Hepatocellular Carcinoma Clinical Trial
Official title:
Clinical Intervention Modelling, Planning and Proof for Ablation Cancer Treatment (ClinicIMPPACT)
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.
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Intervention Model: Single Group Assignment, Masking: Open Label, Primary Purpose: Diagnostic
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