This multidisciplinary project involves computer engineering, physics and life sciences. Cancer is the second leading cause of death in the industrialized countries and about 60% of the patients are treated with external beam radiotherapy (RT). Today, RT planning is based on a single computed tomography (CT) data set acquired at the onset of treatment. However, the position and shape of healthy organs, and the morphology and biology of the tumour vary significantly during the weeks of treatment, and tumour definition based on CT has limited accuracy.
These uncertainties are taken into account via generic 'safety' margins around the tumour, which are often too large. Integrating multi-modality images such as CT, MRI and PET acquired several times during treatment and adapting the treatment accordingly will increase the dose to the target and limit the dose to nearby healthy organs. The main bottleneck in multi-modal RT is the substantial increase in data and workload. Organ and target contouring, an essential step in RT, is carried out manually on the computer on each image slice and takes hours per data set.
The project will develop novel automated image segmentation and fusion technology to enable efficient and consistent treatment, and the fellow will get training on the clinical aspects involved. Adaptive RT will improve life for the aging population, with the potential to save a few thousand lives per year. The outgoing host Princess Margaret Hospital, Toronto, Canada, is the leading clinical research centre f or adaptive multi-modal RT and has recently implemented the supporting infrastructure. The return host Philips Research, Hamburg, is one of the leading research groups for image acquisition and processing technology. The researcher will strongly profit fro m the excellent interdisciplinary environment of a world-leading clinical research centre to gain state-of-the-art knowledge in clinical oncology studies.
Call for proposal
See other projects for this call