ArticleEJNMMI research2017
Impact of the EARL harmonization program on automatic delineation of metabolic active tumour volumes (MATVs).
Article in EJNMMI research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- EANM guideline on the role of 2-[European journal of nuclear medicine and molecular imaging · 2021Guideline
- Quantitative [Molecular imaging and biology · 2026Trial
- Clinical Robustness of FDG-PET/CT Quantitative Metrics Post-Harmonization in a Multicenter, Cross-Scanner Setting.Tomography (Ann Arbor, Mich.) · 2026Article
- Article
- Review on radiomic analysis inCancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts.European journal of nuclear medicine and molecular imaging · 2023Article
- Principal component analysis of texture features derived from FDG PET images of melanoma lesions.EJNMMI physics · 2022Article
- Joint EANM/SNMMI/ANZSNM practice guidelines/procedure standards on recommended use of [European journal of nuclear medicine and molecular imaging · 2022Article
- New PET technologies - embracing progress and pushing the limits.European journal of nuclear medicine and molecular imaging · 2021Article
- Asphericity of tumor FDG uptake in non-small cell lung cancer: reproducibility and implications for harmonization in multicenter studies.EJNMMI research · 2020Article
- Characterization of FDG PET Images Using Texture Analysis in Tumors of the Gastro-Intestinal Tract: A Review.Biomedicines · 2020Review
- Granulomatous-Lymphocytic Interstitial Lung Disease in Common Variable Immunodeficiency-Features of CT andFrontiers in immunology · 2020Observational
- Hormonal Receptor Immunochemistry Heterogeneity andFrontiers in oncology · 2020Article
- Repeatability of [EJNMMI research · 2019Article
- Why harmonization is needed when using FDG PET/CT as a prognosticator: demonstration with EARL-compliant SUV as an independent prognostic factor in lung cancer.European journal of nuclear medicine and molecular imaging · 2019Article
- FDG PET/CT for assessing tumour response to immunotherapy : Report on the EANM symposium on immune modulation and recent review of the literature.European journal of nuclear medicine and molecular imaging · 2019Review
- Implications of reconstruction protocol for histo-biological characterisation of breast cancers using FDG-PET radiomics.EJNMMI research · 2018Article
- Combining baseline TMTV and gene profiling for a better risk stratification in diffuse large B cell lymphoma.European journal of nuclear medicine and molecular imaging · 2018Article
- Reply to: "All that glitters is not gold - new reconstruction methods using Deauville criteria for patient reporting".European journal of nuclear medicine and molecular imaging · 2018Article
- Volumetric parameters on FDG PET can predict early intrahepatic recurrence-free survival in patients with hepatocellular carcinoma after curative surgical resection.European journal of nuclear medicine and molecular imaging · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe clinical validation of the EARL harmonization program for standardised uptake value (SUV) metrics is well documented; however, its potential for defining metabolic active tumour volume (MATV) has not yet been investigated. We aimed to compare delineation of MATV on images reconstructed using conventional ordered subset expectation maximisation (OSEM) with those reconstructed using point spread function modelling (PSF-reconstructed images), and either optimised for diagnostic potential (PSF) or filtered to meet the EANM/EARL harmonising standards (PSF
methodsImages from 18 stage IIIA-IIIB lung cancer patients were reconstructed using all the three methods. MATVs were then delineated using both a 40% isocontour and a gradient-based method. MATVs were compared by means of Bland-Altman analyses, and Dice coefficients and concordance indices based on the unions and intersections between each pair of reconstructions (PSF vs OSEM, PSF
resultsUsing the 40% isocontour method and taking the MATVs delineated on OSEM images as a reference standard, the use of PSF
conclusionThis study demonstrates that automatic contouring of lung tumours on EARL-compliant PSF images using the widely adopted automatic isocontour methodology is an accurate means of overcoming reconstruction variability in MATV delineation. Although gradient-based methodology appears to be less sensitive to reconstruction variability, the use of EARL-compliant PSF images significantly improved the Dice coefficients and concordance indices, demonstrating the importance of harmonised-images, even when more advanced contouring algorithms are used.
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.