Cervical cancer is the most commonly diagnosed cancer among women. Early diagnosis and prediction will greatly improve the treatment outcome. Many clinical parameters have been used as diagnostic and prognostic factors for cervical cancer patients, including tumor stage, histological type, lymph node status, but with limitations in prediction accuracy. The development of noninvasive biomarker with the potential to provide more specific tumor characterization before treatment begins or during therapy is urgent needed, which may permit clinicians to administer a more individualized anti-cancer treatment. Radiomics is a mathematical-statistical procedure extracting information from medial images, which has the potential for prediction of staging, histological type, node status, relapse and survival in patients with cervical cancer. In this manuscript, we reviewed recent clinical studies and future potential for the application of radiomics in the treatment of patients with cervical cancer, and discussed the current challenges and limitations of radiomics for oncology.

宫颈癌是女性中最常被诊断出的癌症。早期诊断和预测将大大改善治疗效果。许多临床参数已被用作宫颈癌患者的诊断和预后因素，包括肿瘤分期，组织学类型，淋巴结状态，但在预测准确性方面受到限制。迫切需要开发能够在治疗开始之前或治疗期间提供更具体肿瘤特征的非侵入性生物标志物，这可能使临床医生可以进行更具个性化的抗癌治疗。Radiomics是一种从内侧图像中提取信息的数学统计方法，具有预测子宫颈癌患者的分期，组织学类型，淋巴结状态，复发和生存的潜力。在这份手稿中