Abstract
Clinical trials are already established for high-temperature treatment of localized cancer, i.e., rise of tissue temperature to more than 55 °C as an effective noninvasive method for the treatment of localized cancer. However, as the computational techniques and capacity have enhanced considerably personalized treatment planning has become a manured tool. In the present investigation, a novel treatment planning framework is being proposed for radio frequency (RF) ablation of cancer tissue based on the tomographic image-based actual model. In patient-specific modeling, different thermal parameters like temperature history during ablation, and thermal damage profile have been virtually determined based on Penne's bioheat transfer model with appropriate boundary conditions. This advancement promises to significantly enhance the capabilities of healthcare practitioners in tailoring personalized treatment strategies for their clinical cases. By leveraging simulation outcomes, clinicians can precisely determine the most effective parameters, such as ablation power and frequency. Unfortunately, the current landscape in India presents a scarcity of specialized medical experts in the field of ablation oncology. Moreover, those who practice in this niche often rely on empirical charts rather than data-driven approaches, highlighting a critical need for increased expertise and the integration of advanced simulation technology to optimize cancer tissue ablation procedures. This real-life patient-specific three-dimensional model-based heat transfer model in a data center-based approach will not only guide the medical practitioner but also a greater number of clinicians can use that. Last but not least, optimizing different operating parameters of RF in this patient-centric approach for accurate treatment has also been discussed.
