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An MRI-based classification scheme to predict passive access of 5 to 50-nm large nanoparticles to tumors

机译:基于MRI的分类方案,可预测5至50 nm大纳米颗粒对肿瘤的被动进入

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Nanoparticles are useful tools in oncology because of their capacity to passively accumulate in tumors in particular via the enhanced permeability and retention (EPR) effect. However, the importance and reliability of this effect remains controversial and quite often unpredictable. In this preclinical study, we used optical imaging to detect the accumulation of three types of fluorescent nanoparticles in eight different subcutaneous and orthotopic tumor models, and dynamic contrast-enhanced and vessel size index Magnetic Resonance Imaging (MRI) to measure the functional parameters of these tumors. The results demonstrate that the permeability and blood volume fraction determined by MRI are useful parameters for predicting the capacity of a tumor to accumulate nanoparticles. Translated to a clinical situation, this strategy could help anticipate the EPR effect of a particular tumor and thus its accessibility to nanomedicines.
机译:纳米粒子是肿瘤学中的有用工具,因为它们具有被动地在肿瘤中蓄积的能力,特别是通过增强的渗透性和保留(EPR)效应。但是,这种效果的重要性和可靠性仍然存在争议,并且常常是不可预测的。在这项临床前研究中,我们使用光学成像技术检测了八种不同的皮下和原位肿瘤模型中三种类型的荧光纳米颗粒的积累,并使用动态对比增强和血管大小指数磁共振成像(MRI)来测量这些功能参数肿瘤。结果表明,由MRI确定的通透性和血容量分数是预测肿瘤积累纳米粒子能力的有用参数。转化为临床情况后,该策略可以帮助预测特定肿瘤的EPR效应,从而有助于其获得纳米药物。

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