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In Vivo Electrical Conductivity Contrast Imaging in a Mouse Model of Cancer Using High-Frequency Magnetoacoustic Tomography With Magnetic Induction (hfMAT-MI) | IEEE Journals & Magazine | IEEE Xplore

In Vivo Electrical Conductivity Contrast Imaging in a Mouse Model of Cancer Using High-Frequency Magnetoacoustic Tomography With Magnetic Induction (hfMAT-MI)


Abstract:

Cancerous tissues have electrical-conductivity signatures different from normal tissues, which contain potentially useful information for early detection. Despite recent ...Show More

Abstract:

Cancerous tissues have electrical-conductivity signatures different from normal tissues, which contain potentially useful information for early detection. Despite recent advancements in electrical-conductivity imaging and its applications, imaging electrical conductivities with high spatial resolution remains a challenge for non-invasive diagnosis of early-stage cancer. Among the various electrical-conductivity imaging methods, magnetoacoustic tomography with magnetic induction (MAT-MI) is a promising technology for non-invasive detection of breast cancer. However, previous efforts to use MAT-MI for cancer imaging have suffered due to insufficient spatial resolution. In this work, we have developed a high-frequency MAT-MI (hfMAT-MI) system with a 2-D spatial resolution of 1 mm, a significant improvement over previous methods. Furthermore, we demonstrated the performance of this method using an in vivo cancer model in nude mice with human breast xenograft hindlimb tumors. hfMAT-MI was able to resolve not only the boundaries between cancerous and healthy tissues, but also the tumors' internal structures. Importantly, we were able to track a growing tumor using our hfMAT-MI method for the first time in an in vivo mouse model, demonstrating the promise of this magneto-acoustic imaging system for effective detection and diagnosis of early-stage breast cancer.
Published in: IEEE Transactions on Medical Imaging ( Volume: 35, Issue: 10, October 2016)
Page(s): 2301 - 2311
Date of Publication: 28 April 2016

ISSN Information:

PubMed ID: 27834641

Funding Agency:


References

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