Evidence map›Paper›PMID 39089812›Full record

ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2024

International Benchmark for Total Metabolic Tumor Volume Measurement in Baseline

Ronald Boellaard, Irène Buvat, Christophe Nioche, Luca Ceriani, Anne-Ségolène Cottereau, Luca Guerra, Rodney J Hicks, Salim Kanoun, Carsten Kobe, Annika Loft and 14 more

Abstract read
In one paragraph

Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Review
  8. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
    Review
  9. Article
  10. Article
  11. Article
  12. Validation of an AI Method for Automated Lymphoma Metabolic Tumor Volume Segmentation Using a Public Benchmark PET/CT Dataset.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2026
    Article
  13. Naïve CD4Nature communications · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. The prognostic value ofAnnals of nuclear medicine · 2026
    Article
  18. Article
  19. Classical Hodgkin Lymphoma Today.Mediterranean journal of hematology and infectious diseases · 2026
    Review
  20. Biological tumor volume predicts survival in recurrent High-Grade glioma: A multiparametric [European journal of nuclear medicine and molecular imaging · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Ronald BoellaardDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Cancer Center Amsterdam, Amsterdam, The Netherlands; r.boellaard@amsterdamumc.nl.
Irène BuvatLITO, Inserm, Institut Curie, Orsay, France.
Christophe NiocheLITO, Inserm, Institut Curie, Orsay, France.
Luca CerianiClinic of Nuclear Medicine and PET-CT Centre, Imaging Institute of Southern Switzerland; and EOC, Institute of Oncology Research, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona, Switzerland.
Anne-Ségolène CottereauDepartment of Nuclear Medicine, Cochin Hospital, APHP; and Faculté de Médecine, Université Paris Cité, Paris, France.
Luca GuerraNuclear Medicine Unit, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy.
Rodney J HicksDepartment of Medicine, St. Vincent's Hospital Medical School, University of Melbourne, Melbourne, Victoria, Australia.
Salim KanounCentre de Recherche Clinique de Toulouse, Team 9, Toulouse, France.
Carsten KobeDepartment of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
Annika LoftPET & Cyclotron Unit 3982, Copenhagen University Hospital, Copenhagen, Denmark.
Heiko SchöderMolecular Imaging and Therapy Service, Memorial Sloan Kettering Cancer Center, New York, New York.
Annibale VersariNuclear Medicine Department, Azienda Unità Sanitaria Locale-IRCCS, Reggio Emilia, Italy.
Conrad-Amadeus VoltinDepartment of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
Gerben J C ZwezerijnenDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Josée M ZijlstraDepartment of Hematology, Amsterdam UMC, Cancer Center Amsterdam, Amsterdam, The Netherlands.
N George MikhaeelDepartment of Clinical Oncology, Guy's Cancer Centre and School of Cancer and Pharmaceutical Sciences, King's College London University, London, United Kingdom.
Andrea GallaminiResearch and Innovation Department, Antoine Lacassagne Cancer Center, Nice, France.
Tarec C El-GalalyDepartment of Hematology, Aalborg University Hospital, Aalborg, Denmark.
Christine HanounDepartment of Hematology and Stem Cell Transplantation, West German Cancer Center, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Stephane ChauvieMedical Physics Division, Santa Croce e Carle Hospital, Cuneo, Italy.
Romain RicciLYSARC, Centre Hospitalier Lyon-Sud, Pierre-Bénite, France.
Emanuele ZuccaOncology Institute of Southern Switzerland; and EOC, Institute of Oncology Research, Faculty of Biomedical Sciences, Università della Svizzera Italiana, Bellinzona, Switzerland; and.
Michel MeignanDepartment of Nuclear Medicine, Cochin Hospital, APHP; and Faculté de Médecine, Université Paris Cité, Paris, France.
Sally F BarringtonKing's College London and Guy's and St. Thomas's PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Total metabolic tumor volume (TMTV) is prognostic in lymphoma. However, cutoff values for risk stratification vary markedly, according to the tumor delineation method used. We aimed to create a standardized TMTV benchmark dataset allowing TMTV to be tested and applied as a reproducible biomarker.

Indexed as

BenchmarkingFluorodeoxyglucose F18LymphomaPositron Emission Tomography Computed TomographyTumor BurdenAdultAgedAged, 80 and overFemaleHumansImage Processing, Computer-AssistedInternationalityMaleMiddle AgedYoung AdultFluorodeoxyglucose F1818F-FDG PET/CTbenchmarklymphomatotal metabolic tumor volume

Identifiers

PMID39089812
PMCPMC11372260

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.