Trial reportEuropean journal of nuclear medicine and molecular imaging2009
Assessment of various strategies for 18F-FET PET-guided delineation of target volumes in high-grade glioma patients.
Trial report in European journal of nuclear medicine and molecular imaging, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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
38 citing papers in PubMed, 109 citations in OpenAlex.
- Trial
- Integrated-boost IMRT or 3-D-CRT using FET-PET based auto-contoured target volume delineation for glioblastoma multiforme--a dosimetric comparison.Radiation oncology (London, England) · 2009Trial
- [(18)F]Fluoroethyltyrosine- positron emission tomography-guided radiotherapy for high-grade glioma.Radiation oncology (London, England) · 2008Trial
- Revisiting the segmentation threshold for Lu-177 SPECT.Medical physics · 2026Article
- A Tumor Volume Segmentation Algorithm Based on Radiomics Features in FDG-PET in Lung Cancer Patients, Validated Using Surgical Specimens.Diagnostics (Basel, Switzerland) · 2024Article
- Repeatability of image features extracted from FET PET in application to post-surgical glioblastoma assessment.Physical and engineering sciences in medicine · 2021Article
- Heterogeneous parameters based onQuantitative imaging in medicine and surgery · 2021Article
- Intensity threshold based solid tumour segmentation method for Positron Emission Tomography (PET) images: A review.Heliyon · 2020Review
- PET segmentation of bulky tumors: Strategies and workflows to improve inter-observer variability.PloS one · 2020Article
- Impact ofScientific reports · 2018Article
- Evaluation of factors influencingNeuroImage. Clinical · 2018Article
- Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211.Medical physics · 2017Article
- Relationship between Glioblastoma Dose Volume Parameters Measured by Dual Time Point Fluoroethylthyrosine-PET and Clinical Outcomes.Frontiers in neurology · 2017Article
- Early static (18)F-FET-PET scans have a higher accuracy for glioma grading than the standard 20-40 min scans.European journal of nuclear medicine and molecular imaging · 2016Article
- Current standards and new concepts in MRI and PET response assessment of antiangiogenic therapies in high-grade glioma patients.Neuro-oncology · 2015Review
- Dose-painting intensity-modulated proton therapy for intermediate- and high-risk meningioma.Radiation oncology (London, England) · 2015Article
- Adaptive threshold segmentation of pituitary adenomas from FDG PET images for radiosurgery.Journal of applied clinical medical physics · 2014Article
- A review on segmentation of positron emission tomography images.Computers in biology and medicine · 2014Review
- Tryptophan PET-defined gross tumor volume offers better coverage of initial progression than standard MRI-based planning in glioblastoma patients.Journal of radiation oncology · 2014Article
- Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods.Cancer management and research · 2014Review
Corrections and comments
- Commented on by
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe purpose of the study is to assess the contribution of (18)F-fluoro-ethyl-tyrosine ((18)F-FET) positron emission tomography (PET) in the delineation of gross tumor volume (GTV) in patients with high-grade gliomas compared with magnetic resonance imaging (MRI) alone. MATERIALS AND
methodsThe study population consisted of 18 patients with high-grade gliomas. Seven image segmentation techniques were used to delineate (18)F-FET PET GTVs, and the results were compared to the manual MRI-derived GTV (GTV(MRI)). PET image segmentation techniques included manual delineation of contours (GTV(man)), a 2.5 standardized uptake value (SUV) cutoff (GTV(2.5)), a fixed threshold of 40% and 50% of the maximum signal intensity (GTV(40%) and GTV(50%)), signal-to-background ratio (SBR)-based adaptive thresholding (GTV(SBR)), gradient find (GTV(GF)), and region growing (GTV(RG)). Overlap analysis was also conducted to assess geographic mismatch between the GTVs delineated using the different techniques.
resultsContours defined using GTV(2.5) failed to provide successful delineation technically in three patients (18% of cases) as SUV(max) < 2.5 and clinically in 14 patients (78% of cases). Overall, the majority of GTVs defined on PET-based techniques were usually smaller than GTV(MRI) (67% of cases). Yet, PET detected frequently tumors that are not visible on MRI and added substantially tumor extension outside the GTV(MRI) in six patients (33% of cases).
conclusionsThe selection of the most appropriate (18)F-FET PET-based segmentation algorithm is crucial, since it impacts both the volume and shape of the resulting GTV. The 2.5 SUV isocontour and GF segmentation techniques performed poorly and should not be used for GTV delineation. With adequate setting, the SBR-based PET technique may add considerably to conventional MRI-guided GTV delineation.
Indexed as
Identifiers
What 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.