Native T1 mapping-based radiomics diagnosis of kidney function and renal fibrosis in chronic kidney disease

• Published in: iScience 2024-08, Vol.27 (8), p.110493, Article 110493
• Main Authors: Wei, Chaogang, Jin, Zhicheng, Ma, Qing, Xu, Yilin, Zhu, Ye, Zeng, Ying, Zhang, Rui, Zhang, Yueyue, Jiang, Linsen, Song, Kai, Jiang, Zhen
• Format: Article
• Language: English
• Subjects: Bioinformatics; Endocrinology
• ISSN: 2589-0042; 2589-0042
• DOI: 10.1016/j.isci.2024.110493

Chronic kidney disease (CKD) raises major concerns for global public health as it is characterized by high prevalence, low awareness, high healthcare costs, and poor prognosis. Therefore, our study prospectively established and validated native T1 mapping-based radiomics models for the prediction of renal fibrosis and renal function in patients with CKD. Moreover, the area under the receiver operating characteristic curve (AUC) and diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate its performance. Thus, our results show that radiomics based on native T1 mapping images can better identify renal function and renal fibrosis in patients with CKD and outperform conventional T1 mapping parameters of ΔT1 and T1%, thus providing more information for CKD management and clinical decision-making. [Display omitted] •Native T1 mapping-based radiomics models can predict renal fibrosis in CKD patients•Native T1 mapping-based radiomics models can identify renal function in CKD patients•Native T1 mapping-based radiomics outperformed the conventional T1 mapping parameters•Native T1 mapping-based radiomics can provide more information for CKD management Endocrinology; Bioinformatics