review and network meta-analysis

BACKGROUND

Glioma is the most common malignant primary brain tumor and it will always recur. To date, various multimodal imaging including magnetic resonance imaging (MRI) and positron emission tomography computed tomography (PET/CT) was used to differentiate the diagnosis of true tumor recurrent (TuR) and treatment-related effects (TrE) in glioma patient but with no overall conclusion. In this study, SROC curve and Bayesian network meta-analysis will be used to conduct a comprehensive analysis of the results of different clinical reports, and assess the efficacy of multimodal imaging in difference TuR and TrE.

METHODS

To find more comprehensive information about the application of multimodal imaging in glioma patients, we searched the EMBASE, Pubmed, and Cochrane Central Register of Controlled Trials for relevant clinical trials. We also reviewed their reference lists to avoid omissions. QUADAS-2, RevMan software, Stata, and R software will be used.

RESULTS

This study will provide reliable evidence for the efficacy of multimodal imaging in the differential diagnosis of TuR and TrE in glioma patients.

CONCLUSION

We will evaluate the effectiveness of different and rank each imaging method in glioma patients to provide a decision-making reference on which method to choose for clinicians. Protocol registration number: CRD42020217861.

PET/CT variants and pitfalls in prostate cancer: What you might see on PET and should never forget

2-deoxy-2-[¹⁸F]fluorodeoxyglucose (FDG) positron emission tomography (PET) gained an impressive role in the diagnostic management of many oncological diseases, even though its use in imaging prostate cancer (PC) is limited to selected cases, mostly advanced stage of PC and selection for prostate specific antigen membrane (PSMA) radioligand therapy (RLT). In the past years, several PET tracers have been developed for both staging and restaging PC. The three most employed PET molecules in daily practice are [¹¹C] or [¹⁸F]F-Choline, [¹⁸F]F-Fluciclovine (Anti-1- amino-3-[18F]Fluorocyclobutane-1-Carboxylic Acid, also known as (Anti-[¹⁸F]FACBC), [⁶⁸Ga]Ga-PSMA and recently FDA approved the first Fluorinated PSMA-based named [¹⁸F]F-DCFPyl. Each one has its own physiological and peculiarity which are worth exploring. Moreover, an increasing number of case reports and studies have reported tracers' variants, pitfalls, or even non-prostatic diseases (benign and malignant) incidentally detected. In prostate oncology, PET can be performed with several indications in different stages of disease, as highlighted in the EAU Guidelines on PC. A correct scan interpretation depends on the knowledge of both the physiological distribution of the tracers and the uptake of possible variants and pitfalls. The aim of this critical review is to provide a comprehensive knowledge of physiological distribution of these three tracers, as well as an updated overview of variants and pitfalls.

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.

Quantitative Features From CHO PET Distinguish the WHO Grades of Primary Diffuse Glioma

PURPOSE

The aim of this study was to investigate the quantitative 18F-fluoroethylcholine (CHO) PET characteristics for differentiating lower-grade glioma (LGG) from glioblastoma (GBM).

PATIENTS AND METHODS

Thirty-nine patients who underwent CHO PET with histopathologically confirmed primary diffuse glioma were prospectively enrolled. The 3-dimensional region of interest was semiautomatically defined based on the SUV threshold, and a total of 74 quantitative features, including 13 shape features, 31 SUV-based features, and 30 normalized SUV-based features, were calculated. Wilcoxon rank sum test, receiver operating characteristic curve, and correlation coefficient analyses were applied to select independent representative features, and patient prognosis was stratified by the World Health Organization (WHO) grade and CHO features.

RESULTS

A total of 89.2% of the quantitative features were significantly different between LGG and GBM, and the SUV-based features displayed higher area under the receiver operating characteristic curve (AUC) values than the other feature groups. Among the 5 traditional features, the SUVmax and the total lesion CHO uptake were the most distinguishing, with AUCs of 0.880 and 0.860 (0.938 and 0.927 after reclassification of 2 outliers), respectively, both of which could also stratify patient prognosis better than WHO grade. Five alternative features, including 2 shape features and 3 SUV-based features, were considered representative, with AUCs ranging from 0.754 to 0.854.

CONCLUSIONS

Quantitative features from CHO PET are reliable in determining the WHO grade of primary diffuse gliomas. Our findings suggest that GBM has a larger volume, a more spherical shape, higher choline activity in most interval segments, and a more symmetrical distribution than LGG.

Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation

BACKGROUND

The radiological differential diagnosis between tumor recurrence and radiation-induced necrosis (ie, pseudoprogression) is of paramount importance in the management of glioma patients.

OBJECTIVE

This research aims to develop a deep learning methodology for automated differentiation of tumor recurrence from radiation necrosis based on routine magnetic resonance imaging (MRI) scans.

METHODS

In this retrospective study, 146 patients who underwent radiation therapy after glioma resection and presented with suspected recurrent lesions at the follow-up MRI examination were selected for analysis. Routine MRI scans were acquired from each patient, including T1, T2, and gadolinium-contrast-enhanced T1 sequences. Of those cases, 96 (65.8%) were confirmed as glioma recurrence on postsurgical pathological examination, while 50 (34.2%) were diagnosed as necrosis. A light-weighted deep neural network (DNN) (ie, efficient radionecrosis neural network [ERN-Net]) was proposed to learn radiological features of gliomas and necrosis from MRI scans. Sensitivity, specificity, accuracy, and area under the curve (AUC) were used to evaluate performance of the model in both image-wise and subject-wise classifications. Preoperative diagnostic performance of the model was also compared to that of the state-of-the-art DNN models and five experienced neurosurgeons.

RESULTS

DNN models based on multimodal MRI outperformed single-modal models. ERN-Net achieved the highest AUC in both image-wise (0.915) and subject-wise (0.958) classification tasks. The evaluated DNN models achieved an average sensitivity of 0.947 (SD 0.033), specificity of 0.817 (SD 0.075), and accuracy of 0.903 (SD 0.026), which were significantly better than the tested neurosurgeons (P=.02 in sensitivity and P<.001 in specificity and accuracy).

CONCLUSIONS

Deep learning offers a useful computational tool for the differential diagnosis between recurrent gliomas and necrosis. The proposed ERN-Net model, a simple and effective DNN model, achieved excellent performance on routine MRI scans and showed a high clinical applicability.

Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature

Tumor resection followed by chemoradiation remains the current criterion standard treatment for high-grade gliomas. Regardless of aggressive treatment, tumor recurrence and radiation necrosis are 2 different outcomes. Differentiation of tumor recurrence from radiation necrosis remains a critical problem in these patients because of considerable overlap in clinical and imaging presentations. Contrast-enhanced MR imaging is the universal imaging technique for diagnosis, treatment evaluation, and detection of recurrence of high-grade gliomas. PWI and PET with novel radiotracers have an evolving role for monitoring treatment response in high-grade gliomas. In the literature, there is no clear consensus on the superiority of either technique or their complementary information. This review aims to elucidate the diagnostic performance of individual and combined use of functional (PWI) and metabolic (PET) imaging modalities to distinguish recurrence from posttreatment changes in gliomas.

Individualized discrimination of tumor recurrence from radiation necrosis in glioma patients using an integrated radiomics-based model

PURPOSE

To develop and validate an integrated model for discriminating tumor recurrence from radiation necrosis in glioma patients.

METHODS

Data from 160 pathologically confirmed glioma patients were analyzed. The diagnostic model was developed in a primary cohort (n = 112). Textural features were extracted from postoperative ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET), ¹¹C-methionine (¹¹C-MET) PET, and magnetic resonance images. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a model for predicting tumor recurrence. The radiomics signature, quantitative PET parameters, and clinical risk factors were incorporated in the model. The clinical value of the model was then assessed in an independent validation cohort using the remaining 48 glioma patients.

RESULTS

The integrated model consisting of 15 selected features was significantly associated with postoperative tumor recurrence (p < 0.001 for both primary and validation cohorts). Predictors contained in the individualized diagnosis model included the radiomics signature, the mean of tumor-background ratio (TBR) of ¹⁸F-FDG, maximum of TBR of ¹¹C-MET PET, and patient age. The integrated model demonstrated good discrimination, with an area under the curve (AUC) of 0.988, with a 95% confidence interval (CI) of 0.975-1.000. Application in the validation cohort showed good differentiation (AUC of 0.914 and 95% CI of 0.881-0.945). Decision curve analysis showed that the integrated diagnosis model was clinically useful.

CONCLUSIONS

Our developed model could be used to assist the postoperative individualized diagnosis of tumor recurrence in patients with gliomas.

Diagnostic Performance and Prognostic Value of PET/CT with Different Tracers for Brain Tumors: A Systematic Review of Published Meta-Analyses

Background: Several meta-analyses reporting data on the diagnostic performance or prognostic value of positron emission tomography (PET) with different tracers in detecting brain tumors have been published so far. This review article was written to summarize the evidence-based data in these settings. Methods: We have performed a comprehensive literature search of meta-analyses published in the Cochrane library and PubMed/Medline databases (from inception through July 2019) about the diagnostic performance or prognostic value of PET with different tracers in patients with brain tumors. Results: We have summarized the results of 24 retrieved meta-analyses on the use of PET or PET/computed tomography (CT) with different tracers in brain tumors. The tracers included were: fluorine-18 fluorodeoxyglucose (¹⁸F-FDG), carbon-11 methionine (¹¹C-methionine), fluorine-18 fluoroethyltyrosine (¹⁸F-FET), fluorine-18 dihydroxyphenylalanine (¹⁸F-FDOPA), fluorine-18 fluorothymidine (¹⁸F-FLT), and carbon-11 choline (¹¹C-choline). Evidence-based data demonstrated good diagnostic performance of PET with different tracers in detecting brain tumors, in particular, radiolabelled amino acid tracers showed the highest diagnostic performance values. All the PET tracers evaluated had significant prognostic value in patients with glioma. Conclusions: Evidence-based data showed a good diagnostic performance for some PET tracers in specific indications and significant prognostic value in brain tumors.

An update on PET-based molecular imaging in neuro-oncology: challenges and implementation for a precision medicine approach in cancer care

PET imaging using novel radiotracers show promises for tumor grading and molecular characterization through visualizing molecular and functional properties of the tumors. Application of PET tracers in brain neoplasm depends on both type of the neoplasm and the research or clinical significance required to be addressed. In clinical neuro-oncology, 18F-FDG is used mainly to differentiate tumor recurrence from radiation-induced necrosis, and novel PET agents show attractive imaging properties. Novel PET tracers can offer biologic information not visible via contrast-enhanced MRI or 18F-FDG PET. This review aims to provide an update on the complementary role of PET imaging in neuro-oncology both in research and clinical settings along with presenting interesting cases in this context.