The GoSmart software environment was originally developed under the European Union’s 7th Framework Programme (No. 600641). Further technical and commercial developments were also part-funded by the European Union’s SME Instrument programme (Grant Agreement No. 868414) under the SIMCARE project.
The main objective of GoSmart is to create an open-end software framework and simulation environment for
Minimally-Invasive Cancer Treatment (MICT).
The software framework will be used by interventional radiologists, researchers and the medical device industry to support the training, planning and the continuous development of simulation-assisted and personalized ablation protocols for different minimally invasive cancer treatments.
Highlights:
There are several methods for image guided percutaneous minimally invasive cancer treatment (MICT) as for example radiofrequency ablation, microwave ablation, cryoablation or irreversible electroporation.
These modalities have many commonalities as well as specific advantages and disadvantages and the choice of the best treatment is challenging as there is a lack of common guidelines for the use of these methods.
GoSmart assists the interventionalist in finding the optimal MICT modality for each patient as it allows to simulate each modality on the patient specific situation using the patient’s anonymized image data and other data from patient’s specific history. Relevant pretreatments to the target tumor as for example transarterial chemoembolization (TACE) can also be taken into account.
But not only the results of simulating different modalities may be compared to each other
Also within one modality several approaches like different needle positions, different equipment or different treatment protocols can be simulated thus indicating an excellent training effect for the interventionalist in planning his treatment.
Furthermore the storage of simulation results of one specific modality or in comparison between different modalities in the database allows a structured scientific evaluation of the treatment results perspectively building the bridge to the establishment of common benchmarks and guidelines for the use of the different MICT modalities.
The different MICT methods are applicable in several organs. Within the GoSmart environment the user is able to simulate MICT in liver, lung and kidney by uploading the patient’s anonymized CT or MRI data and additionally entering data from the patient’s history as for example blood values relevant for the target organ.
Automated algorithms create precise segmentations of the organ and vessel anatomy within few minutes. Afterwards the user segments target tumor either semiautomatic using a seed point based algorithm or manually per “point and click”.
Whenever necessary each segmentation can be easily refined by the user. Multiple different image series of the target organ - even when acquired at different time points (e.g. preop image + image of the real needle position) - can be easily registered together by a simple point based method.
In conclusion a precise 3D model of the target organ including anatomy and the tumor helps the interventionalist to optimally plan the patient’s specific MICT approach.
In GoSmart MICT manufactures can define their own simulation. To do so they define a set of components which are essentially parameter sets. The core components are: