The objective of this proposed research program is to develop a platform for planning and guidance during Radio Frequency Ablation (RFA). RFA is a thermally mediated ablation technique, where an applicator carrying one electrode is inserted into tumors percutaneously (or via laparoscopy, or open surgical approaches). Radio Frequency (RF) energy is applied, denaturating and coagulating tissues in a volume of 2cm to 5cm of diameter. Some RFA electrodes are shaped as straight needles;others deploy an umbrella of tines to ablate a larger volume. RFA is attractive as it can be used percutaneously resulting minimally invasive. RFA is a widely accepted cancer treatment therapy, and is applied to primary and secondary tumors in different organs, including liver, lung, kidney, breast, and in musculoskeletal interventions. RFA is often the preferred treatment option for inoperable patients. The typical approach for RFA is percutaneous. Physicians therefore have no direct view of the location of electrodes and of tissues. CT and Ultrasound are used intraoperatively to track the location of electrodes, but both CT and Ultrasound (US) have limited ability to visualize the necrotization of tissues under RFA. It is hard therefore to assess which tissues have been treated and which not. Currently physicians rely on "mental maps" of where they have previously ablated tissues and estimate where to go next. The necrotization volume is also "mentally estimated" from lesion geometry charts provided in print by electrode manufacturers. These charts show the expected ablation geometry for a uniform tissue and do not account for the anatomy or the presence of blood vessels, which can modify and reduce the ablation volume as they transport heat away. The overarching goal of this program is to develop a platform for pre-operative planning and intraoperative RFA guidance, based on simulation of the electrical / thermal effects of RFA and real-time intraoperative prediction of necrotization patterns. Image fusion of RFA simulations onto CT intraoperative images would constitute a guidance system able to show which tissues have been treated and which not, allowing the physicians to properly repositions electrodes and achieve consistent overlap. This would improve outcomes of RFA particularly for patients with tumors greater than 4cm, for which total necrotization has been shown to be particularly hard without guidance.
This program aims at developing a platform for intraoperative image guidance during Radio Frequency Ablation (RFA), an ablation technique based on the application of Radio Frequency energy to the tissues by needle electrodes that are inserted into the tumors. In percutaneous interventions it is hard for physicians to estimate which tissues have been treated and which not, as current imaging technologies (CT, Ultrasound) do not show well treated tissues during RFA. We propose to build computer models predicting the ablation geometry and to superimpose them to intraoperative CT images, to guide the intervention and facilitate uniform and complete necrotization of target tissues.