• Ping Yin, Ning Mao, Xia Liu, Chao Sun, Sicong Wang, Lei Chen, and Nan Hong.
• Department of Radiology, Peking University People's Hospital, Beijing, P.R. China.
• J Magn Reson Imaging. 2020 Feb 1; 51 (2): 435-445.

BackgroundChondrosarcoma (CS) is the second most common primary malignant bone tumor, with a relatively high recurrence rate. However, an effective method that estimates whether pelvic CS will recur after surgery, which influences the formulation of a clinical treatment plan, remains lacking.PurposeTo develop and validate a clinical radiomics nomograms based on 3D multiparametric magnetic resonance imaging (mpMRI) features and clinical characteristics that could estimate early recurrence (ER) (≤1 year) of pelvic CS.Study TypeRetrospective.PopulationIn all, 103 patients (ER = 41, non-ER = 62) with histologically proven CS were retrospectively analyzed and divided into a training set (n = 72) and a validation set (n = 31).Field Strength/Sequence3.0T axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), diffusion weighted imaging (DWI), contrast-enhanced T1 -weighted (CET1 -w).AssessmentRisk factors (sex, age, type, grade, resection margins, etc.) associated with ER were evaluated. Five individual models based on T1 -w, T2 -w, DWI, CET1 -w, and clinical data were built. Then we compared the performance of models based on T1 -w, T2 -w, CET1 -w and their combination. Lastly, two nomograms based on the best model + clinical data and DWI + clinical data were built.Statistical TestsThe area under the receiver operating characteristic curve (AUC) and accuracy (ACC) were used to evaluate different models.ResultsGrade was the most important univariate clinical predictor of ER of pelvic CS patients (odds ratio [OR]1 = 4.616, OR2 = 8.939, P < 0.05). T1 -w + T2 -w + CET1 -w had a significantly higher performance than CET1 -w in the training set (P = 0.01). Radiomics features are more important than clinical characteristics in clinical radiomics nomograms, especially for multisequence combined features (OR = 3.208, P < 0.01). Clinical radiomics nomogram based on combined features (T1 -w + T2 -w + CET1 -w) + clinical data achieved an AUC of 0.891 and ACC of 0.857, followed by DWI + clinical data (AUC = 0.882, ACC = 0.760) in the validation set.Data ConclusionThe clinical radiomics nomogram had good performance in estimating ER of pelvic CS patients, which would be helpful in clinical decision-making.Level Of Evidence4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:435-445.© 2019 International Society for Magnetic Resonance in Medicine.

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