Abstract
Ablation therapy is a type of minimally invasive treatment, utilized for various organs including the brain, heart, and kidneys. The accuracy of the ablation process is critically important to avoid both insufficient and excessive ablation, which may result in compromised efficacy or complications. The thermal ablation is formulated by two theoretical models: the heat transfer (HT) and necrosis formation (NF) models. In modern medical practices, feed-forward (FF) and temperature feedback (TFB) controls are primarily used as ablation control methodologies. FF involves pre-therapy procedure planning based on previous experiences and theoretical knowledge without monitoring the intraoperative tissue response, hence, it can't compensate for discrepancies in the assumed HT or NF models. These discrepancies can arise due to individual patient's tissue characteristic differences and specific environmental conditions. Conversely, TFB control is based on the intraoperative temperature profile. It estimates the resulting heat damage based on the monitored temperature distribution and assumed NF model. Therefore, TFB can make necessary adjustments even if there is an error in the assumed HT model. TFB is thus seen as a more robust control method against modeling errors in the HT model. Still, TFB is limited as it assumes a fixed NF model, irrespective of the patient or the ablation technique used. An ideal solution to these limitations would be to actively monitor heat damage to the tissue during the operation and utilize this data to control ablation. This strategy is defined as necrosis feedback (NFB) in this study. Such real-time necrosis monitoring modalities making NFB possible are emerging, however, there is an absence of a generalized study that discusses the integration and quantifies the significance of the real-time necrosis monitor techniques for ablation therapy. Such an investigation is expected to clarify the universal principles of how these techniques would improve ablation therapy. In this study, we examine the potential of NFB in suppressing errors associated with the NF model as NFB is theoretically capable of monitoring and suppressing the errors associated with the NF models in its closed control loop. We simulate and compare the performances of TFB and NFB with artificially generated modeling errors using the finite element method (FEM). The results show that NFB provides more accurate ablation control than TFB when NF-oriented errors are applied, indicating NFB's potential to improve the ablation control accuracy and highlighting the value of the ongoing research to make real-time necrosis monitoring a clinically viable option.