With this project we aim to reduce the need for surgical biopsies in patients with a brain tumour by developing artificial intelligence (AI) technology to predict diagnosis non-invasively from MRI only: a virtual biopsy. As a PhD student, you will develop and perform an ‘in silico’ trial to compare outcomes of patients who undergo a virtual biopsy versus a conventional surgical biopsy. This is a challenging and multidisciplinary project, bridging technical, biological and clinical disciplines.

This is one of several positions in the Brain Tumour Virtual Biopsy Project, on which 2 PhD students already started in 2023 and a post-doc is being recruited. Together, they work on developing the AI algorithms which provide the virtual biopsy. A first prototype of the algorithm and a large dataset are already available.

At the moment, it would be premature to evaluate the virtual biopsy in a true clinical trial: the results are not yet good enough. However, delaying this assessment until predictions are 100% accurate is also not an option: at that point it would be unethical to subject patients to invasive procedures if non-invasive alternatives are available and sufficient. The question is, however, when such predictions are ‘good enough’. For instance, vulnerable patients in whom tumour biopsy is undesirable could already benefit from imperfect non-invasive diagnostic tools to guide treatment decisions if they are too frail for a surgical biopsy.

By interrogating multidisciplinary teams of clinical experts as well as patients and their loved ones on a variety of – hypothetical but realistic – clinical scenarios, you will gain the required insights into the requirements for acceptance of AI in clinical settings. In an ‘in silico trial’ you will model the outcomes of patients undergoing a – hypothetical – virtual trial versus patients undergoing the conventional surgical trial. These results will eventually pave the way for assessing virtual biopsy in a future true clinical trial.

• You should be an independent and highly motivated researcher with an MSc degree in a health sciences or economics domain (e.g., Health Sciences, Medicine, Econometrics, Economics, Mathematics).
• You should be able to communicate and work with clinicians and patients as well as researchers from various fields.
• Excellent proficiency in English is required and affinity with the Dutch language is preferred.

• You will receive a temporary position for 4 years.
• The gross monthly salary is € 3.017,- in the 1st year and gradually increases to € 3.824,- in the 4th year (scale OIO).
• Excellent fringe benefits, such as a 13th month that is already paid out in November and a individual travel expense package.
• An International Office which aids you in preparing for you arrival and stay.
• Pension insurance with ABP. We take care of approximately 2/3 of the monthly contribution.
• Special benefits, such as a incompany physiotherapist and bicycle repairer. And there is also a gym where you can work on your fitness after work.

Erasmus MC

As a PhD student you will be based both in the department of Radiology & Nuclear Medicine of the Erasmus MC and the department of Health Technology Assessment (HTA) of the Erasmus School of Health Policy & Management (ESHPM; part of the Erasmus University Rotterdam). Both departments have an international character with a good balance between internationally recognised, high-end research and an excellent social working environment. The supervision for the project will be provided by Prof. Marion Smits at Erasmus MC and by Dr. Brenda Leeneman at ESHPM.

The department of Radiology & Nuclear Medicine of the Erasmus MC is one of the largest imaging departments in Europe with 10 clinical MRI scanners at several field strengths and 1 PET-MRI scanner. In Rotterdam, the project is locally embedded in the Neuro-Oncological Imaging group. The HTA department of ESHPM is responsible for research programs in health economics. This includes evaluating the implications of introducing, distributing, and implementing (new) medical technologies, as well as assessing the resulting health benefits.

The project is furthermore performed together with Radboud University Medical Centre (Radboudumc) in Nijmegen, AmsterdamUMC, Delft University of Technology, Leiden University Medical Centre, Memorial Sloan Kettering Cancer Center (New York, USA), and with advisors from University College London (UK).