Abstract
Poor penetration of anti-cancer drugs through tumor vasculature and cancer cell membrane as well as slow diffusion of the drugs in the interstitium limit efficacy of cancer chemo- and biotherapy. Recently we proposed to use ultrasound-induced cavitation (formation, growth, and collapse of microbubbles) to enhance anti-cancer drug delivery through these barriers. Cavitation can be selectively induced in tumors by using interaction of ultrasound with nanoparticles that lower cavitation threshold and can be accumulated in tumors. In this paper, we measured cavitation threshold in water suspensions of polymer (polystyrene) nanoparticles and studied efficacy of cancer therapy in nude mice with the use of this technique. Experiments were performed at different irradiation conditions and concentration and size of nanoparticles. In vivo studies were conducted in nude mice bearing human colon (KM20) tumors at optimum conditions found in the experiments in water suspensions. Our studies demonstrated that: (1) polystyrene nanoparticles decrease cavitation threshold in water; and (2) application of this drug delivery technique substantially improve the efficacy of cancer therapy in nude mice when ultrasound was used in combination with polymer nanoparticle injections. Our results suggest that the ultrasound-induced cavitation enhances drug delivery in tumors and may provide efficient cancer chemo- and biotherapy.
Original language | English (US) |
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Pages (from-to) | 492-493 |
Number of pages | 2 |
Journal | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
Volume | 1 |
State | Published - 2002 |
Event | Proceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States Duration: Oct 23 2002 → Oct 26 2002 |
Keywords
- Drug delivery
- Nanoparticle
- Ultrasound
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics