Real-Time Three-Dimensional Microwave Monitoring of Interstitial Thermal Therapy

• Published in: IEEE transactions on biomedical engineering 2018-03, Vol.65 (3), p.528-538
• Main Authors: Chen, Guanbo, Stang, John, Haynes, Mark, Leuthardt, Eric, Moghaddam, Mahta
• Format: Article
• Language: English
• Subjects: Algorithms; Approximation; Background noise; Born approximation; Brain; Brain - diagnostic imaging; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - therapy; Dielectric properties; Dielectrics; Distorted Born; Electric fields; Electrical properties; Finite difference time domain method; Forward problem; Humans; hyperthermia; Hyperthermia, Induced - methods; Image processing; Image reconstruction; Imaging, Three-Dimensional - methods; inverse scattering; Inversions; Iterative methods; Mathematical analysis; Mathematical models; Medical treatment; microstrip patch antennas; Microwave imaging; Microwave theory and techniques; Microwaves; Monitoring; Neuroimaging; Neuroimaging - methods; Noise; Nonlinear Dynamics; Real time; Real-time systems; Temperature effects; Therapy; thermal monitoring; thermal therapy; Time domain analysis; Tissues; Volume integral equations
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2017.2702182

We report a method for real-time threedimensional monitoring of thermal therapy through the use of noncontact microwave imaging. This method is predicated on using microwaves to image changes in the dielectric properties of tissue with changing temperature. Instead of the precomputed linear Born approximation that was used in prior work to speed up the frame-to-frame inversions, here we use the nonlinear distorted Born iterative method (DBIM) to solve the electric volume integral equation (VIE) to image the temperature change. This is made possible by using a recently developed graphic processing unit accelerated conformal finite difference time domain method to solve the forward problem and update the electric field in the monitored region in each DBIM iteration. Compared to our previous work, this approach provides a far superior approximation of the electric field within the VIE, and thus yields a more accurate reconstruction of tissue temperature change. The proposed method is validated using a realistic numerical model of interstitial thermal therapy for a deep-seated brain lesion. With the new DBIM, we reduced the average estimation error of the mean temperature within the region of interest from 2.5° to 1.0° for the noise-free case, and from 2.9° to 1.7° for the 2% background noise case.