Fat-containing soft-tissue tumors: Imaging findings and pathologic correlation.
Authors
Affiliations (6)
Affiliations (6)
- Department 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. [email protected].
- Department of Radiology, ARNAS G. Brotzu - Businco Oncologic Hospital, Cagliari, Italy.
- Department 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.
- Diagnostic and Interventional Radiology Unit, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
- Department of Pathology and Forensic Medicine, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil.
- Department of Orthopedics and Anesthesiology, Ribeirao Preto Medical School, University of Sao Paulo, Ribeirão Preto, São Paulo, Brazil.
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.