Feasibility analysis of EIT-guided lung tumor tracking with prior information for robotic arm-assisted radiotherapy

Lung cancer remains one of the most prevalent and lethal forms of cancer worldwide. Radiotherapy is an effective therapeutic strategy for its management, where precise tumor localization plays a pivotal role in ensuring treatment accuracy and efficacy. Electrical Impedance Tomography (EIT), a non-invasive and cost-effective imaging technique with a high temporal resolution, shows promise for tissue abnormality detection by exploiting the inherent differences in electrical properties among biological tissues. In this study, we propose a method that combines EIT with prior information from X-ray Computed Tomography (XCT) to determine tumor position. The integrated localization data are then transferblack to a robotic arm, which uses this information to accurately guide radiotherapy procedures. The detailed system design of the EIT-guided robotic arm for radiotherapy is presented. Additionally, both simulations and water tank experiments are conducted to validate the feasibility of this approach. The results demonstrate the potential of integrating EIT with XCT and robotic systems for tumor localization and targeted radiotherapy, thereby broadening the clinical applications of EIT in the medical field.