Radiomics in the era of big data and artificial intelligence:a new paradigm in the diagnosis and treatment of kidney tumor
10.12483/j.issn.1009-8291.2026.03.016
- VernacularTitle:大数据与人工智能背景下的影像组学：肾脏肿瘤精准诊疗新范式
- Author:
Wenbo ZHAI
1
;
Lei PANG
1
Author Information
1. Department of Urology, Shanxi Provincial People's Hospital Affiliated to Shanxi Medical University, Taiyuan 030012, China
- Publication Type:Journal Article
- Keywords:
precision surgery for kidneys;
radiomics;
big data;
artificial intelligence;
surgical decision-making
- From:
Journal of Modern Urology
2026;31(3):288-293
- CountryChina
- Language:Chinese
-
Abstract:
In recent years, the integration of radiomics and artificial intelligence has brought revolutionary breakthroughs to the precise diagnosis and treatment of kidney tumors. This article systematically reviews the latest advances of radiomics in preoperative diagnosis, surgical planning, evaluation of postoperative prognosis, and prediction of treatment responses. Our findings show that radiomics models based on machine learning and deep learning can effectively distinguish benign and malignant kidney tumors, predict pathological classifications and nuclear gradings, and provide anatomical basis for the development of surgical plans. In addition, the rise of radiogenomics has revealed the association between radiomics features and molecular markers, opening up a new direction for the development of non-invasive biomarkers. However, there are still challenges such as insufficient data standardization, small sample size and model interpretability. In the future, multi-center collaboration can be achieved through federated learning, combined with multimodal data to construct dynamic prediction systems and develop interpretable artificial intelligence technology. This will promote the transformation of radiomics from scientific research to clinical applications, thus achieving precision and individualization of the entire process of diagnosis and treatment of renal tumors.
