ArticleEuropean journal of nuclear medicine and molecular imaging2015
Prognostic value of volume-based measurements on (11)C-methionine PET in glioma patients.
Article in European journal of nuclear medicine and molecular imaging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- MRI combined with PET-CT of different tracers to improve the accuracy of glioma diagnosis: a systematic review and meta-analysis.Neurosurgical review · 2019Pooled it
- Prognostic Value of the Metabolic and Volumetric Parameters ofAJNR. American journal of neuroradiology · 2018Pooled it
- 11C-methionine-PET for differentiating recurrent brain tumor from radiation necrosis: radiomics approach with random forest classifier.Scientific reports · 2019Trial
- Tumor boundary delineation in IDH-wildtype glioblastoma: A prospective comparative analysis ofNeuro-oncology practice · 2026Article
- Evaluation of [Journal of clinical medicine · 2025Article
- Radiomics for residual tumour detection and prognosis in newly diagnosed glioblastoma based on postoperative [Scientific reports · 2024Article
- Prognosis prediction based on methionine metabolism genes signature in gliomas.BMC medical genomics · 2023Article
- Article
- Differentiating high-grade glioma progression from treatment-related changes with dynamic [European radiology · 2023Article
- Article
- Prognostic value of 11C-methionine volume-based PET parameters in IDH wild type glioblastoma.PloS one · 2022Article
- Worse prognosis for IDH wild-type diffuse gliomas with larger residual biological tumor burden.Annals of nuclear medicine · 2021Article
- Met-PET uptake index for total tumor resection: identification ofNeurosurgical review · 2021Article
- Preoperative Texture Analysis UsingDiagnostics (Basel, Switzerland) · 2021Article
- Semi-automatic evaluation of baseline whole-body tumor burden as an imaging biomarker ofAbdominal radiology (New York) · 2020Article
- Maximum Uptake and Hypermetabolic Volume of 18F-FDOPA PET Estimate Molecular Status and Overall Survival in Low-Grade Gliomas: A PET and MRI Study.Clinical nuclear medicine · 2020Article
- Nose-to-brain delivery: exploring newer domains for glioblastoma multiforme management.Drug delivery and translational research · 2020Review
- Influence of the scan time point when assessing hypoxia inEuropean journal of nuclear medicine and molecular imaging · 2020Article
- Article
- Multimodal imaging-defined subregions in newly diagnosed glioblastoma: impact on overall survival.Neuro-oncology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose(11)C-methionine (MET) PET is an established diagnostic tool for glioma. Studies have suggested that MET uptake intensity in the tumor is a useful index for predicting patient outcome. Because MET uptake is known to reflect tumor expansion more accurately than MRI, we aimed to elucidate the association between volume-based tumor measurements and patient prognosis.
methodsThe study population comprised 52 patients with newly diagnosed glioma who underwent PET scanning 20 min after injection of 370 MBq MET. The tumor was contoured using a threshold of 1.3 times the activity of the contralateral normal cortex. Metabolic tumor volume (MTV) was defined as the total volume within the boundary. Total lesion methionine uptake (TLMU) was defined as MTV times the mean standardized uptake value (SUVmean) within the boundary. The tumor-to-normal ratio (TNR), calculated as the maximum standardized uptake value (SUVmax) divided by the contralateral reference value, was also recorded. All patients underwent surgery (biopsy or tumor resection) targeting the tissue with high MET uptake. The Kaplan-Meier method was used to estimate the predictive value of each measurement.
resultsGrade II tumor was diagnosed in 12 patients (3 diffuse astrocytoma, 2 oligodendroglioma, and 7 oligoastrocytoma), grade III in 18 patients (8 anaplastic astrocytoma, 6 anaplastic oligodendroglioma, and 4 anaplastic oligoastrocytoma), and grade IV in 22 patients (all glioblastoma). TNR, MTV and TLMU were 3.1 ± 1.2, 51.6 ± 49.9 ml and 147.7 ± 153.3 ml, respectively. None of the three measurements was able to categorize the glioma patients in terms of survival when all patients were analyzed. However, when only patients with astrocytic tumor (N = 33) were analyzed (i.e., when those with oligodendroglial components were excluded), MTV and TLMU successfully predicted patient outcome with higher values associated with a poorer prognosis (P < 0.05 and P < 0.01, respectively), while the predictive ability of TNR did not reach statistical significance (P = NS).
conclusionMTV and TLMU may be useful for predicting outcome in patients with astrocytic tumor.
Indexed as
Identifiers
25852010What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.