Evidence map›Paper›PMID 41714734›Full record

ReviewSkeletal radiology2026

Fat-containing soft-tissue tumors: Imaging findings and pathologic correlation.

Leonor G Savarese, Nicolas Papalexis, Mateus A Hernandes, Paolo Spinnato, Joel Del Bel Pádua, Giancarlo Facchini, Nelson F Gava, Edgard E Engel, Marcello Henrique Nogueira-Barbosa

Abstract readReview
In one paragraph

Review in Skeletal radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Leonor G SavareseDepartment of Medical Imaging, Hematology and Clinical Oncology, Ribeirao Preto Medical School, University of Sao Paulo, Av. Bandeirantes, 3900 CEP, Ribeirão Preto, SP, 14049-090, Brazil. lsavarese@hcrp.usp.br.ORCID http://orcid.org/0000-0002-1372-9162
Nicolas PapalexisDepartment of Radiology, ARNAS G. Brotzu - Businco Oncologic Hospital, Cagliari, Italy.
Mateus A HernandesDepartment of Medical Imaging, Hematology and Clinical Oncology, Ribeirao Preto Medical School, University of Sao Paulo, Av. Bandeirantes, 3900 CEP, Ribeirão Preto, SP, 14049-090, Brazil.
Paolo SpinnatoDiagnostic and Interventional Radiology Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Joel Del Bel PáduaDepartment of Pathology and Forensic Medicine, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil.
Giancarlo FacchiniDiagnostic and Interventional Radiology Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
Nelson F GavaDepartment of Orthopedics and Anesthesiology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil.
Edgard E EngelDepartment of Orthopedics and Anesthesiology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil.
Marcello Henrique Nogueira-BarbosaDepartment of Medical Imaging, Hematology and Clinical Oncology, Ribeirao Preto Medical School, University of Sao Paulo, Av. Bandeirantes, 3900 CEP, Ribeirão Preto, SP, 14049-090, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fat-containing soft-tissue tumors encompass a broad spectrum of entities, ranging from indolent lipomas to aggressive liposarcomas, many of which share overlapping MRI features that pose diagnostic challenges even for experienced radiologists. In this review, we provide a focused, evidence-based synthesis of the current literature to outline a practical framework for the imaging evaluation of adipocytic soft-tissue lesions. Key MRI features that aid in distinguishing benign from intermediate and malignant tumors are discussed, with emphasis on imaging-pathology correlation and common diagnostic pitfalls. While conventional MRI criteria, such as lesion size, depth, septal thickness, and nodularity, remain central to risk stratification, we also review the complementary role of contrast-enhanced MRI and molecular testing, including MDM2 amplification and FUS::DDIT3 fusion analysis, particularly in indeterminate cases. Emerging tools, such as radiomics and artificial intelligence-based approaches, are briefly addressed as evolving adjuncts. By integrating classical imaging principles with contemporary classification frameworks, this article aims to serve as a comprehensive and clinically relevant reference for radiologists involved in the assessment and management of fat-containing soft-tissue tumors.

Indexed as

Adipose TissueLipomaMagnetic Resonance ImagingNeoplasms, Adipose TissueSoft Tissue NeoplasmsContrast MediaDiagnosis, DifferentialHumansRadiomicsContrast MediaFatLipomaLiposarcomaMagnetic resonance imagingMRINeoplasmSoft-tissue tumor

Identifiers

PMID41714734
PMCPMC13198520

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.