Evidence map›Paper›PMID 36975465›Full record

ArticleCurrent oncology (Toronto, Ont.)2023

Evaluation of Classic and Quantitative Imaging Features in the Differentiation of Benign and Atypical Lipomatous Soft Tissue Tumors Using a Standardized Multiparametric MRI Protocol: A Prospective Single-Centre Study in 45 Patients.

Leonhard Gruber, Christian Kremser, Bettina Zelger, Anton Schwabegger, Ena Josip, Dietmar Dammerer, Martin Thaler, Benjamin Henninger

Open access · goldFull text read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2023. 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
0.8field-weighted citation impact, top 26% of its field
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, 3 citations in OpenAlex.

  1. Review
  2. 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 at 3 institutions in 2 countries.

Leonhard GruberDepartment of Radiology, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Christian KremserDepartment of Radiology, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.ORCID 0000-0002-6953-935X
Bettina ZelgerDepartment of Pathology, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Anton SchwabeggerDepartment of Plastic, Reconstructive and Aesthetic Surgery, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Ena JosipDepartment of Radiology, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Dietmar DammererDepartment of Orthopaedics and Trauma Surgery, Universitätsklinikum Krems, 3500 Krems an der Donau, Austria.ORCID 0000-0002-3212-4580
Martin ThalerArthroplasty Center Munich West, Helios Klinikum, Steinerweg 5, 81241 Munich, Germany.
Benjamin HenningerDepartment of Radiology, Medical University Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria.
Innsbruck Medical University · ATUniversitätsklinikum Krems · ATUniversitätsmedizin Greifswald · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiscrimination between benign and atypical lipomatous tumors (ALT) is important due to potential local complications and recurrence of ALT but can be difficult due to the often-similar imaging appearance. Using a standardized MRI protocol, this study aimed to rank established and quantitative MRI features by diagnostic value in the differentiation of benign and atypical lipomatous tumors and to develop a robust scoring system.

methodsPatients with clinical or sonographic suspicion of a lipomatous tumor were prospectively and consecutively enrolled from 2015 to 2019 after ethic review board approval. Histology was confirmed for all ALT and 85% of the benign cases. Twenty-one demographic and morphologic and twenty-three quantitative features were extracted from a standardized MRI protocol (T1/T2-proton-density-weighting, turbo-inversion recovery magnitude, T2* multi-echo gradient-echo imaging, qDIXON-Vibe fat-quantification, T1 relaxometry, T1 mapping, diffusion-weighted and post-contrast sequences). A ranking of these features was generated through a Bayes network analysis with gain-ratio feature evaluation.

resultsForty-five patients were included in the analysis (mean age, 61.2 ± 14.2 years, 27 women [60.0%]). The highest-ranked ALT predictors were septation thickness (gain ratio merit [GRM] 0.623 ± 0.025,

conclusionsSeveral single MRI features have a substantial diagnostic value in the identification of ALT, yet a multiparametric approach by a simple combination algorithm may support radiologists in the identification of lipomatous tumors in need for further histological assessment.

Indexed as

LipomaLiposarcomaMultiparametric Magnetic Resonance ImagingSoft Tissue NeoplasmsAgedBayes TheoremFemaleHumansMiddle AgedProspective Studiesatypical lipomatous tumorsimaging featureslipomaMRIrankingsoft tissue tumors

Identifiers

PMID36975465
PMCPMC10047222
OpenAlexW4324056331

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LicenceCC BY
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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.