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Magnetic Targeting Enhanced Theranostic Strategy Based on Multimodal Imaging for Selective Ablation of Cancer
Author(s) -
Li Zhiwei,
Yin Shengnan,
Cheng Liang,
Yang Kai,
Li Yonggang,
Liu Zhuang
Publication year - 2014
Publication title -
advanced functional materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.069
H-Index - 322
eISSN - 1616-3028
pISSN - 1616-301X
DOI - 10.1002/adfm.201303345
Subject(s) - photothermal therapy , materials science , nanomedicine , photoacoustic imaging in biomedicine , magnetic resonance imaging , nanotechnology , tumor ablation , nanoparticle , biomedical engineering , cancer imaging , cancer , ablation , medicine , radiology , optics , physics
The booming development of nanomedicine offers great opportunities for cancer diagnostics and therapeutics. Herein, a magnetic targeting‐enhanced cancer theranostic strategy using a multifunctional magnetic‐plasmonic nano‐agent is developed, and a highly effective in vivo tumor photothermal therapy, which is carefully planed based on magnetic resonance (MR)/photoacoustic (PA) multimodal imaging, is realized. By applying an external magnetic field (MF) focused on the targeted tumor, a magnetic targeting mediated enhanced permeability and retention (MT‐EPR) effect is observed. While MR scanning provides tumor localization and reveals time‐dependent tumor homing of nanoparticles for therapeutic planning, photoacoustic imaging with higher spatial resolution allows noninvasive fine tumor margin delineation and vivid visualization of three dimensional distributions of theranostic nanoparticles inside the tumor. Utilizing the near‐infrared (NIR) plasmonic absorbance of those nanoparticles, selective photothermal tumor ablation, whose efficacy is predicted by real‐time infrared thermal imaging intra‐therapeutically, is carried out and then monitored by MR imaging for post‐treatment prognosis. Overall, this study illustrates the concept of imaging‐guided MF‐targeted photothermal therapy based on a multifunctional nano‐agent, aiming at optimizing therapeutic planning to achieve the most efficient cancer therapy.