Radboudumc collaborates with the UMC Groningen and the NKI-AVL to investigate cardiac toxicity associated with radiotherapy for lung cancer patients. In the past years, there is increased awareness that cardiac toxicity is or will be relevant for the treatment of lung cancer, however, no adequate models are available that predict cardiac toxicity. In the project, you will develop such models using data from 6 institutes adding to a total of 4000 patients. You will analyze the data using advanced techniques such as Deep Learning, and use different Machine Learning techniques to automatically detect abnormalities and learn from the data. The aim of the project is to construct and validate robust prediction models that calculate the risk of cardiac toxicity, radiation pneumonitis and survival

Project
One of the reasons that robust dose-effect relationships of the heart have not yet been established is due to the use of relatively small cohorts, and the cumbersome and time consuming nature of manual delineation of the heart. Therefore, the first step within the project is to optimize automatic heart delineation, to optimize and validate the method published by our collaborators at the NKI and to compare the performance with state-of-the-art deep learning models to further improve the methodology.

As a second step, these results will be applied to generate and validate algorithms that enable the automatic detection of radiotherapy induced toxicity (pericarditis and pneumonitis), based on imaging before and after treatment.

Finally, machine learning techniques will be used to create prediction models. This study will be performed in close collaboration with 6 institutes. The project will help to allocate the appropriate treatment and optimize radiotherapy for the individual patient and results in implementation into daily clinical practice.

Tasks and responsibilities
You will be part of a research project funded by the Radboudumc, and as a member of the Radboud Institute of Health Siences (RIHS) be stationed at the Radiotherapy department. You will collaborate closely with the image analysis group of the departement of Radiology (DIAG). Your responsibilities will consist of :

• The acquisition of the large multi-institutional cohort, this will involve site visits in the US, Germany and the Netherlands;
• Using existing software and developing new software to automatically delineate relevant structures in CT and automatically asses induced toxicity of the CT's available in the cohort;
• Using machine learning techniques to create prediction models;
• Of all the above projects you write scientific papers that will be submitted to peer reviewed papers;
• Within 4 years you will finish writing a thesis for your promotion according to rules of the Radboud university.

You have a MSc degree in physics, computer science, mathematics, biomedical engineering, technical medicine or a comparable degree. Preferably you are experienced in programming. Prior knowledge of image analysis and statistical techniques such as machine learning is desirable. You are attracted to working on clinical problems and you like working in a multidisciplinary team.

You will be stationed in the Radboudumc, deptartement of Radiotherapy. The project will performed in close collaboration with the image analysis group of the department of Radiology (DIAG), the department of radiation oncology of the Netherlands Cancer Institute and the department of radiation oncology of the UMCG.

Upon commencement of employment we require a certificate of conduct (Verklaring Omtrent het Gedrag, VOG) and there will be a screening based on the provided CV. Radboud university medical center's HR Department will apply for this certificate on your behalf.

Read more about the Radboudumc employment conditions and what our International Office can do for you when moving to the Netherlands.

Radboudumc

The department of Radiotherapy at the Radboudumc has seven linear accelerators, one brachytherapy facility and treats close to 2500 patients per year. The department has a clinical focus on Head and Neck, Prostate and Lung cancer. The research at the department focuses on radiobiology, predictive modeling & radiomics and tumor immunology.

Radboudumc
Radboudumc strives to be a leading developer of sustainable, innovative and affordable healthcare to improve the health and wellbeing of people and society in the Netherlands and beyond. This is the core of our mission: To have a significant impact on healthcare. To get a better picture of what this entails, check out our strategy.

Read more about what it means to work at Radboudumc and how you can do your part.