Department of Radiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, P.R. China.
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China.
J Magn Reson Imaging. 2019 May;49(5):1420-1426. doi: 10.1002/jmri.26531. Epub 2018 Oct 26.
Lymph-vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI.
To develop and validate an axial T contrast-enhanced (CE) MR-based radiomics nomogram that incorporated a radiomics signature and some clinical parameters for predicting LVSI of cervical cancer preoperatively.
Retrospective.
In all, 105 patients were randomly divided into two cohorts at a 2:1 ratio.
FIELD STRENGTH/SEQUENCE: T CE MRI sequences at 1.5T.
Univariate analysis was performed on the radiomics features and clinical parameters. Multivariate analysis was performed to determine the optimal feature subset. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of prediction model and radiomics nomogram.
The Mann-Whitney U-test and the chi-square test were used to evaluate the performance of clinical characteristics and LVSI status by pathology. The minimum-redundancy/maximum-relevance and recursive feature elimination methods were applied to select the features. The radiomics model was constructed using logistic regression.
Three radiomics features and one clinical characteristic were selected. The radiomics nomogram showed favorable discrimination between LVSI and non-LVSI groups. The AUC was 0.754 (95% confidence interval [CI], 0.6326-0.8745) in the training cohort and 0.727 (95% CI, 0.5449-0.9097) in the validation cohort. The specificity and sensitivity were 0.756 and 0.828 in the training cohort and 0.773 and 0.692 in the validation cohort.
T CE MR-based radiomics nomogram serves as a noninvasive biomarker in the prediction of LVSI in patients with cervical cancer preoperatively.
4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1420-1426.
淋巴血管空间侵犯（LVSI）是宫颈癌的一个不利预后因素。不幸的是，目前还没有用于术前预测 LVSI 的临床工具。
开发和验证一种基于轴位 T 对比增强（CE）MR 的放射组学列线图，该列线图结合了放射组学特征和一些临床参数，用于术前预测宫颈癌的 LVSI。
回顾性。
总共，105 名患者以 2:1 的比例随机分为两组。
磁场强度/序列：1.5T 的 T CE MRI 序列。
对放射组学特征和临床参数进行单变量分析。进行多变量分析以确定最佳特征子集。通过接收者操作特征（ROC）分析评估预测模型和放射组学列线图的性能。
Mann-Whitney U 检验和卡方检验用于评估临床特征和病理 LVSI 状态的性能。应用最小冗余/最大相关性和递归特征消除方法来选择特征。使用逻辑回归构建放射组学模型。
选择了三个放射组学特征和一个临床特征。放射组学列线图显示出区分 LVSI 和非 LVSI 组的良好能力。在训练队列中的 AUC 为 0.754（95%置信区间[CI]，0.6326-0.8745），在验证队列中的 AUC 为 0.727（95%CI，0.5449-0.9097）。在训练队列中的特异性和敏感性分别为 0.756 和 0.828，在验证队列中的特异性和敏感性分别为 0.773 和 0.692。
基于 T CE MR 的放射组学列线图可作为预测宫颈癌患者术前 LVSI 的非侵入性生物标志物。
4 技术功效：第 2 阶段 J. Magn. Reson. Imaging 2019;49:1420-1426。
