一种以疾病为中心的癌症精确肿瘤学视觉语言基础模型
A disease-centric vision-language foundation model for precision oncology in kidney cancer.
摘要(中文译文)
肾脏肿物的无创评估仍是泌尿肿瘤学中的关键挑战，诊断不确定性常导致过度治疗。在此，我们开发了RenalCLIP，一种用于肾癌精准肿瘤学的视觉-语言基础模型。利用来自多个中心队列8809例患者的27866次计算机断层扫描，我们采用两阶段预训练策略对齐领域特定的视觉与文本表征。RenalCLIP在涵盖解剖评估、诊断分类和生存预测的十项核心临床任务中实现了更优的性能与泛化能力，显著优于最先进的通用基础模型。此外，RenalCLIP在诊断分类中展现出强大的数据效率，仅使用20%的训练数据即可达到峰值基线性能。该模型还表现出稳健的零样本诊断能力、有效的图文检索以及高质量的医学报告生成。我们的研究结果确立了RenalCLIP作为一种强大、可泛化的工具，可用于提高诊断精度、优化预后分层以及实现肾脏肿物的个性化管理。
Abstract
The non-invasive assessment of renal masses remains a critical challenge in urologic oncology, where diagnostic uncertainty frequently causes overtreatment. Here, we develop RenalCLIP, a vision-language foundation model for precision oncology in kidney cancer. Utilizing 27,866 computed tomography scans from 8809 patients across diverse multi-center cohorts, we employ a two-stage pre-training strategy to align domain-specific visual and textual representations. RenalCLIP achieves enhanced performance and generalizability across ten core clinical tasks, spanning anatomical assessment, diagnostic classification, and survival prediction, significantly outperforming state-of-the-art general-purpose foundation models. Furthermore, RenalCLIP demonstrates strong data efficiency in diagnostic classification, achieving peak baseline performance using only 20% of the training data. The model also exhibits robust zero-shot diagnostic capabilities, effective image-text retrieval, and high-quality medical report generation. Our findings establish RenalCLIP as a powerful, generalizable tool to enhance diagnostic precision, refine prognostic stratification, and personalize the management of renal masses.
如何引用
AMA
Yuhui Tao, Zhongwei Zhao, Zilong Wang, Xufang Luo, Feng Chen, Kang Wang, et al. A disease-centric vision-language foundation model for precision oncology in kidney cancer.. Nature communications. 2026; doi:10.1038/s41467-026-74175-w.
APA
Yuhui Tao, Zhongwei Zhao, Zilong Wang, Xufang Luo, Feng Chen, Kang Wang, et al (2026). A disease-centric vision-language foundation model for precision oncology in kidney cancer.. Nature communications. https://doi.org/10.1038/s41467-026-74175-w
GB/T 7714
Yuhui Tao, Zhongwei Zhao, Zilong Wang, Xufang Luo, Feng Chen, Kang Wang, et al. A disease-centric vision-language foundation model for precision oncology in kidney cancer.[J]. Nature communications, 2026 doi:10.1038/s41467-026-74175-w.
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