%0 Journal Article %T Computed Tomography Manifestations of Histologic Subtypes of Retroperitoneal Liposarcoma %J Asian Pacific Journal of Cancer Prevention %I West Asia Organization for Cancer Prevention (WAOCP), APOCP's West Asia Chapter. %Z 1513-7368 %D 2014 %\ 12/01/2014 %V 15 %N 15 %P 6041-6046 %! Computed Tomography Manifestations of Histologic Subtypes of Retroperitoneal Liposarcoma %K Retroperitoneal liposarcoma %K histologic subtypes %K Computed Tomography %K retrospective analysis %R %X Objective: Liposarcoma (LPS) is the most common soft tissue sarcoma and accounts for approximately 20% of all mesenchymal malignancies, often occurring in deep soft tissue of retroperitoneal space. Accurate preoperative diagnosis is therefore necessary. We explored whether computed tomography (CT) could be used to differentiate between the various types of retroperitoneal liposarcoma (RPLS). Method: Forty-seven cases of RPLS, diagnosed surgically and histologically, were analyzed retrospectively. CT features were correlatedwith postoperative pathological appearance. Results: The study radiologist identified 29, 11, 2, 2 and 3 RPLS as atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL), dedifferentiated liposarcoma (DDL), myxoid/round cell liposarcoma (ML/RCL), pleomorphic liposarcoma (PL) and mixed-type liposarcoma. Analysis of CT scans revealed the following typical findings of the different subtypes of RPLS: ALT/WDL was mainly visible as a well-delineated fatty hypodense tumor with uniform density and integrity margin; DDL was markedby the combination of focal nodular density and hypervascularity. ML/RCL, PL and mixed liposarcoma showed malignant biological behaviour and CT findings need further studies. Conclusions: CT scanning can reveal important details including internal components, margins and surrounding tissues. Based on CT findings, tumor type can be roughly evaluated and biopsy location and therapeutic scheme guided. %U https://journal.waocp.org/article_29554_3726c9e4d785380a14080029d3e46359.pdf