Navigating advanced renal cell carcinoma in the era of artificial intelligence.

IF 3.5 2区 医学 Q2 ONCOLOGY Cancer Imaging Pub Date : 2025-02-18 DOI:10.1186/s40644-025-00835-7
Elie J Najem, Mohd Javed S Shaikh, Atul B Shinagare, Katherine M Krajewski
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Abstract

Background: 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.

Conclusion: 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.

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人工智能时代的晚期肾细胞癌导航。
背景:研究有助于更好地了解肾细胞癌,并加强对局部晚期和转移性疾病患者的管理。最近,人工智能已经成为癌症研究的有力工具,特别是在肿瘤成像方面。尽管人工智能在肾细胞癌研究中取得了可喜的成果,但大多数研究都集中在局部疾病上,而针对晚期和转移性疾病的研究相对较少。本文总结了人工智能的主要进展,主要集中在其潜在的临床价值,从早期分期和高风险特征识别到预测晚期肾细胞癌的治疗反应,同时指出了一些模型发展的主要局限性,并强调了未来研究的新途径。结论:人工智能支持的模型在改善晚期肾细胞癌的临床诊断和管理方面具有巨大的潜力,特别是当从临床病理和放射学数据中发展时。
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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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