Magnetic resonance imaging for predicting personalized antitumor nanomedicine efficacy

Abstract

Magnetic resonance imaging (MRI) is widely used to diagnose cancer and study patterns and effectiveness of nanocarrier delivery of anticancer drugs. Accumulation of nanoparticles in a tumor varies widely in a given population; it is also highly dependent on biological factors, which remain largely unstudied. In recent years, there was developed a hypothesis that suggests that MRI can be used to predict response to nanoformulations-based anticancer therapy since it provides data on accumulation of MRI contrast agents in the tumor. Pilot tests prove feasibility of the approach based on this hypothesis, however, there is a number of conceptual and technical problems and limitations that hamper its introduction into the routine clinical practice. This article discusses the advantages and disadvantages of methods to stratify tumors by level of nanoparticles accumulation. Further research in this field would facilitate development of effective algorithms of personalized treatment with anticancer drugs delivered by nanoparticles.