Clinical Intervention Modelling, Planning and Proof for Ablation Cancer Treatment

Overview

The main objective of the project is to bring the existing radio frequency ablation (RFA) model for liver cancer treatment (Project IMPPACT, Grant No. 223877, completed in February 2012) into clinical practice. Therefore the project will pursue the following objectives: i) to prove and refine the RFA model in a small clinical study; ii) to develop the model into a real-time patient specific RFA planning and support system for Interventional Radiologists (IR) under special consideration of their clinical workflow needs; iii) to establish a corresponding training procedure for IR's; iv) to evaluate the clinical practicality and benefit of the model for use in the routine workflow in a user survey and expert forum.

This ClinicIMPPACT proposal builds upon the success of the IMPPACT project (Grant No. 223877, completed in February 2012), which created a model for facilitating more accurate RFA treatment. This preliminary RFA model was tested in swine, with extensive histological workup, and in a clinical simulation study based on patient data, both of which reported relatively high correlations between estimated and actual tumor volumes. The mapping software for liver cancer RFA was developed through this project and provides a simulator for radiologists to plan, review and optimize procedures. Within IMPPACT, extensive experiments were performed on pigs and cells to develop a micro-scale cellular death model, which we used for calibrating the software. After porcine liver calibration, eight patient lesions were selected from a database of clinical procedures, and the planning software was used retrospectively to simulate interventions and predict lesion shapes. Predicted volumes were then compared against real thermal lesions, visualized and segmented in contrast-enhanced CT one month after ablation. These comparisons showed simulated and real lesion volumes to be acceptably matched after taking virtual tissue perfusion values into account. Some lesion shapes were mismatched, possibly due to inaccuracies in segmenting radiological images. Treatment with RFA could be improved using a validated software solution to estimate lesion size and identify possible complications in advance-ideally, a solution which is adapted to real-time clinical requirements. However, the current state of the art involves long, hardware-intensive computing time (\~5 hours), which is impractical for clinical use. The main goal of this project is to develop a simulation tool, driven by a user-friendly, ergonomically optimized graphical user interface, to support the complex requirements of clinicians. Therefore, the working steps of this international project and its medical and technical partners are to accelerate simulation speed, optimize needle registration, and integrate patients' individual perfusion values into software calculations, as well as accurate validation techniques, to produce more sophisticated and reliable predictions. The software could also aid in offline planning and simulation and as an RFA teaching tool for radiologists. Its use in retrospective analysis should improve clinical follow up and scientific evaluation.