Comparison of l-Methyl-11C-Methionine PET With Magnetic Resonance Spectroscopy in Detecting Newly Diagnosed Glioma

Kebir, Sied; Lazaridis, Lazaros; Weber, Manuel; Deuschl, Cornelius; Stoppek, Ann-Kathrin; Schmidt, Teresa; Mönninghoff, Christoph; Blau, Tobias; Keyvani, Kathy; Umutlu, Lale; Pierscianek, Daniela; Forsting, Michael; Stuschke, Martin; Antoch, Gerald; Sure, Ulrich; Kleinschnitz, Christoph; Scheffler, Björn; Colletti, Patrick M.; Rubello, Domenico; Herrmann, Ken; Glas, Martin

doi:10.1097/rlu.0000000000002577

Cited by 13 publications

(12 citation statements)

References 17 publications

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“…Kebir et al scanned 19 histologically confirmed gliomas with MET PET and MRS in a single standardized imaging session, prior to treatment, and compared their ability to classify glioma molecular subtypes [ 64 ]. The spectroscopy peaks for NAA, choline, and Cr were used as the MRS parameters.…”

Section: Resultsmentioning

confidence: 99%

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

2021

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Introduction. Standard neuroimaging protocols for brain tumors have well-known limitations. The clinical use of additional modalities including amino acid PET (aaPET) and advanced MRI (aMRI) techniques (including DWI, PWI, and MRS) is emerging in response to the need for more accurate detection of brain tumors. In this systematic review of the past 2 years of the literature, we discuss the most recent studies that directly compare or combine aaPET and aMRI for brain tumor imaging. Methods. A PubMed search was conducted for human studies incorporating both aaPET and aMRI and published between July 2018 and August 2020. Results. A total of 22 studies were found in the study period. Recent studies of aaPET with DWI showed a superiority of MET, FET, FDOPA, and AMT PET for detecting tumor, predicting recurrence, diagnosing progression, and predicting survival. Combining modalities further improved performance. Comparisons of aaPET with PWI showed mixed results about spatial correlation. However, both modalities were able to detect high-grade tumors, identify tumor recurrence, differentiate recurrence from treatment effects, and predict survival. aaPET performed better on these measures than PWI, but when combined, they had the strongest results. Studies of aaPET with MRS demonstrated that both modalities have diagnostic potential but MET PET and FDOPA PET performed better than MRS. MRS suffered from some data quality issues that limited analysis in two studies, and, in one study that combined modalities, overall performance actually decreased. Four recent studies compared aaPET with emerging MRI approaches (such as CEST imaging, MR fingerprinting, and SISTINA), but the initial results remain inconclusive. Conclusions. aaPET outperformed the aMRI imaging techniques in most recent studies. DWI and PWI added meaningful complementary data, and the combination of aaPET with aMRI yielded the best results in most studies.

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Section: Resultsmentioning

confidence: 99%

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

2021

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“…One O-(2-18 F-fluoroethyl)-L-tyrosine( 18 F-FET) PET research in a mixed group of glioma patients, which included 16 oligodendrogliomas (IDH mutated and 1p/19q co-deleted), 27 astrocytomas (IDH mutated only) and 47 glioblastomas (IDH-wildtype), suggested that gliomas with IDH mutation are typically shown with a lower tumor to brain ratios(TNRmean and TNRmax), prolonged time to peak, and a slow-rise time-activity curve of 20-50 min (29). By contrast, another 3,4-dihydroxy-6-[ 18 F]fluoro-L-phenylalanine ( 18 F-FDOPA) imaging study in a total of 43 newly diagnosed glioma cases described paradoxically higher 18 F-FDOPA uptake in diffuse grade II and III gliomas with IDH mutation (30). This inconsistency may be explained by the different amino acids PET probe uptake models in glioma (31).…”

Section: Discussionmentioning

confidence: 99%

“…The MET uptake of IDH-wildtype glioblastoma was significantly higher than that of IDH-mutant glioma ( 17 ). TNRmax derived from 11 C-MET PET appears to be superior to MRS in differentiating IDH status with a ROC of 0.67 ( 18 ). The investigations on the relationship between amino acid tracer uptake and IDH status were not totally consistent.…”

Section: Discussionmentioning

confidence: 99%

“…The results are inspiring since T2-weighted MR imaging is widely available and routinely performed in the assessment of gliomas. Some studies have explored the relationship between amino acid uptake characteristics of gliomas and IDH mutation status (15)(16)(17)(18)(19). We aimed to develop a novel and convenient statistical model that combines PET features and clinical factors for an IDH-predictive signature.…”

Section: Introductionmentioning

confidence: 99%

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

Zhou

Wen

et al. 2020

Front. Oncol.

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Purpose: We developed a 11 C-Methionine positron emission tomography/computed tomography ( 11 C-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 11 C-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 11 C-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: 11 C-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 11 C-Methionine PET/CT and clinical age features might be clinically useful in non-invasive IDH mutation status prediction for untreated glioma patients.

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“…Moreover, the ability of 18 F-DOPA ( 18 F-f luorodihydroxyphenylalanine) uptake parameters from PET-CT to reflect molecular and histological features is limited, and the prediction of prognosis is inefficient (7). In contrast, MRI markers can better reflect glioma biological features and predict a patient's progression-free survival (8,9).…”

Section: Introductionmentioning

confidence: 99%

Predicting cancer malignancy and proliferation in glioma patients: intra-subject inter-metabolite correlation analyses using MRI and MRSI contrast scans

Su¹,

Li²,

Chen³

et al. 2021

Quant Imaging Med Surg

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Background: The non-invasive characterization of glioma metabolites would greatly assist the management of glioma patients in the clinical setting. This study investigated the applicability of intra-subject inter-metabolite correlation analyses for differentiating glioma malignancy and proliferation.Methods: A total of 17 negative controls (NCs), 39 low-grade gliomas (LGGs) patients, and 25 highgrade gliomas (HGGs) subjects were included in this retrospective study. Amide proton transfer (APT) and magnetization transfer contrast (MTC) imaging contrasts, as well as total choline/total creatine (tCho/tCr) and total N-acetylaspartate/total creatine (tNAA/tCr) ratios quantified from magnetic resonance spectroscopic imaging (MRSI) were co-registered voxel-wise and used to produce three intra-subject inter-metabolite correlation coefficients (IMCCs), namely, R APT vs. MTC , R APT vs. tCho/tCr , and R MTC vs. tNAA/tCr . The correlation between the IMCCs and tumor grade and Ki-67 labeling index (LI) for tumor proliferation were explored. The differences in the IMCCs between the three groups were compared with one-way analysis of variance (ANOVA). Finally, regression analysis was used to build a combined model with multiple IMCCs to improve the diagnostic performance for tumor grades based on receiver operator characteristic curves.Results: Compared with the NCs, gliomas showed stronger inter-metabolic correlations. R APT vs. MTC was significantly different among the three groups (NC vs. LGGs vs. HGGs: −0.18±0.38 vs. −0.40±0.34 vs. −0.70±0.29, P<0.0001). No significant differences were detected in R MTC vs. tNAA/tCr among the three groups. R APT vs. MTC and R APT vs. tCho/tCr correlated significantly with tumor grade (R=−0.41, P=0.001 and R=0.448, P<0.001, respectively).However, only R APT vs. MTC was mildly correlated with Ki-67 (R=−0.33, P=0.02). R APT vs. MTC and R APT vs. tCho/tCr achieved areas under the curve (AUCs) of 0.754 and 0.71, respectively, for differentiating NCs from gliomas; and 0.77 and 0.78, respectively, for differentiating LGGs from HGGs. The combined multi-IMCCs model improved the correlation with the Ki-67 LI (R=0.46, P=0.0008) and the tumor-grade stratification with AUC increased to 0.85 (sensitivity: 80.0%, specificity: 79.5%).Conclusions: This study demonstrated that glioma patients showed stronger inter-metabolite correlations than control subjects, and the IMCCs were significantly correlated with glioma grade and proliferation. The multi-IMCCs combined model further improved the performance of clinical diagnosis.

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Comparison of l-Methyl-11C-Methionine PET With Magnetic Resonance Spectroscopy in Detecting Newly Diagnosed Glioma

Cited by 13 publications

References 17 publications

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

Comparison of Amino Acid PET to Advanced and Emerging MRI Techniques for Neurooncology Imaging: A Systematic Review of the Recent Studies

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

Predicting cancer malignancy and proliferation in glioma patients: intra-subject inter-metabolite correlation analyses using MRI and MRSI contrast scans

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