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Chemodosimetry of in vivo tumor liposomal drug concentration using MRI
Author(s) -
Viglianti Benjamin L.,
Ponce Ana M.,
Michelich Charles R.,
Yu Daohai,
Abraham Sheela A.,
Sanders Linda,
Yarmolenko Pavel S.,
Schroeder Thies,
MacFall James R.,
Barboriak Daniel P.,
Colvin O. Michael,
Bally Marcel B.,
Dewhirst Mark W.
Publication year - 2006
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.21032
Subject(s) - in vivo , doxorubicin , liposome , drug delivery , drug , perfusion , chemistry , distribution (mathematics) , fibrosarcoma , pharmacokinetics , chemotherapy , biomedical engineering , pharmacology , medicine , pathology , radiology , biology , mathematical analysis , biochemistry , microbiology and biotechnology , mathematics , organic chemistry
Effective cancer chemotherapy depends on the delivery of therapeutic drugs to cancer cells at cytotoxic concentrations. However, physiologic barriers, such as variable vessel permeability, high interstitial fluid pressure, and heterogeneous perfusion, make it difficult to achieve that goal. Efforts to improve drug delivery have been limited by the lack of noninvasive tools to evaluate intratumoral drug concentration and distribution. Here we demonstrate that tumor drug concentration can be measured in vivo using T 1 ‐weighted MRI, following systemic administration of liposomes containing both drug (doxorubicin (DOX)) and contrast agent (manganese (Mn)). Mn and DOX concentrations were calculated using T 1 relaxation times and Mn:DOX loading ratios, as previously described. Two independent validations by high‐performance liquid chromatography (HPLC) and histologic fluorescence in a rat fibrosarcoma (FSA) model indicate a concordant linear relationship between DOX concentrations determined using T 1 and those measured invasively. This method of imaging exhibits potential for real‐time evaluation of chemotherapeutic protocols and prediction of tumor response on an individual patient basis. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.