Microwave-induced thermoacoustic tomography: applications and corrections for the effects of acoustic heterogeneities

Abstract

This research is primarily focused on developing potential applications for microwaveinduced thermoacoustic tomography and correcting for image degradations caused by acoustic heterogeneities. Microwave-induced thermoacoustic tomography was first used to verify the feasibility of noninvasively detecting the coagulated damage based on different dielectric properties between normal tissue and lesion treated with high intensity focused ultrasound. Good image contrasts were obtained for the lesions. A comparison of the size of the lesion measured with microwave-induced thermoacoustic tomography and the size measured by a gross pathologic photograph was presented to verify the effectiveness the proposed method. Clinical data for breast tumors were also collected to verify the feasibility of using microwave-induced thermoacoustic tomography in breast cancer imaging. Next, the effects of acoustic heterogeneities on microwave-induced thermoacoustic tomography in weakly refractive medium were investigated. A correction method based on ultrasonic transmission tomography was proposed to correct for the image distortion. Numerical simulations and phantom experiments verify the effectiveness of this correction method. The compensation is important for obtaining higher resolution images of small tumors in acoustically heterogeneous tissues. Finally, the effects of the highly refractive skull on transcranial brain imaging were studied. A numerical method, which considered wave reflection and refraction at the skull surfaces, was proposed to compensate for the image degradation. The results obtained with the proposed model were compared with the results without considering the skull-induced distortion to evaluate the skull-induced effects on the image reconstruction. It was demonstrated by numerical simulations and phantom experiments that the image quality could be improved by incorporating the skull shape and acoustic properties into image reconstruction. This compensation method is important when the thickness of skull cannot be neglected in transcranial brain imaging.