| Autor: |
Chaogang Wei, Zhicheng Jin, Qing Ma, Yilin Xu, Ye Zhu, Ying Zeng, Rui Zhang, Yueyue Zhang, Linsen Jiang, Kai Song, Zhen Jiang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
iScience, Vol 27, Iss 8, Pp 110493- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2589-0042 |
| DOI: |
10.1016/j.isci.2024.110493 |
| Popis: |
Summary: 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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