Parametrial infiltration (PMI)是分期和规划宫颈癌治疗的必要因素。本研究旨在利用18F-FDG PET/MRI图像的特征，开发一个辐射组学模型，评估IB-IIB宫颈癌患者的PMI。在这项回顾性研究中，对66名FIGO IB-IIB宫颈癌患者（22名有PMI，44名没有PMI）进行18F-FDG PET/MRI扫描，分为训练组（n = 46）和测试组（n = 20）。从18F-FDG PET/MRI的肿瘤和周围组织区域提取特征。以随机森林法开发单模态和多模态辐射组学模型用于预测PMI。使用F1得分，准确度和AUC评估模型性能。使用Kappa检验观察病理结果和基于辐射组学的PMI评估之间的差异。测量从每个ROI提取的特征的内类相关系数。进行三倍交叉验证以确认特征的诊断能力。基于T2加权下的肿瘤和PET周围组织区域的特征开发的单一ROI辐射组学模型（F1分数= 0.400，准确度= 0.700，AUC= 0.708，Kappa = 0.211，P = 0.329）在测试数据集中表现更好；综合应用两种特征得到的模型表现最佳（F1分数= 0.727，准确度= 0.850，AUC= 0.774，Kappa = 0.625，P <0.05）。结果表明，18F-FDG PET/MRI可提供宫颈癌的补充信息。综合应用肿瘤和周围组织区域的特征进行基于辐射组学的评估，可获得更优异的PMI评估性能。本文受版权保护。保留所有权利。

Parametrial infiltration (PMI) is an essential factor in staging and planning treatment of cervical cancer. The purpose of this study was to develop a radiomics model for accessing PMI in patients with IB-IIB cervical cancer using the features from 18 F-FDG PET/MRI images. In this retrospective study, 66 patients with FIGO stage IB-IIB cervical cancer (22 with PMI and 44 without PMI) underwent 18 F-FDG PET/MRI were divided into a training (n = 46) and a testing dataset (n = 20). Features were extracted from both tumoral and peritumoral regions on 18 F-FDG PET/MRI. Single-modality and multi-modality radiomics models were developed with random forest to predict PMI. The performance of models was evaluated with F1 score, accuracy and AUC. Kappa test was used to observe the differences between pathological results and PMI evaluated by radiomics-based models. Intraclass correlation coefficient for features extracted from each ROI was measured. Three-fold cross-validation was conducted to confirm the diagnostic ability of the features. The radiomics models developed by features from primary tumor on T2 weighted (F1 Score = 0.400, accuracy = 0.700, AUC = 0.708, Kappa = 0.211, P = 0.329) and peritumoral region on PET (F1 Score = 0.533, accuracy = 0.650, AUC = 0.714, Kappa = 0.271, P = 0.202) achieved better performances in the testing dataset among four single-ROI radiomics models. The combined model using the features from primary tumor on T2 weighted and peritumoral region on PET achieved the best performance (F1 Score = 0.727, accuracy = 0.850, AUC = 0.774, Kappa = 0.625, P < 0.05). The results suggest that 18 F-FDG PET/MRI could provide complementary information of cervical cancer. The radiomics-based method integrating the features from tumoral and peritumoral regions on 18 F-FDG PET/MRI had a superior performance on PMI evaluation.This article is protected by copyright. All rights reserved.