• Xiaopan Xu, Xi Zhang, Qiang Tian, Huanjun Wang, Long-Biao Cui, Shurong Li, Xing Tang, Baojuan Li, Jose Dolz, Ismail Ben Ayed, Zhengrong Liang, Jing Yuan, Peng Du, Hongbing Lu, and Yang Liu.
• School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, PR China.
• J Magn Reson Imaging. 2019 May 1; 49 (5): 1489-1498.

BackgroundPreoperative discrimination between nonmuscle-invasive bladder carcinomas (NMIBC) and the muscle-invasive ones (MIBC) is very crucial in the management of patients with bladder cancer (BC).PurposeTo evaluate the discriminative performance of multiparametric MRI radiomics features for precise differentiation of NMIBC from MIBC, preoperatively.Study TypeRetrospective, radiomics.PopulationFifty-four patients with postoperative pathologically proven BC lesions (24 in NMIBC and 30 in MIBC groups) were included.Field Strength/Sequence3.0T MRI/T2 -weighted (T2 W) and multi-b-value diffusion-weighted (DW) sequences.AssessmentA total of 1104 radiomics features were extracted from carcinomatous regions of interest on T2 W and DW images, and the apparent diffusion coefficient maps. Support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were used to construct an optimal discriminative model, and its performance was evaluated and compared with that of using visual diagnoses by experts.Statistical TestsChi-square test and Student's t-test were applied on clinical characteristics to analyze the significant differences between patient groups.ResultsOf the 1104 features, an optimal subset involving 19 features was selected from T2 W and DW sequences, which outperformed the other two subsets selected from T2 W or DW sequence in muscle invasion discrimination. The best performance for the differentiation task was achieved by the SVM-RFE+SMOTE classifier, with averaged sensitivity, specificity, accuracy, and area under the curve of receiver operating characteristic of 92.60%, 100%, 96.30%, and 0.9857, respectively, which outperformed the diagnostic accuracy by experts.Data ConclusionThe proposed radiomics approach has potential for the accurate differentiation of muscle invasion in BC, preoperatively. The optimal feature subset selected from multiparametric MR images demonstrated better performance in identifying muscle invasiveness when compared with that from T2 W sequence or DW sequence only.Level Of Evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1489-1498.© 2018 International Society for Magnetic Resonance in Medicine.

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