Magnetic nanoparticles (MNP) enhanced microwave imaging could provide an effective approach for an early stage diagnosis of breast cancer, if encouraging results coming from accurate and realistic numerical studies are confirmed by an experimental proof of concept framework. To this end, an ad hoc laboratory setup has been designed and built up to verify the possibility of detecting the low signal scattered by MNP when embedded into a simplified but realistic breast phantom. This paper describes the developed measurement setup and the results coming from a first run of experiments, which confirm the possibility to detecting realistic amounts of accumulated nanoparticles. Moreover, the experimental results analysis allows addressing the future developments required to determine the ultimate detection limits of the technique, giving relevant information to plan the preclinical assessment.

Experimental framework for magnetic nanoparticles enhanced breast cancer microwave imaging

Borgia, Antonio;Costanzo, Sandra;Di Massa, Giuseppe;
2017-01-01

Abstract

Magnetic nanoparticles (MNP) enhanced microwave imaging could provide an effective approach for an early stage diagnosis of breast cancer, if encouraging results coming from accurate and realistic numerical studies are confirmed by an experimental proof of concept framework. To this end, an ad hoc laboratory setup has been designed and built up to verify the possibility of detecting the low signal scattered by MNP when embedded into a simplified but realistic breast phantom. This paper describes the developed measurement setup and the results coming from a first run of experiments, which confirm the possibility to detecting realistic amounts of accumulated nanoparticles. Moreover, the experimental results analysis allows addressing the future developments required to determine the ultimate detection limits of the technique, giving relevant information to plan the preclinical assessment.
2017
breast cancer; Contrast enhanced microwave imaging; magnetic nanoparticles; Computer Science (all); Materials Science (all); Engineering (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/272268
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