Xu Bai1,2, Qingbo Huang3, Panli Zuo4, Xiaojing Zhang2, Jing Yuan5, Xu Zhang3, Meifeng Wang2, Wei Xu2, Huiyi Ye2, Jinkun Zhao6, Haoran Sun7, Bin Shao8, Haiyi Wang9. 1. Medical School of Chinese PLA, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China. 2. 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 District, Beijing, 100853, China. 6. Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, North of Huanhu West Road Sports Institute, Hexi District, Tianjin, 300060, China. 7. Department of Radiology, Tianjin Medical University General Hospital, No. 154 Anshan Road, Heping District, Tianjin, 300052, China. 8. Department of Radiology, Weihai Central Hospital, No. 3 West Part of Mishan East Road, Wendeng District, Weihai, 264400, Shandong, China. 9. Department of Radiology, First Medical Centre, Chinese PLA General Hospital, No. 28 Fuxing Road, Haidian District, Beijing, 100853, China. wanghaiyi301@outlook.com.
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 SDM-related 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. KEY POINTS: • Radiomics features derived from multiparametric magnetic resonance images showed relevant association with synchronous distant metastasis in clear cell renal cell carcinoma. • MRI radiomics-based nomogram may serve as a potential tool for the risk prediction of synchronous distant metastasis in clear cell renal cell carcinoma.
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 SDM-related 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. KEY POINTS: • Radiomics features derived from multiparametric magnetic resonance images showed relevant association with synchronous distant metastasis in clear cell renal cell carcinoma. • MRI radiomics-based nomogram may serve as a potential tool for the risk prediction of synchronous distant metastasis in clear cell renal cell carcinoma.
Authors: Hugo J W L Aerts; Emmanuel Rios Velazquez; Ralph T H Leijenaar; Chintan Parmar; Patrick Grossmann; Sara Carvalho; Sara Cavalho; Johan Bussink; René Monshouwer; Benjamin Haibe-Kains; Derek Rietveld; Frank Hoebers; Michelle M Rietbergen; C René Leemans; Andre Dekker; John Quackenbush; Robert J Gillies; Philippe Lambin Journal: Nat Commun Date: 2014-06-03 Impact factor: 14.919
Authors: Jinkui Wang; Chenghao Zhanghuang; Xiaojun Tan; Tao Mi; Jiayan Liu; Liming Jin; Mujie Li; Zhaoxia Zhang; Dawei He Journal: Front Public Health Date: 2022-01-28