The value of clinical parameters combined with magnetic resonance imaging (MRI) features for preoperatively distinguishing different subtypes of uterine sarcomas: An observational study (STROBE compliant). Issue 16 (April 2020)

• Record Type: Journal Article
• Authors: Bi, Qiu; Wu, Kunhua; Lv, Fajin; Xiao, Zhibo; Xiong, Yulin; Shen, Yiqing
• Other Names: Thomas. Michael Albert section editor.
• Is Part Of: Medicine. Volume 99:Issue 16(2020)
• Publication Date: 2020-04
• Subjects: apparent diffusion coefficient -- carcinosarcoma -- endometrial stromal sarcoma -- magnetic resonance imaging -- uterine leiomyosarcoma -- uterine sarcoma; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000019787
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: To investigate clinical parameters combined with magnetic resonance imaging (MRI) features including apparent diffusion coefficient (ADC) values in preoperative identification of different subtypes of uterine sarcomas including uterine leiomyosarcoma (LMS), endometrial stromal sarcoma (ESS), and carcinosarcoma (CS). Data from 71 patients with uterine sarcoma confirmed by surgery and pathology were collected. The clinical characteristics, conventional MRI features, mean ADC values, minimum ADC values, and lesion-muscle ADC ratio (rADC) values were compared with different subtypes of uterine sarcomas. Age, clinical manifestation, tumor location, shape, and T1-weighted image (T1WI) signals were significantly different between CS and LMS or ESS (all P < .01). The presence of band sign was significantly higher in ESS than in LMS or CS (both P < .001). The cystic change or necrosis and enhancement could help to differentiate LMS from ESS or CS (both P < .02). Significant differences were observed in T2-weighted image (T2WI) signals of the solid components of LMS compared with CS ( P < .001). There was a significant difference between ESS and CS in the rADC values ( P = .004). Clinical parameters combined with MRI features could help narrowing preoperative diagnostic possibilities in distinguishing subtypes of uterine sarcomas. These findings may be beneficial in helping guide operative decisions.