Evidence map›Paper›PMID 40785919›Full record

ArticleQuantitative imaging in medicine and surgery2025

Comparison of standardized uptake value and standardized uptake lean body mass metrics in

Jorge D Oldan, Christopher E Jensen, Deborah M Stephens, Natalie S Grover, Anne W Beaven, Christopher E Dittus, Martin A Lodge, Thad E Benefield, Steven P Rowe

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Clinical Medicine Insights. Oncology · 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

9 authors.

Jorge D OldanDivision of Molecular Imaging and Therapeutics, Department of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-8979-2010
Christopher E JensenDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-6673-335X
Deborah M StephensDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0001-9188-5008
Natalie S GroverDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-1346-3157
Anne W BeavenDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-9174-3568
Christopher E DittusDivision of Hematology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-9794-7908
Martin A LodgeThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID https://orcid.org/0000-0003-0922-6519
Thad E BenefieldDepartment of Radiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA.ORCID https://orcid.org/0000-0002-4218-3330
Steven P RoweDepartment of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID https://orcid.org/0000-0003-2897-4694

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The maximum standardized uptake value normalized to body weight (BW) (SUVmax) is a commonly used metric in Methods: We conducted a retrospective, single-center analysis of PET/computed tomography (CT) scans from patients with CLL or FL, measuring the most avid lesion using both SUVmax and SULmax. High-grade transformation was identified through pathological records within 3 months after the scan, and receiver operating characteristic curves were used to compare the diagnostic performance of SUVmax and SULmax. Results: A total of 32 patients with CLL and 58 with FL were included. Some patients had more than one biopsy, giving a total of 43 samples for CLL and 91 samples for FL. The receiver operating curve analysis showed insufficient evidence (P=0.92) of a statistical difference between SUVmax and SULmax in predicting transformation for CLL, with an area under the curve (AUC) of 0.918 for SUVmax and 0.921 for SULmax. In FL, SULmax also showed similar performance (AUC =0.754) to SUVmax (AUC =0.745) for predicting transformation to diffuse large B-cell lymphoma, with the difference again not significant (P=0.93). When grade 3B FL was also considered to be transformed lymphoma, SUVmax was effectively equal (P=0.96) to SULmax (AUC =0.932 and 0.931, respectively). Optimal cutoffs were about 7 to 8 for both diseases using SUVmax, and 5 for CLL or transformation of FL to a higher-grade lymphoma, but 9 if grade 3B was not counted. Conclusions: Both SUVmax and SULmax can be reliably used for assessing the transformation of CLL and FL to aggressive lymphomas on 18F-FDG PET/CT. Given SULmax's stability with respect to weight changes, it may be more appropriate for assessing therapeutic response in patients with significant weight fluctuations. Further studies are needed to refine the use of these metrics in clinical practice.

Indexed as

lymphomapositron emission tomography (PET)quantitationStandardized uptake value (SUV)transformation

Identifiers

PMID40785919
PMCPMC12332721

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Registered trials

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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.