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Project Description


ContraCancrum aims to enhance the existing tumour simulators well beyond the state-of-the-art, especially on the biochemical level (molecular dynamics), on the molecular level (detailed molecular networks) and on the cellular and upper biocomplexity levels (angiogenesis, embryology considerations, biomechanics, medical image analysis etc.). More significantly, it will bring together different levels of biocomplexity producing an integrated oncosimulator and validating it on two dedicated clinical studies concerning gliomas and lung cancer. The project will model and simulate cancer/normal tissue behaviour at different levels of biocomplexity, and also model a facet of the systemic circulation via pharmacokinetics and synthesize models of hematological reactions to chemotherapy. The models will be positioned markedly beyond the state of the art of the available models and will be clearly multilevel.

In order to construct multi-level simulation models of tumour growth and tumour and normal tissue response to treatment schemes and schedules Contra Cancrum will:

  • Develop medical image analysis algorithms and software for extracting pathophysiological information from different levels of diagnostic information (e.g. MRI, CT, PET, and ultrasound. Several bio-medical parameters/markers will be tested in order to optimize information extraction from treatment monitoring medical images.
  • Develop macroscopic biomechanical finite element models of the brain and lung to calculate the stress/strain in these tissues. Deformations of both tumour and neighbouring normal tissues will be simulates based on tissue biomechanical properties and detailed anatomic atlases.
  • Deploy two important clinical studies for validating the models, one on lung cancer and one on gliomas. The crucial validation work will be based on comparing the multi-level therapy simulation predictions with the actual medical data (including medical images), acquired before and after therapy. ContraCancrum aims to pave the way for translating clinically validated multilevel cancer models into clinical practice.
  • Create a workflow environment that will allow remote access to clinical data and will assist the end clinical user to validate the cancer models by using its web services. The project will use open-source software that will allow for future extensions of models as well as the extension to large scale clinical trials. Data pseudonymization will ensure adoption of the European legal and ethical data handling guidelines.