Jul 1, 2021
Feasibility of Temperature Control by Electrical Impedance Tomography in Hyperthermia
Redi Poni, Esra Neufeld, Myles Capstick, Stephan Bodis, Theodoros Samaras, and Niels Kuster, Cancers, Volume 13, Issue 13, Article No. 3297, online 30 June 2021; doi: 10.3390/cancers13133297
We present a simulation study in which the feasibility of electrical impedance tomography (EIT) is investigated 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-treatment-like 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 show that, introduction of an iterative reconstruction approach combined with adaptive prior regions and tissue-dependent penalties, planning-based reference models, measurement-based reweighting, and physics-based constraints, makes it possible to map conductivity-changes throughout the heated domain with an accuracy of within about 5% and with 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 on 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.
The scientific and technical impact of the study can be summarized as:
- EIT is a potential non-invasive and low-cost method to provide conductivity reconstruction that can be translated to temperature- and perfusion-change maps in HT treatments
- The Duke and Glenn anatomical models of the Virtual Population with highly heterogeneous tissues and complex geometries were used in the investigation of simulated HT treatments
- Critical aspects that influence the accuracy of conductivity reconstruction were identified as the volume of heating, the signal-to-noise ratio of the measurement voltages, and the accuracy of the patient model implemented
- The use of prior information from HT treatment planning allows the accuracy of the conductivity reconstruction to be enhanced, making treatment monitoring feasible
