Prediction of early renal allograft dysfunction using multiparametric magnetic resonance imaging

作者：Ling Zhang, Zhenshan Ding, Pu Xia, Xiuzheng Yue, Yiwei Li, Sophie Zhuang, Sheng Xie · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2025 · DOI：10.21037/qims-24-2182 · 被引用次数：2 · 研究领域：MRI in cancer diagnosis、Renal and Vascular Pathologies、Organ Donation and Transplantation

Background: Multiparametric magnetic resonance imaging (mpMRI) has shown potential as a non-invasive tool for evaluating renal allografts. This study aimed to evaluate whether mpMRI could serve as a biomarker for predicting early renal allograft dysfunction. Methods: -tests, Chi-squared tests, logistic regression, ROC curves, and intraclass correlation coefficients (ICCs) to assess the data. Results: . 98.3±9.7 ms, P=0.01, respectively). The binary logistic regression indicated that the baseline RBF and T1ρ values were significantly correlated with renal function at 3 months after transplantation (P<0.05). The ROC curve analysis revealed areas under the curve (AUCs) of 0.739 for RBF and 0.845 for T1ρ in distinguishing between stable and impaired allograft function. The AUC for the combination of RBF and T1ρ was 0.927, indicating that this combination had the highest performance in predicting early renal allograft dysfunction. Conclusions: This study shows that mpMRI parameters, particularly RBF and T1ρ mapping, have potential as biomarkers for predicting early renal allograft dysfunction.