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      Omental lipoma: a rare cause of a giant intra-abdominal mass

      case-report
      Author(s): , ,
      Publication date (Electronic):
      Journal: Journal of Surgical Case Reports
      Publisher: Oxford University Press

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          Abstract

          Primary tumors of the omentum, let alone omental lipomas, are rare causes of a large intra-abdominal mass. We report a case of an adult male presenting with an intra-abdominal mass, representative of a giant omental lipoma radiologically, confirmed on histopathology after complete resection at laparotomy. The case highlights the preoperative workup of a suspected omental lipoma, including the utility of various radiological modalities in differentiating from malignant pathologies, and anatomical characterization of the lesion for surgical planning.

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          Review of large deep lipomatous tumours.

          Jonathan W Serpell, L. Chen (2007)
          Lipomatous tumours comprise a range of diagnoses. There are controversies regarding the histopathological diagnosis, nomenclature, diagnostic method, surgical management, roles of radiotherapy and the risk of metastasis, local recurrence and dedifferentiation. This study describes our experience with such tumours. Retrospective review of 224 soft tissue tumours from the Senior Author's (J. W. S.) database identified 28 patients with deep lipomatous tumours. Clinical features and outcomes were studied with median follow up of 1.5 years. Eleven deep lipomas, six deep atypical lipomas, four well-differentiated (lipoma-like) liposarcomas, three well-differentiated liposarcomas and four liposarcomas were studied. Preoperative diagnosis was established by image-guided core biopsy in 20 patients, excisional biopsy in 6, incisional biopsy in 1 and fine-needle aspiration in 1. All patients diagnosed with deep lipoma and deep atypical lipoma underwent marginal excision. The median size of the excised tumour was 11 cm. Recurrence occurred in three deep atypical lipomas and one liposarcoma. Dedifferentiation occurred in one deep atypical lipoma, which transformed into a liposarcoma. None had metastasis or died of metastatic malignancy. Large deep lipomatous tumours are uncommon and although they do not tend to metastasize, they not infrequently recur locally. Hence their local treatment to prevent local recurrence is important. Key aspects in achieving a complete, but marginal resection of the deep atypical lipoma and the well-differentiated lipoma-like liposarcoma is accurate preoperative diagnosis with core biopsy and accurate imaging to assess deep unsuspected extensions of the tumour.
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            PET evaluation of fatty tumors in the extremity: possibility of using the standardized uptake value (SUV) to differentiate benign tumors from liposarcoma.

            Kenji Takagishi, Ryoko Suzuki, Tetsuya Shinozaki … (2005)
            The relative utility of various preoperative diagnostic imaging modalities, including PET (utilizing FDG and FMT), CT, and MR imaging, for evaluation of lipoma and liposarcoma, especially well-differentiated liposarcoma, was investigated. Imaging findings in 32 patients with histopathologically documented lipoma, including one with fibrolipoma and one with angiolipoma, and 25 patients with liposarcomas whose subtypes included 10 well-differentiated, 10 myxoid, and 5 other types were reviewed retrospectively. Pre-operative imaging included FDG-PET (n = 44), FMT-PET (n = 21), CT (n = 25), and MR imaging (n = 53). Statistically significant imaging features of MR images favoring a diagnosis of liposarcoma involved lesions containing less than 75% fat (p < 0.001) as well as the presence of septa (p < 0.001). As compared with well-differentiated liposarcoma, benign lesions were differentiated significantly only by the presence of septa (p < 0.001), which also provided significant differentiation on CT (p < 0.05). The mean SUVs for malignant tumors were significantly higher than those for benign lesions in both FDG- and FMT-PET analyses (p < 0.0001, p = 0.0011, respectively). By using a cut-off value for FDG- and FMT-PET set at 0.81 and 1.0 respectively, which provided the highest accuracy, benign lesions were differentiated significantly from liposarcomas (p < 0.001, and p < 0.02). Furthermore, benign tumors and the three subtypes of liposarcoma were divided significantly into four biological grades by FDG- and FMT-accumulation rates (rho = 0.793, p < 0.0001; and rho = 0.745, p = 0.0009, respectively). A cut-off value of 0.81 for FDG-PET provided significant differentiation between benign lesions and well-differentiated liposarcoma (p < 0.01). The presence of septa on MR images differentiated lipomas from liposarcoma, even well-differentiated type. PET analysis, especially FDG-PET, quantitatively provided not only the differentiation but also the metabolic separation among subtypes of liposarcoma. Interpretation of the visual diagnostic modalities requires extensive experience and carries a risk of ignoring a critical portion of malignancy. PET metabolic imaging may be an objective and useful modality for evaluating adipose tissue tumors preoperatively.
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              Resection of liposarcoma of the greater omentum: A case report and literature review

              Shintaro Hashimoto, Junichi Arai, Masato Nishimuta … (2019)
              Highlights • Intraabdominal liposarcoma including omental liposarcoma is rare. • Liposarcoma can be difficult to distinguish from other lipomotous tumor. • We surgically managed a case of liposarcoma of omentum ovserved as lipoma 3 years ago.
              Article 0 comments Cited 8 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Jia Xi Julian Li
                Hugh Lewis Giddings
                Gareth Owen
                Journal
                Journal ID (nlm-ta): J Surg Case Rep
                Journal ID (iso-abbrev): J Surg Case Rep
                Journal ID (publisher-id): jscr
                Title: Journal of Surgical Case Reports
                Publisher: Oxford University Press
                ISSN (Electronic): 2042-8812
                Publication date Collection: April 2022
                Publication date (Electronic): 25 April 2022
                Publication date PMC-release: 25 April 2022
                Volume: 2022
                Issue: 4
                Electronic Location Identifier: rjac160
                Affiliations
                Department of Surgery , St Vincent’s Hospital Sydney, Darlinghurst, New South Wales, Australia
                Department of Surgery , St Vincent’s Hospital Sydney, Darlinghurst, New South Wales, Australia
                Department of Surgery , St Vincent’s Hospital Sydney, Darlinghurst, New South Wales, Australia
                Author notes
                Correspondence address. Department of Surgery, St Vincent’s Hospital Sydney, 390 Victoria Street, Darlinghurst, New South Wales 2010, Australia. Tel: +61 2 9237 2500; E-mail: jiaxi.li@ 123456svha.org.au
                Article
                Publisher ID: rjac160
                DOI: 10.1093/jscr/rjac160
                PMC ID: 9038225
                PubMed ID: 35481249
                SO-VID: 0b754e15-01ea-4d0a-aa81-aeedb682243c
                Copyright © Published by Oxford University Press and JSCR Publishing Ltd. All rights reserved. © The Author(s) 2022.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Date received : 6 March 2022
                Date accepted : 23 March 2022
                Page count
                Pages: 3
                Categories
                Subject: AcademicSubjects/MED00910
                Subject: jscrep/040
                Subject: Case Report

                Data availability:

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