Medical cancer treatments can have serious side effects which under circumstance can be debilitating. When tumour board members discuss possible treatments, they often have to make important decisions with little insight into the extent of such consequences. As a result, patients and physicians have to rely on the personal experience and intuition when selecting between possible (surgical) interventions.

To give evidence-based foundations to such choices, we will construct a personalized, detailed, high resolution functional digital model of each individual patient, a genuine virtual look-alike. This virtual patient will combine data obtained from medical imaging and other biomechanical technologies in one functional model. High quality 3D animations incorporate the anatomy, physiology, and neuron-musculature of the virtual patient.

Physicians will “apply” the curative treatment options to this virtual patient to realize an audiovisual dynamic representation of the functional sequelae of treatment. The virtual patient will simulate the effect on important functions, e.g., mastication, swallowing, and audible speech in head and neck cancer. This gives the tumour board and the patient direct access to the use of a functional predictive tool, to realize evidence based decisions on treatment proposals. Furthermore it enables tailoring of the proposed treatment to the individual patient, to improve functional outcome and decide on additional pre- and post-treatment therapy. It will also clarify the individual functional consequences of the proposed treatment in an audiovisual manner during the counselling procedure.

In ten years, we want to be able to construct a digital model not only for head and neck cancer patients, but for each cancer patient where treatments could impair mechanical functions.

These digital models will store all medical images, physiological data, and all state-of-the-art knowledge of therapy consequences and functional side effects. High quality 3D animations will visualize the likely outcomes of treatments, and their development over time, to the tumour board and patients. Before treatment, these visualizations will guide important decisions about treatment options and selection.