Evidence map›Paper›PMID 34272315›Full record

ArticleJournal of nuclear medicine : official publication, Society of Nuclear Medicine2022

Quantitative Radiomics Features in Diffuse Large B-Cell Lymphoma: Does Segmentation Method Matter?

Jakoba J Eertink, Elisabeth A G Pfaehler, Sanne E Wiegers, Tim van, de Brug, Pieternella J Lugtenburg, Otto S Hoekstra, Josée M Zijlstra, Henrica C W de Vet, Ronald Boellaard

Abstract read
In one paragraph

Article in Journal of nuclear medicine : official publication, Society of Nuclear Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

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

  1. Pooled it
  2. Diagnostic Value ofTechnology in cancer research & treatment
    Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. A proof of concept study ofScientific reports · 2025
    Article
  8. Summary Report of the SNMMI AI Task Force Radiomics Challenge 2024.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025
    Article
  9. Association of [Diagnostics (Basel, Switzerland) · 2025
    Article
  10. Article
  11. Article
  12. Radiomics based onQuantitative imaging in medicine and surgery · 2025
    Article
  13. Review
  14. Article
  15. Article
  16. Predicting T-Cell Lymphoma in Children FromJournal of imaging informatics in medicine · 2024
    Article
  17. Article
  18. Article
  19. PrognosticDiagnostics (Basel, Switzerland) · 2023
    Article
  20. 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

10 authors.

Jakoba J EertinkDepartment of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Elisabeth A G PfaehlerDepartment of Nuclear Medicine, University Hospital Augsburg, Augsburg, Germany.
Sanne E WiegersDepartment of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Tim van
de BrugDepartment of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Pieternella J LugtenburgDepartment of Hematology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands; and.
Otto S HoekstraDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Josée M ZijlstraDepartment of Hematology, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Henrica C W de VetDepartment of Epidemiology and Data Science, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Ronald BoellaardDepartment of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands r.boellaard@amsterdamumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiomics features may predict outcome in diffuse large B-cell lymphoma (DLBCL). Currently, multiple segmentation methods are used to calculate metabolic tumor volume (MTV). We assessed the influence of segmentation method on the discriminative power of radiomics features in DLBCL at the patient level and for the largest lesion.

Indexed as

Lymphoma, Large B-Cell, DiffusePositron Emission Tomography Computed TomographyFluorodeoxyglucose F18HumansNeoplasm Recurrence, LocalTumor BurdenFluorodeoxyglucose F1818F-FDG PET/CTdiffuse large B-cell lymphomaradiomicssegmentation methods

Identifiers

PMID34272315
PMCPMC8978204

What OpenQuestion holds

Textmetadata
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.