Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
603-03-010 ISMRM Abstract

Machine Learning Based on Multiparametric MRI Radiomic for Pathology Aggressive Prediction in Clear Cell Renal Cell Carcinoma

Primary: Body - Kidney
Secondary: Analysis Methods - Classification and Prediction
603-03-010 · AI for Diagnostic and Prognostic Applications · Thursday, 14 May, 4:00 PM–5:50 PM · Auditorium 1
Keywords: Radiomics Magnetic resonance imaging Renal cell carcinoma Machine learning
Accepted
Jie Zhan 1, Lei Sun2, Enming Cui3, Zhitao Yang1, Jiankun Dai4, Xin Zhen5, Ruimeng Yang1
1Department of Radiology, Guangzhou First People’s Hospital, Guangzhou，Guangdong, China
2Zhujiang Hospital, Southern Medical University, Guangzhou, China
3Department of Radiology, Jiangmen Central Hospital, Jiangmen，Guangdong, China
4MR Research, Beijing, China
5School of Biomedical Engineering, Southern Medical University, Guangzhou，Guangdong, China
Presenting Author: Jie Zhan

Synopsis

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References

1. Rose TL, Kim WY. Renal Cell Carcinoma: A Review. JAMA. 2024;332(12). doi:10.1001/jama.2024.12848. [doi]
2. Ali RM, Muhealdeen DN, Fakhralddin SS, et al. Prognostic factors in renal cell carcinoma: A single‑center study. Molecular and clinical oncology. 2023;19(3):66. doi:10.3892/mco.2023.2662. [doi]
3. Askarpour M, Aminsharifi A. Minimally Invasive Salvage Approaches for Management of Recurrence After Primary Renal Mass Ablation. Cancers. 2025;17(6). doi:10.3390/cancers17060974. [doi]
4. Pierorazio PM, Johnson MH, Patel HD, et al. Management of Renal Masses and Localized Renal Cancer: Systematic Review and Meta-Analysis. Journal of Urology. 2016;196(4):989-99. doi:10.1016/j.juro.2016.04.081. [doi]
5. Pourvaziri A, Mojtahed A, Hahn PF, et al. Renal lesion characterization: clinical utility of single-phase dual-energy CT compared to MRI and dual-phase single-energy CT. European radiology. 2023;33(2):1318-28. doi:10.1007/s00330-022-09106-6. [doi]
6. Wang W, Cao K, Jin S, et al. Differentiation of renal cell carcinoma subtypes through MRI-based radiomics analysis. European radiology. 2020;30(10):5738-47. doi:10.1007/s00330-020-06896-5. [doi]
7. Cui E, Li Z, Ma C, et al. Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics. European radiology. 2020;30(5):2912-21. doi:10.1007/s00330-019-06601-1. [doi]
8. Shimada W, Kimura K, Tanaka H, et al. Significance of tumor shape irregularity: Radiomics analysis based on dynamic computed tomography for predicting pT3a upstaging in cT1b‐2N0M0 renal cell carcinoma. International Journal of Urology. 2022;29(11):1387-9. doi:10.1111/iju.15005. [doi]
9. Tanaka H, Fukuda S, Kimura K, et al. Defining Tumour Shape Irregularity for Preoperative Risk Stratification of Clinically Localised Renal Cell Carcinoma. European urology open science. 2023;48:36-43. doi:10.1016/j.euros.2022.12.003. [doi]

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http://echo.ismrm.org/p/ISMRM2026/603-03-010