Developing a clinical scoring system to differentiate deep-seated atypical lipomatous tumor from lipoma of soft tissue.

Asian J Surg

Division of Plastic Surgery, Department of Surgery, National Taiwan University Hospital, College of Medicine, Taipei, Taiwan. Electronic address:

Published: August 2019

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Article Abstract

Background: Atypical lipomatous tumor (ALT) is a low-grade malignancy that frequently occurs at a subfascial anatomical location. While marginal excision is adequate for lipomas, excision with a surgical margin is suggested for ALTs. However, ALTs and lipomas are difficult to differentiate preoperatively, even with the help of imaging studies. In this study, we aimed to formulate a scoring system based on selected clinical and imaging characteristics to enhance the accuracy of pre-operative diagnosis of deep-seated ALTs.

Methods: We enrolled 417 cases of deep-seated lipoma and 53 cases of ALTs from soft tissue treated between 2005 and 2016. Tumors arising from the bone, internal cavities, retroperitoneum, or nervous system were excluded. Clinical data were analyzed along with magnetic resonance image (MRI) features. We further developed a scoring formula to distinguish deep-seated ALTs from lipomas.

Results: Older age, tumor location at lower limbs, and the presence of MRI features (larger size, thick septa > 2 mm, contrast enhancement>1 cm, fat component <75%) are identified as risk factors of ALT and were utilized to develop a scoring system for distinguishing ALTs from lipomas. The formula exhibited 90% sensitivity and 92.5% specificity, and a score more than 0.214 suggested a diagnosis of ALT.

Conclusions: The scoring system developed in this study can facilitate the pre-operative diagnosis of deep-seated ALTs and lipomas. If ALT is suspected, further tumor biopsy followed by molecular diagnosis can establish a definite diagnosis. Therefore, this scoring system can serve as a cost-effective tool for the clinical management of deep-seated lipomatous tumors.

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http://dx.doi.org/10.1016/j.asjsur.2018.12.012DOI Listing

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