MRI radiomics-based nomogram for individualised prediction of synchronous distant metastasis in patients with clear cell
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IMAGING INFORMATICS AND ARTIFICIAL INTELLIGENCE
MRI radiomics-based nomogram for individualised prediction of synchronous distant metastasis in patients with clear cell renal cell carcinoma Xu Bai 1,2 & Qingbo Huang 3 & Panli Zuo 4 & Xiaojing Zhang 2 & Jing Yuan 5 & Xu Zhang 3 & Meifeng Wang 2 & Wei Xu 2 & Huiyi Ye 2 & Jinkun Zhao 6 & Haoran Sun 7 & Bin Shao 8 & Haiyi Wang 2 Received: 13 March 2020 / Revised: 30 June 2020 / Accepted: 12 August 2020 # European Society of Radiology 2020
Abstract Objective To evaluate the performance of a multiparametric MRI radiomics-based nomogram for the individualised prediction of synchronous distant metastasis (SDM) in patients with clear cell renal cell carcinoma (ccRCC). Methods Two-hundred and one patients (training cohort: n = 126; internal validation cohort: n = 39; external validation cohort: n = 36) with ccRCC were retrospectively enrolled between January 2013 and June 2019. In the training cohort, the optimal MRI radiomics features were selected and combined to calculate the radiomics score (Rad-score). Incorporating Rad-score and SDMrelated clinicoradiologic characteristics, the radiomics-based nomogram was established by multivariable logistic regression analysis, then the performance of the nomogram (discrimination and clinical usefulness) was evaluated and validated subsequently. Moreover, the prediction efficacy for SDM in ccRCC subgroups of different sizes was also assessed. Results Incorporating Rad-score derived from 9 optimal MR radiomics features (age, pseudocapsule and regional lymph node), the radiomics-based nomogram was capable of predicting SDM in the training cohort (area under the ROC curve (AUC) = 0.914) and validated in both the internal and external cohorts (AUC = 0.854 and 0.816, respectively) and also showed a convincing predictive power in ccRCC subgroups of different sizes (≤ 4 cm, AUC = 0.875; 4–7 cm, AUC = 0.891; 7–10 cm, 0.908; > 10 cm, AUC = 0.881). Decision curve analysis indicated that the radiomics-based nomogram is of clinical usefulness. Conclusions The multiparametric MRI radiomics-based nomogram could achieve precise individualised prediction of SDM in patients with ccRCC, potentially improving the management of ccRCC.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00330-020-07184-y) contains supplementary material, which is available to authorized users. * Haiyi Wang [email protected] 1
2
Medical School of Chinese PLA, No. 28 Fuxing Road, Haidian District, Beijing 100853, China Department of Radiology, First Medical Centre, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing 100853, China
3
Department of Urology, First Medical Centre, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing 100853, China
4
Huiying Medical Technology Co. Ltd., Dongsheng Science and Technology Park, Haidian District, Beijing 100192, China
5
Department of Pathology, First Medical Centre, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian Dis
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