WelcomeIMPPACT is a European research project, which develops an intervention planning system for Radiofrequency Ablation of malignant liver tumours. TU Graz is dealing with medical visualization and augmented reality in the project.
Problem or ContextRadiofrequency Ablation (RFA) is a minimally invasive form to treat cancer without open surgery, by placing a needle inside the malignancy and destroying it through intensive heating. Though the advantages of this approach are obvious, the intervention is currently hard to plan, almost impossible to monitor or assess, and therefore is not the first choice for treatment.
ProjectIMPPACT will develop a physiological model of the liver and simulate the RFA intervention?s result, accounting for patient specific physiological factors.
- Closing gaps in the understanding of particular aspects of the RFA treatment by multi-scale studies on cells and animals
- Transforming microscopic findings and into macroscopic equations
- Extending the long-established bio-heat equation to incorporate multiple scales
- Validating results at multiple levels
- Cross checking validity for human physiology by comparison to images from ongoing patient treatment
- Visual comparison of simulation and treatment results gathered in animal studies and during patient treatment
- Extensive validation together with a user-centred software design approach guarantee suitability of the solution for clinical practice
Patients can only be examined radiologically and prediction therefore has to rely on macroscopic parameters and tissue properties that can be measured minimally invasive. However, during the heating process microscopic changes at a cellular level affect the end result and should be incorporated the macroscopic equations to allow patient specific prediction. Therefore, both scales are dynamically linked together implying the multi-scale modelling approach to gain iteratively the optimum description. IMPPACT will use several approaches on the macroscopic scale:
- Creation of a complete virtual liver model and simulation of changes in computational results as a function of variations in the complete model. This will investigate the accuracy and tolerance with regards to macroscopic properties such as blood pressure and temperature, but also patient specific tissue properties.
- Visualization of the RFA process subject to variations in the models parameters in the ablation algorithm. By providing visual comparison of the results from RFA simulations one can better investigate the impact of different parameters on the ablation outcome.
- Developing empirical models for different ablations in identical tissue properties as well as across tissue properties.
- Developing a model of cell death due to heating based on existing models of cellular death but adapted specifically for the liver.
- Construct a model of a region of cells: The ?empirical? results obtained from the cellular model yield microscopic behaviour over a larger length scale. Treat the model with different heating rates and doses.
- Incorporate models of the micro- and macro-vasculature into the ?super-cellular? model, to link the behaviour to the blood supply and blood pressure.
Work at TU Graz
Within IMPPACT TU Graz takes the role of visualization and visual computing expert. The following topics are researched:
- Computer Graphics
- Scientific visualization
- Medical visualization
- Volume rendering
- Visualization based macroscopic modelling
- Augmented reality
- Virtual reality interaction for sientific visualization
- Interactive registration refinement
- User-guided image fusion
Expected Results & ImpactsIMPPACT will be modelling a physiological organ including the metabolism and patient specific tissue properties. This alone is a huge step forward as compared to the state-of-the-art intervention planning systems that do not address this issue. IMPPACT will be modelling a physiological organ including the metabolism and patient specific tissue properties. This alone is a huge step forward as compared to the state-of-the-art intervention planning systems that do not address this issue.
The IPS will allow prediction of treatment results on a patient specific base. It will therefore bring down the risk of local recurrences and eliminate the nowadays so common repeated treatments of the same tumour, making RFA an as effective treatment as resection.
At the same time the IPS will make RFA treatment much safer. By reliably predicting tissue heating it will warn of possible damage to surrounding organs in advance and allows choosing a safe needle position and path.
The greatest impact will be achieved by installing the created application in many hospitals in Europe. To be able to directly use the IPS in clinical practice medical personnel in those hospitals needs to be trained in using it. The augmented reality training simulator provides an excellent opportunity as it trains surgeons directly with the IPS
All developed software will be open source and run with common hospital equipment. Its deployment to virtually every hospital in Europe is solely a question of using a deployment infrastructure.