• Meiling Xiao, Fenghua Ma, Ying Li, Yongai Li, Mengdie Li, Guofu Zhang, and Jinwei Qiang.
• Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China.
• J Magn Reson Imaging. 2020 Sep 1; 52 (3): 885-896.

BackgroundLymph node metastasis (LNM) is a critical risk factor affecting treatment strategy and prognosis in patients with early-stage cervical cancer.PurposeTo establish a multiparametric MRI (mpMRI)-based radiomics nomogram for preoperatively predicting LNM status.Study TypeRetrospective.PopulationAmong 233 consecutive patients, 155 patients were randomly allocated to the primary cohort and 78 patients to the validation cohort.Field StrengthRadiomic features were extracted from a 1.5T mpMRI scan (T1 -weighted imaging [T1 WI], fat-saturated T2 -weighted imaging [FS-T2 WI], contrast-enhanced [CE], diffusion-weighted imaging [DWI], and apparent diffusion coefficient [ADC] maps).AssessmentThe performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The area under the receiver operating characteristics curve (ROC AUC), accuracy, sensitivity, and specificity were also calculated.Statistical TestsThe least absolute shrinkage and selection operator (LASSO) method was used for dimension reduction, feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the radiomics nomogram. An independent sample t-test and chi-squared test were used to compare the differences in continuous and categorical variables, respectively.ResultsThe radiomic signature allowed a good discrimination between the LNM and non-LNM groups, with a C-index of 0.856 (95% confidence interval [CI], 0.794-0.918) in the primary cohort and 0.883 (95% CI, 0.809-0.957) in the validation cohort. Additionally, the radiomics nomogram also had a good discriminating performance and yielded good calibration both in the primary and validation cohorts (C-index, 0.882 [95% CI, 0.827-0.937], C-index, 0.893 [95% CI, 0.822-0.964], respectively). Decision curve analysis demonstrated that the radiomics nomogram was clinically useful.Data ConclusionA radiomics nomogram was developed by incorporating the radiomics signature with the MRI-reported LN status and FIGO stage. This nomogram might be used to facilitate the individualized prediction of LNM in patients with early-stage cervical cancer.Level Of Evidence3 TECHNICAL EFFICACY STAGE: 2 J. Magn. Reson. Imaging 2020;52:885-896.© 2020 International Society for Magnetic Resonance in Medicine.

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