Lee Pei-Hua, Huang Shao Min, Tsai Yi-Ching, Wang Yu-Ting, Chew Fatt Yang
Department of Medical Imaging, China Medical University Hospital, Taichung 404, Taiwan.
Department of Radiology, School of Medicine, China Medical University, Taichung 404, Taiwan.
Int J Mol Sci. 2025 Mar 21;26(7):2869. doi: 10.3390/ijms26072869.
Contrast-induced nephropathy (CIN) represents a significant complication associated with the use of iodinated contrast media (ICM), especially in individuals with preexisting renal impairment. The pathophysiology of CIN encompasses oxidative stress, inflammation, endothelial dysfunction, and hemodynamic disturbances, resulting in acute kidney injury (AKI). Early detection is essential for effective management; however, conventional markers like serum creatinine (sCr) and estimated glomerular filtration rate (eGFR) exhibit limitations in sensitivity and timeliness. This review emphasizes the increasing significance of novel biomarkers in enhancing early detection and risk stratification of contrast-induced nephropathy (CIN). Recent advancements in artificial intelligence and computational analytics have improved the predictive capabilities of these biomarkers, enabling personalized risk assessment and precision medicine strategies. Additionally, we discuss mitigation strategies, including hydration protocols, pharmacological interventions, and procedural modifications, aimed at reducing CIN incidence. Incorporating biomarker-driven assessments into clinical decision-making can enhance patient management and outcomes. Future research must prioritize the standardization of biomarker assays, the validation of predictive models across diverse patient populations, and the exploration of novel therapeutic targets. Utilizing advancements in biomarkers and risk mitigation strategies allows clinicians to improve the safety of contrast-enhanced imaging and reduce the likelihood of renal injury.
对比剂肾病(CIN)是使用碘化对比剂(ICM)相关的一种重要并发症,尤其在已有肾功能损害的个体中。CIN的病理生理学包括氧化应激、炎症、内皮功能障碍和血流动力学紊乱,导致急性肾损伤(AKI)。早期检测对于有效管理至关重要;然而,血清肌酐(sCr)和估算肾小球滤过率(eGFR)等传统标志物在敏感性和及时性方面存在局限性。本综述强调新型生物标志物在加强对比剂肾病(CIN)的早期检测和风险分层方面日益重要。人工智能和计算分析的最新进展提高了这些生物标志物的预测能力,实现了个性化风险评估和精准医学策略。此外,我们讨论了缓解策略,包括水化方案、药物干预和操作改进,旨在降低CIN的发生率。将生物标志物驱动的评估纳入临床决策可以改善患者管理和预后。未来的研究必须优先考虑生物标志物检测的标准化、跨不同患者群体的预测模型的验证以及新型治疗靶点的探索。利用生物标志物和风险缓解策略的进展使临床医生能够提高对比增强成像的安全性并降低肾损伤的可能性。