Najem Elie J, Shaikh Mohd Javed S, Shinagare Atul B, Krajewski Katherine M
Department of Imaging, Dana-Farber Cancer Institute, Boston, MA, USA.
Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA.
Cancer Imaging. 2025 Feb 18;25(1):16. doi: 10.1186/s40644-025-00835-7.
Research has helped to better understand renal cell carcinoma and enhance management of patients with locally advanced and metastatic disease. More recently, artificial intelligence has emerged as a powerful tool in cancer research, particularly in oncologic imaging. BODY: Despite promising results of artificial intelligence in renal cell carcinoma research, most investigations have focused on localized disease, while relatively fewer studies have targeted advanced and metastatic disease. This paper summarizes major artificial intelligence advances focusing mostly on their potential clinical value from initial staging and identification of high-risk features to predicting response to treatment in advanced renal cell carcinoma, while addressing major limitations in the development of some models and highlighting new avenues for future research.
Artificial intelligence-enabled models have a great potential in improving clinical practice in the diagnosis and management of advanced renal cell carcinoma, particularly when developed from both clinicopathologic and radiologic data.
研究有助于更好地理解肾细胞癌，并改善局部晚期和转移性疾病患者的管理。最近，人工智能已成为癌症研究中的一种强大工具，尤其是在肿瘤影像学方面。
尽管人工智能在肾细胞癌研究中取得了有前景的结果，但大多数研究都集中在局限性疾病上，而针对晚期和转移性疾病的研究相对较少。本文总结了主要的人工智能进展，主要关注其从晚期肾细胞癌的初始分期和高危特征识别到预测治疗反应的潜在临床价值，同时探讨了一些模型开发中的主要局限性，并强调了未来研究的新途径。
基于人工智能的模型在改善晚期肾细胞癌的诊断和管理的临床实践中具有巨大潜力，特别是当从临床病理和放射学数据开发时。
