Exploring Respiratory Motion Tracking Through Electrical Impedance Tomography
Qi Wang, Jianming Wang, Xiuyan Li, Xiaojie Duan, Ronghua Zhang, Hong Zhang, Yanhe Ma, Huaxiang Wang, Jiabin Jia
Abstract
Motion tracking is an effective approach for the management of respiratory motion during the medical imaging process, which has always been a major concern in diagnostic imaging, interventional, and noninvasive therapy. However, the low imaging speed of traditional medical imaging techniques limits the practical application of real-time motion tracking. Electrical impedance tomography (EIT) is proved to be an effective tool for continuous monitoring of lung activity/status. However, the respiratory motion has never been studied in the medical EIT field before. In this article, preliminary research of lung movement during the respiratory process is first studied based on EIT. Multiring electrode thorax models under different respiratory statuses were constructed to obtain simulation data of EIT. A modified TV algorithm is used for the estimation of lung volume and movement based on 3-D EIT images, which improve the quality of reconstruction by approximately 30% and 20% compared with the traditional Tikhonov method and the total variation (TV) method, respectively. Both simulations and experiments were conducted to show the potential of respiratory motion tracking through 3-D EIT reconstruction.