Evidence map›Paper›PMID 40824452›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2026

Can we obtain prognostic information from healthy tissue uptake and volume in baseline

Nienke R Gerards, Sanne E Wiegers, Anne L Bes, Jakoba J Eertink, Pieternella J Lugtenburg, Josée M Zijlstra, Ronald Boellaard, Gerben J C Zwezerijnen

Abstract read
In one paragraph

Article in European journal of nuclear medicine and molecular imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

8 authors.

Nienke R GerardsDepartment of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands. n.r.gerards@amsterdamumc.nl.ORCID 0009-0002-7288-7416
Sanne E WiegersCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands.ORCID 0000-0003-3698-8121
Anne L BesCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands.
Jakoba J EertinkCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands.ORCID 0000-0002-6094-0016
Pieternella J LugtenburgDepartment of Haematology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.ORCID 0000-0002-6735-8651
Josée M ZijlstraCancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands.ORCID 0000-0003-1074-5922
Ronald BoellaardDepartment of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.ORCID 0000-0002-0313-5686
Gerben J C ZwezerijnenDepartment of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.ORCID 0000-0002-9571-9362

Funding

KWF Kankerbestrijding 2018-11648
6 · The paper itself

Abstract

purposeDiffuse large B-cell lymphoma (DLBCL) patients often experience relapse or progression after treatment, emphasizing the need for better prognostic markers. This study investigated baseline FDG uptake and volume of healthy tissues and tumours, to assess their association with time-to-progression (TTP) in DLBCL.

methodsThis study included 259 newly diagnosed DLBCL patients. Outcome was two-year TTP after treatment initiation. Automatic segmentation of tissues was performed on the low dose CT scans. Tumour lesions were outlined with a semi-automated segmentation method (standardised uptake value ≥ 4) and subtracted from the tissues. Mean standardised uptake value (SUVmean), tissue-to-blood SUVmean ratio, volume, and total lesion glycolysis (TLG) were determined for the spleen, liver, kidneys, lungs, and brain. Only SUVmean and SUVmean ratio were assessed for fat, bone, and skeletal muscle. Intercorrelations among all tissues and correlations with tumour TLG were calculated. Volume and uptake measures were compared between patients with and without progression using the Wilcoxon signed-rank test. Any measure significantly associated with two-year TTP was added to an existing logistic regression model based on baseline tumour characteristics to assess its added prognostic value.

resultsPatients with progression showed a significantly higher spleen-to-blood SUVmean ratio, lower SUVmean and TLG in the brain, lower SUVmean in skeletal muscle, and a larger liver volume. Liver volume and spleen-to-blood SUVmean ratio did not significantly improve the prediction of two-year TTP compared to the original model only based on tumour characteristics.

conclusionHealthy tissue PET/CT measures were significantly associated with two-year TTP in DLBCL patients. However, these measures did not improve the prediction of two-year TTP compared to models using only tumour characteristics. TRIAL REGISTRATION NUMBER AND DATE OF REGISTRATION: HOVON-84: EudraCT: 2006-005, 174 - 42, retrospectively registered 01-08-2008.

Indexed as

Fluorodeoxyglucose F18Lymphoma, Large B-Cell, DiffusePositron Emission Tomography Computed TomographyAdultAgedAged, 80 and overBiological TransportDisease ProgressionFemaleHumansMaleMiddle AgedPrognosisTumor BurdenYoung AdultFluorodeoxyglucose F1818F-FDG PET/CTDiffuse large b-cell lymphomaHealthy tissuesPrediction

Identifiers

PMID40824452
PMCPMC12830424

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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.