CT-based AI framework leveraging multi-scale features for predicting pathological grade and Ki67 index in clear cell renal cell carcinoma: a multicenter study

CT-based AI framework leveraging multi-scale features for predicting pathological grade and Ki67 index in clear cell renal cell carcinoma: a multicenter study

Abstract Purpose To explore whether a CT-based AI framework, leveraging multi-scale features, can offer a non-invasive approach to accurately predict pathological grade and Ki67 index in clear cell renal cell carcinoma (ccRCC). Methods In this multicenter retrospective study, a total of 1073 patholo...

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Bibliographic Details
Main Authors: Huancheng Yang, Yueyue Zhang, Fan Li, Weihao Liu, Haoyang Zeng, Haoyuan Yuan, Zixi Ye, Zexin Huang, Yangguang Yuan, Ye Xiang, Kai Wu, Hanlin Liu
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Insights into Imaging
Subjects:
Clear cell renal cell carcinoma
Machine learning
Ki67
WHO classification
Renal cell carcinoma pathology/grading
Online Access:https://doi.org/10.1186/s13244-025-01980-0
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