Scientific and Technological Objectives

Open End Extendable Data and Simulation Model Repository for MICTs

The major challenge of the framework design is to appropriately address the commonalities of the different types of MICT while supporting a flexible structure to allow the incorporation of further MICT modalities, organs, and patient data. On one hand, the framework will allow for the refinement of existing simulation models through model re-learning on a wider patient database to achieve a high level of robustness for MICT simulations. On the other hand, each patient dataset will allow the user to generate an optimal set of patient specific model parameters and MICT protocols.

Multi-Scale Numerical Models for Different Types of MICT

In the Go-Smart open-end environment users will upload new medical data and models, run simulation sessions, and validate simulation results against ground truth medical data. In this way, evolution of the generic simulation tool will be developed that will allow users to work with different types of minimally invasive techniques through exploiting the common physics associated with each procedure. The macro- and micro-scale numerical solvers will be integrated together with a simplified data flow to ensure new tumour cell death models can be easily integrated in future projects. As existing models will be used, we will obtain validation from literature for each of the treatment modules, where the model assumptions, theoretical formulations, data sources and numerical methods are established across all the modules. Simple and easy to use standards will be implemented, which will produce a global standard that can be adopted by scientists, industry and clinicians working in these cancer therapy domains. The simulation environment will apply to different organs such as the liver, prostate, lung and kidney, amongst others.

Unified Image Analysis Software for Workflow Creation and Evaluation

Any MICT simulation relies on a patient specific 3D model reconstruction from image data. The project will develop a generic framework to build patient specific geometries for extremely diverse data (various organs, various image modalities and the specific needs of each type of MICT). Segmentation, registration and meshing modules will rely on generic methods for 3-D model reconstruction. Hence the project will apply modular design and open end implementation to allow the incorporation of further modules and algorithms for different data, organs and treatments. This image-processing application will be unique as it comprises all necessary tools for patient-specific FEM model creation and evaluation of simulation results, into a single software code. This provides a faste and simple workflow for end-users.

Real-Time Multi-Dimensional Visualization

Go-Smart will allow a visual real-time comparison of different MICT simulations in multiple dimensions. Thereby, multiple patient scans with different modalities and at different points of time will be combined with a temporally developing MICT simulation in a multi-dimensional visualization environment. In order to achieve this, direct volume rendering (DVR) algorithms, as normally used for patient scan data (e.g. CT, MRI), will be combined with unstructured grid data, suitable for finite element (FEM) simulations. Combinations like this are completely novel and rarely considered by the scientific community.

Multi-Scale Mesh Refinement for Simulation Results Combined with Flexible User Interfaces

By integrating the simulation, imaging and visualization, Go-Smart will create a clinical framework for IRs, the accessibility of which will depend on a powerful and simple User Interface. IRs are accustomed to a combined 2D/3D representation with a moderate level of complexity, keeping the learning effort low. Scientists however need a flexible visualization environment to experiment with performance and the accuracy of various simulation results. Go-Smart will provide extensions to common medical frameworks with various sets of default parameters which will satisfy both the above requirements. Continuous research on multi-dimensional real-time visualization methods will provide novel representations for combined simulation results and unique user-interfaces.

Standards for MICTs, Medical Data and Instruments:
User-Driven Cross Validation and Benchmarking

The introduction of standards and benchmarks across different MICT is absolutely crucial for selection of the optimal type of MICT for individual patient treatment. Creating a user-driven simulation environment in which new medical data will be added and new medical instruments will be benchmarked will foster the generation of common standards and MICT protocols. This will provide a robust and reproducible information flow to the IRs, but it will also foster valuable feedback from the IRs to support further development of the simulation environment by the researchers. This way both a high level of reproducibility and re-use of the MICT modelling will be established. Any substantive testing of the open software environment has to rely on the independent opinion of external users. Go-Smart will involve usability engineers and web designers for the development of user-friendly intuitive interfaces. By involving the external IRs, model developers and industrial medical partners to take part in open-end trials of the simulation environment Go-Smart will prove the accessibility of the medical data repository and re-use of the simulation models. By this rigorous evaluation the overall framework’s applicability will be ensured. Direct volume rendering (DVR) algorithms, as normally used for patient scan data (e.g. CT, MRI), need to be combined with unstructured grid data, suitable for finite element (FEM) simulations. Combinations like this are completely novel and rarely considered by the scientific community.