Feasibility of Temperature Control by Electrical Impedance Tomography in Hyperthermia

SIMPLE SUMMARY: Online treatment monitoring is an important tool to ensure the safety and effectiveness of hyperthermia cancer therapy. However, current solutions provide only sparse/inaccurate data, demand extensive access to complex and expensive infrastructure, or are associated with increased toxicity. In this study, we present a simulation-based evaluation of the feasibility of electrical impedance tomography (EIT) for hyperthermia treatment monitoring. EIT is a low cost, information-rich, non-invasive technique that could potentially be adapted and employed to reconstruct conductivity changes and translate them to temperature- and perfusion-change maps. Using an innovative reconstruction methodology that leverages (ideally personalized) treatment simulations, physics-motivated constraints, multiple frequencies, measurement-derived compensation, and novel numerical approaches, we investigated the impact of factors such as noise and reference model accuracy on the temperature- and perfusion-reconstruction accuracy. Results suggest that EIT can provide valuable real-time monitoring capabilities. As a next step, experimental confirmation under real-world conditions is needed to validate our results. ABSTRACT: We present a simulation study investigating the feasibility of electrical impedance tomography (EIT) as a low cost, noninvasive technique for hyperthermia (HT) treatment monitoring and adaptation. Temperature rise in tissues leads to perfusion and tissue conductivity changes that can be reconstructed in 3D by EIT to noninvasively map temperature and perfusion. In this study, we developed reconstruction methods and investigated the achievable accuracy of EIT by simulating HT treatmentlike scenarios, using detailed anatomical models with heterogeneous conductivity distributions. The impact of the size and location of the heated region, the voltage measurement signal-to-noise ratio, and the reference model personalization and accuracy were studied. Results showed that by introducing an iterative reconstruction approach, combined with adaptive prior regions and tissue-dependent penalties, planning-based reference models, measurement-based reweighting, and physics-based constraints, it is possible to map conductivity-changes throughout the heated domain, with an accuracy of around 5% and cm-scale spatial resolution. An initial exploration of the use of multifrequency EIT to separate temperature and perfusion effects yielded promising results, indicating that temperature reconstruction accuracy can be in the order of 1 °C. Our results suggest that EIT can provide valuable real-time HT monitoring capabilities. Experimental confirmation in real-world conditions is the next step.