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The Added Value of Diagnostic and Theranostic PET Imaging for the Treatment of CNS Tumors.

ABSTRACT: This review highlights the added value of PET imaging in Central Nervous System (CNS) tumors, which is a tool that has rapidly evolved from a merely diagnostic setting to multimodal molecular diagnostics and the guidance of targeted therapy. PET is the method of choice for studying target expression and target binding behind the assumedly intact blood-brain barrier. Today, a variety of diagnostic PET tracers can be used for the primary staging of CNS tumors and to determine the effect of therapy. Additionally, theranostic PET tracers are increasingly used in the context of pharmaceutical and radiopharmaceutical drug development and application. In this approach, a single targeted drug is used for PET diagnosis, upon the coupling of a PET radionuclide, as well as for targeted (nuclide) therapy. Theranostic PET tracers have the potential to serve as a non-invasive whole body navigator in the selection of the most effective drug candidates and their most optimal dose and administration route, together with the potential to serve as a predictive biomarker in the selection of patients who are most likely to benefit from treatment. PET imaging supports the transition from trial and error medicine to predictive, preventive, and personalized medicine, hopefully leading to improved quality of life for patients and more cost-effective care.

SUBMITTER: Pruis IJ

PROVIDER: S-EPMC7037158 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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The Added Value of Diagnostic and Theranostic PET Imaging for the Treatment of CNS Tumors.

Pruis Ilanah J IJ van Dongen Guus A M S GAMS Veldhuijzen van Zanten Sophie E M SEM

International journal of molecular sciences 20200204 3

This review highlights the added value of PET imaging in Central Nervous System (CNS) tumors, which is a tool that has rapidly evolved from a merely diagnostic setting to multimodal molecular diagnostics and the guidance of targeted therapy. PET is the method of choice for studying target expression and target binding behind the assumedly intact blood-brain barrier. Today, a variety of diagnostic PET tracers can be used for the primary staging of CNS tumors and to determine the effect of therapy ...[more]

PMID: 32033160

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Project description:BACKGROUND AND PURPOSE:Perfusion and spectroscopic MR imaging provide noninvasive physiologic and metabolic characterization of tissues, which can help in differentiating brain tumors. We investigated the diagnostic role of perfusion and spectroscopic MR imaging using individual and combined classifiers of these modalities and assessed the added performance value that spectroscopy can provide to perfusion using optimal combined classifiers that have the highest differential diagnostic performance to discriminate lymphomas, glioblastomas, and metastases. MATERIALS AND METHODS:From January 2013 to January 2016, fifty-five consecutive patients with histopathologically proved lymphomas, glioblastomas, and metastases were included after undergoing MR imaging. The perfusion parameters (maximum relative CBV, maximum percentage of signal intensity recovery) and spectroscopic concentration ratios (lactate/Cr, Cho/NAA, Cho/Cr, and lipids/Cr) were analyzed individually and in optimal combinations. Differences among tumor groups, differential diagnostic performance, and differences in discriminatory performance of models with quantification of the added performance value of spectroscopy to perfusion were tested using 1-way ANOVA models, receiver operating characteristic analysis, and comparisons between receiver operating characteristic analysis curves using a bivariate ?2, respectively. RESULTS:The highest differential diagnostic performance was obtained with the following combined classifiers: maximum percentage of signal intensity recovery-Cho/NAA to discriminate lymphomas from glioblastomas and metastases, significantly increasing the sensitivity from 82.1% to 95.7%; relative CBV-Cho/NAA to discriminate glioblastomas from lymphomas and metastases, significantly increasing the specificity from 92.7% to 100%; and maximum percentage of signal intensity recovery-lactate/Cr and maximum percentage of signal intensity recovery-Cho/Cr to discriminate metastases from lymphomas and glioblastomas, significantly increasing the specificity from 83.3% to 97.0% and 100%, respectively. CONCLUSIONS:Spectroscopy yielded an added performance value to perfusion using optimal combined classifiers of these modalities, significantly increasing the differential diagnostic performances for these common brain tumors.

Project description:PurposeTo evaluate the performance of combined PET and multiparametric MRI (mpMRI) radiomics for the group-wise prediction of postsurgical Gleason scores (psGSs) in primary prostate cancer (PCa) patients.MethodsPatients with PCa, who underwent [68 Ga]Ga-PSMA-11 PET/MRI followed by radical prostatectomy, were included in this retrospective analysis (n = 101). Patients were grouped by psGS in three categories: ISUP grades 1-3, ISUP grade 4, and ISUP grade 5. mpMRI images included T1-weighted, T2-weighted, and apparent diffusion coefficient (ADC) map. Whole-prostate segmentations were performed on each modality, and image biomarker standardization initiative (IBSI)-compliant radiomic features were extracted. Nine support vector machine (SVM) models were trained: four single-modality radiomic models (PET, T1w, T2w, ADC); three PET + MRI double-modality models (PET + T1w, PET + T2w, PET + ADC), and two baseline models (one with patient data, one image-based) for comparison. A sixfold stratified cross-validation was performed, and balanced accuracies (bAcc) of the predictions of the best-performing models were reported and compared through Student's t-tests. The predictions of the best-performing model were compared against biopsy GS (bGS).ResultsAll radiomic models outperformed the baseline models. The best-performing (mean ± stdv [%]) single-modality model was the ADC model (76 ± 6%), although not significantly better (p > 0.05) than other single-modality models (T1w: 72 ± 3%, T2w: 73 ± 2%; PET: 75 ± 5%). The overall best-performing model combined PET + ADC radiomics (82 ± 5%). It significantly outperformed most other double-modality (PET + T1w: 74 ± 5%, p = 0.026; PET + T2w: 71 ± 4%, p = 0.003) and single-modality models (PET: p = 0.042; T1w: p = 0.002; T2w: p = 0.003), except the ADC-only model (p = 0.138). In this initial cohort, the PET + ADC model outperformed bGS overall (82.5% vs 72.4%) in the prediction of psGS.ConclusionAll single- and double-modality models outperformed the baseline models, showing their potential in the prediction of GS, even with an unbalanced cohort. The best-performing model included PET + ADC radiomics, suggesting a complementary value of PSMA-PET and ADC radiomics.

Project description:BackgroundProstate specific membrane antigen (PSMA) PET imaging has recently gained attention in glioblastoma (GBM) patients as a potential theranostic target for PSMA radioligand therapy. However, PSMA PET has not yet been established in a murine GBM model. Our goal was to investigate the potential of PSMA PET imaging in the syngeneic GL261 GBM model and to give an outlook regarding the potential of PMSA radioligand therapy in this model.MethodsWe performed an 18F-PSMA-1007 PET study in the orthotopic GL261 model (n=14 GBM, n=7 sham-operated mice) with imaging at day 4, 8, 11, 15, 18 and 22 post implantation. Time-activity-curves (TAC) were extracted from dynamic PET scans (0-120 min p. i.) in a subset of mice (n=4 GBM, n=3 sham-operated mice) to identify the optimal time frame for image analysis, and standardized-uptake-values (SUV) as well as tumor-to-background ratios (TBR) using contralateral normal brain as background were calculated in all mice. Additionally, computed tomography (CT), ex vivo and in vitro 18F-PSMA-1007 autoradiographies (ARG) were performed.ResultsTAC analysis of GBM mice revealed a plateau of TBR values after 40 min p. i. Therefore, a 30 min time frame between 40-70 min p. i. was chosen for PET quantification. At day 15 and later, GBM mice showed a discernible PSMA PET signal on the inoculation site, with highest TBRmean in GBM mice at day 18 (7.3 ± 1.3 vs. 1.6 ± 0.3 in shams; p=0.024). Ex vivo ARG confirmed high tracer signal in GBM compared to healthy background (TBRmean 26.9 ± 10.5 vs. 1.6 ± 0.7 in shams at day 18/22 post implantation; p=0.002). However, absolute uptake values in the GL261 tumor remained low (e.g., SUVmean 0.21 ± 0.04 g/ml at day 18) resulting in low ratios compared to dose-relevant organs (e.g., mean tumor-to-kidney ratio 1.5E-2 ± 0.5E-2).ConclusionsAlthough 18F-PSMA-1007 PET imaging of GL261 tumor-bearing mice is feasible and resulted in high TBRs, absolute tumoral uptake values remained low and hint to limited applicability of the GL261 model for PSMA-directed therapy studies. Further investigations are warranted to identify suitable models for preclinical evaluation of PSMA-targeted theranostic approaches in GBM.

Project description:ObjectiveWe performed a systematic review and network meta-analysis (NMA) to compare the diagnostic value of seven different imaging modalities for the detection of neuroblastic tumors in diverse clinical settings.MethodsPubMed, Embase, Medline, and the Cochrane Library were searched to identify eligible studies from inception to Sep 29, 2020. Quality assessment of included studies was appraised with Quality Assessment of Diagnostic Accuracy Studies. Firstly, direct pairwise meta-analysis was conducted to calculate the pooled estimates of odds ratio (OR) and 95% confidence interval (CI) of the sensitivity, specificity, NPV, PPV, and DR. Next, NMA using Bayesian methods was performed. The superiority index was assessed to quantify the rank probability of a diagnostic test. The studies performed SPECT/CT or SPECT were analyzed separately from the ones only performed planar imaging.ResultsA total of 1135 patients from 32 studies, including 7 different imaging modalities, were eligible for this NMA. In the pairwise meta-analysis, 18F-FDOPA PET/CT had a relatively high value of all the outcomes (sensitivity: 10.195 [5.332-19.493]; specificity: 17.906 [5.950-53.884]; NPV: 16.819 [7.033-40.218]; PPV: 11.154 [4.216-29.512]; and DR 5.616 [3.609-8.739]). In the NMA, 18F-FDOPA PET/CT exhibited relatively high sensitivity in all subgroups (all data: 0.94 [0.87-0.98]; primary tumor: 0.89 [0.53-1]; bone/bone marrow metastases: 0.96 [0.83-1]; and primary tumor and metastases (P + M): 0.92 [0.80-0.97]), the highest specificity in the subgroup of P + M (0.85 [0.61-0.97]), and achieved the highest superiority index in the subgroups of all data (8.57 [1-15]) and P + M (7.25 [1-13]).Conclusion18F-FDOPA PET/CT exhibited the best diagnostic performance in the comprehensive detection of primary tumor and metastases for neuroblastic tumors, followed by 68Ga-somatostatin analogs, 123I-meta-iodobenzylguanidine (MIBG), 18F-FDG, and 131I-MIBG tomographic imaging.

Dataset Information

The Added Value of Diagnostic and Theranostic PET Imaging for the Treatment of CNS Tumors.

Publications

The Added Value of Diagnostic and Theranostic PET Imaging for the Treatment of CNS Tumors.

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