Wasnik Ashish P, Menias Christine O, Platt Joel F, Lalchandani Usha R, Bedi Deepak G, Elsayes Khaled M
Ashish P Wasnik, Joel F Platt, Department of Radiology, University of Michigan Health System, Ann Arbor, MI 48105, United States.
World J Radiol. 2013 Mar 28;5(3):113-25. doi: 10.4329/wjr.v5.i3.113.
Ovarian cystic masses include a spectrum of benign, borderline and high grade malignant neoplasms. Imaging plays a crucial role in characterization and pretreatment planning of incidentally detected or suspected adnexal masses, as diagnosis of ovarian malignancy at an early stage is correlated with a better prognosis. Knowledge of differential diagnosis, imaging features, management trends and an algorithmic approach of such lesions is important for optimal clinical management. This article illustrates a multi-modality approach in the diagnosis of a spectrum of ovarian cystic masses and also proposes an algorithmic approach for the diagnosis of these lesions.
卵巢囊性肿物包括一系列良性、交界性和高级别恶性肿瘤。影像学在偶然发现或疑似附件肿物的特征性诊断及治疗前规划中起着关键作用，因为早期诊断卵巢恶性肿瘤与更好的预后相关。了解此类病变的鉴别诊断、影像学特征、管理趋势及算法方法对于优化临床管理很重要。本文阐述了一种多模态方法用于诊断一系列卵巢囊性肿物，并提出了一种诊断这些病变的算法方法。
