Malignant histological transformation in surgically excised lipomas larger than 5 cm: Analysis of 73 cases

Background: Lipomas are benign tumors commonly presenting as soft-tissue masses. Lipomas exceeding 5 cm in diameter may pose a challenge regarding their potential malignancy. Methods: We analyzed 73 consecutive patients undergoing surgical excision for lipomas greater than 5 cm. Clinical, demographic, and histopathological data were reviewed. Tumor localization was categorized based on regions subject to high mechanical friction (neck, axillae, knees, and legs) compared with abdominal or low-friction areas. Results: Of the 73 cases initially diagnosed clinically as benign lipomas, histopathological analysis identified malignancy in 14 cases (19.2%), exclusively located in high-friction regions. Malignant cases predominantly comprised well-differentiated liposarcomas (n = 10), dedifferentiated liposarcomas (n = 3), and one case of pleomorphic liposarcoma. No malignancies were identified in abdominal (low-friction) locations. Conclusions: The significant association between tumor location in regions of high mechanical friction and the incidence of malignancy underscores the potential role of mechanical stress in malignant transformation.

Authors

Institutions

Publication Details

Journal
Il Giornale di Chirurgia - Journal of the Italian Association of Hospital Surgeons
Published
2025-12-01
DOI
https://doi.org/10.1097/ia9.0000000000000078
Primary Topic
Sarcoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Malignant histological transformation in surgically excised lipomas larger than 5 cm: Analysis of 73 cases

Sara Izzo, Massimo Zollo, Silvia Lai, Andrea Polistena et al.
Il Giornale di Chirurgia - Journal of the Italian Association of Hospital Surgeons
Sarcoma Diagnosis and Treatment
article

Malignant histological transformation in surgically excised lipomas larger than 5 cm: Analysis of 73 cases

Sara Izzo, Massimo Zollo, Silvia Lai, Andrea Polistena, Marcello Molle, Luciano Izzo, Paolo Meloni, Simone Sibio, Paolo Izzo
article en

Abstract

Background: Lipomas are benign tumors commonly presenting as soft-tissue masses. Lipomas exceeding 5 cm in diameter may pose a challenge regarding their potential malignancy. Methods: We analyzed 73 consecutive patients undergoing surgical excision for lipomas greater than 5 cm. Clinical, demographic, and histopathological data were reviewed. Tumor localization was categorized based on regions subject to high mechanical friction (neck, axillae, knees, and legs) compared with abdominal or low-friction areas. Results: Of the 73 cases initially diagnosed clinically as benign lipomas, histopathological analysis identified malignancy in 14 cases (19.2%), exclusively located in high-friction regions. Malignant cases predominantly comprised well-differentiated liposarcomas (n = 10), dedifferentiated liposarcomas (n = 3), and one case of pleomorphic liposarcoma. No malignancies were identified in abdominal (low-friction) locations. Conclusions: The significant association between tumor location in regions of high mechanical friction and the incidence of malignancy underscores the potential role of mechanical stress in malignant transformation.

Il Giornale di Chirurgia - Journal of the Italian Association of Hospital SurgeonsVol. 45(6)
University of Campania "Luigi Vanvitelli" (IT), Policlinico Umberto I (IT), Ospedale di Sanremo (IT), Campus Bio Medico University Hospital (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 42%
Sarcoma Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.