影像组学列线图在卵巢肿瘤诊断中的应用

Application of radiomics nomogram in diagnosis of ovarian tumors

卵巢肿瘤病理类型繁多,异质性明显。影像学检查为诊断卵巢肿瘤提供了可靠的依据。影像组学在传统影像学技术的基础上,高通量地提取及分析特征,已被用于卵巢肿瘤的诊断、分期、预后分析等方面。列线图模型通过整合多方面的预测因素,量化具体临床事件的风险,被广泛应用于肿瘤学研究。本文就国内外基于影像组学的列线图模型应用于卵巢肿瘤诊断中的研究作一综述,并探讨该技术所面临的挑战及发展前景。

There are many pathological types of ovarian tumors with obvious intratumoral heterogeneity.Various imaging techniques play a crucial part in the diagnosis of ovarian tumors.Radiomics–the high-throughput extraction of large amounts of image features from radiographic images,has been used in the diagnosis,staging and prognostic analysis of ovarian tumors.The nomogram models are widely used in oncology researches by integrating diverse predictors to quantify the risk of specific clinical events.The following is a systematic review of the application of nomogram model based on radiomics in the diagnosis of ovarian tumors at home and abroad,and we discussed the challenge and development prospect of this technique.