OPINION

Magnetic resonance imaging for predicting personalized antitumor nanomedicine efficacy

Naumenko VA1, Garanina AS2, Vodopyanov SS1, Nikitin AA1,2, Prelovskaya AO1, Demihov EI4, Abakumov MA1,3, Majouga AM1,2,5, Chekhonin VP3
About authors

1 Laboratory of Biomedical Nanomaterials National University of Science and Technology MISiS, Moscow

2 Research Laboratory of Tissue-Specific Ligands, Faculty of Chemistry Federal State Budget Educational Institution of Higher Education MV Lomonosov Moscow State University, Moscow

3 Pirogov Russian National Research Medical University, Moscow, Russia

4 Lebedev Physical Institute, Russian Academy of Sciences, Moscow

5 Mendeleyev University of Chemical Technology of Russia, Moscow

Correspondence should be adressed: Viktor A. Naumenko
Leninsky 4, Moscow, 119049; moc.liamg@tciv.oknemuan

About paper

Funding: the study was financially supported by the Ministry of Education and Science of the Russian Federation under the Federal Targeted Programme for Research and Development in Priority Areas of Development of the Russian Scientific and Technological Complex for 2014–2020, Agreement #14.575.21.0147 of 27.09.2017 (Agreement ID RFMEFI57517X0147).

Received: 2018-08-30 Accepted: 2018-09-25 Published online: 2018-12-31
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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.

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