Center for Molecular Imaging and Nuclear Medicine, State Key Laboratory of Radiation Medicine and Protection, School for Radiological and Interdisciplinary Sciences (RAD-X), Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Soochow University, Suzhou, 215123, China.
School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, 4072, Australia.
Adv Sci (Weinh). 2024 Oct;11(39):e2405719. doi: 10.1002/advs.202405719. Epub 2024 Aug 20.
The PEGylated ultrasmall iron oxide nanoparticles (PUSIONPs) exhibit longer blood residence time and better biodegradability than conventional gadolinium-based contrast agents (GBCAs), enabling prolonged acquisitions in contrast-enhanced magnetic resonance angiography (CE-MRA) applications. The image quality of CE-MRA is dependent on the contrast agent concentration and the parameters of the pulse sequences. Here, a closed-form mathematical model is demonstrated and validated to automatically optimize the concentration, echo time (TE), repetition time (TR) and flip angle (FA). The pharmacokinetic studies are performed to estimate the dynamic intravascular concentrations within 12 h postinjection, and the adaptive concentration-dependent sequence parameters are determined to achieve optimal signal enhancement during a prolonged measurement window. The presented model is tested on phantom and in vivo rat images acquired from a 3T scanner. Imaging results demonstrate excellent agreement between experimental measurements and theoretical predictions, and the adaptive sequence parameters obtain better signal enhancement than the fixed ones. The low-dose PUSIONPs (0.03 mmol kg and 0.05 mmol kg) give a comparable signal intensity to the high-dose one (0.10 mmol kg) within 2 h postinjection. The presented mathematical model provides guidance for the optimization of the concentration and sequence parameters in PUSIONPs-enhanced MRA, and has great potential for further clinical translation.
聚乙二醇化超小氧化铁纳米颗粒(PUSIONPs)比传统的基于钆的对比剂(GBCAs)具有更长的血液停留时间和更好的生物降解性,能够在对比增强磁共振血管造影(CE-MRA)应用中进行长时间采集。CE-MRA 的图像质量取决于对比剂浓度和脉冲序列的参数。本文展示并验证了一个封闭形式的数学模型,用于自动优化浓度、回波时间(TE)、重复时间(TR)和翻转角(FA)。进行药代动力学研究以估计注射后 12 小时内的血管内动态浓度,并确定自适应浓度依赖性序列参数,以在延长的测量窗口期间实现最佳信号增强。该模型在体模和 3T 扫描仪采集的活体大鼠图像上进行了测试。成像结果表明,实验测量值与理论预测值之间具有极好的一致性,并且自适应序列参数比固定序列参数获得更好的信号增强。低剂量 PUSIONPs(0.03mmol/kg 和 0.05mmol/kg)在注射后 2 小时内提供与高剂量 PUSIONPs(0.10mmol/kg)相当的信号强度。所提出的数学模型为 PUSIONPs 增强 MRA 中浓度和序列参数的优化提供了指导,并且具有进一步临床转化的巨大潜力。