卵巢癌是最恶性的妇科疾病,病死率极高,其明确诊断对治疗和预后意义重大。不同扩散模型能够无创地通过一系列定量参数为临床提供更多信息,从而提高卵巢肿瘤诊断的准确性。影像组学是人工智能的一种方法,能够更全面、客观地揭示病变的内在异质性,在肿瘤检测、初级分期、治疗计划、预后预测以及反应评估方面具有良好的应用前景。本文综述了不同扩散模型及影像组学在卵巢肿瘤中的研究进展。

Ovarian cancer is the most malignant gynecological disease, the mortality is extremely high, its definite diagnosis is of great significance to the treatment and prognosis. Different diffusion models can provide more information for clinic noninvasively through a series of quantitative parameters, thus improving the accuracy of ovarian tumor diagnosis. imaging is a method of artificial intelligence, which can reveal the intrinsic heterogeneity of lesions more comprehensively and objectively, and has a good application prospect in tumor detection, primary stage, treatment plan, prognosis prediction and response evaluation. This article reviews the progress of different diffusion models and imaging in ovarian tumors.

内蒙古医科大学“科技百万工程”项目,编号：YKD2016KJBW(LH)004 ,吴慧,牛广明,钱洛丹,蔚纳