PhD in AI-based analysis of body composition in breast cancer patients

Breast cancer is the most common cancer in women globally. Rising incidence and improvements in cancer care have contributed to a growing number of breast cancer survivors. As these cancer survivors live longer, and with the majority of the patients being older than 50, they are at higher risk of developing other chronic diseases and conditions, including cardiovascular disease (CVD), neurovascular disease, weight gain, and osteoporosis.

Imaging is an integral part of breast cancer care and follow-up. A large majority of breast cancer patients undergo the acquisition of radiotherapy planning computed tomography (CT) scans. In addition to the requested information about tumor anatomy and location, these scans also contain information on risk factors for other diseases, including high fat and low muscle mass. In daily clinical practice, this potentially valuable but unrequested information is not systematically assessed or reported. However, systematic assessment and reporting of the presence of (risk factors of) chronic conditions on radiotherapy planning CT scans would allow timely identification and treatment of high-risk patients, improving their long-term outcomes and quality of life.

Using radiotherapy planning CT scans, the PhD candidate will develop trustworthy AI systems for automated detection and quantification of the indicators of body composition, such as muscle mass and adipose tissue that are intensively investigated in relation to prognosis in cancer patients.

The PhD project is embedded in the qurAI group at the Department of Biomedical Engineering and Physics and the Department of Radiology.

The qurAI group is an interfaculty, multidisciplinary group between the Department of Biomedical Engineering and Physics of the Amsterdam University Medical Center (AUMC) and the Institute of Informatics of the University of Amsterdam. The qurAI group focuses on the development, validation and clinical integration of AI solutions for data analysis challenges in healthcare. The group aims at designing and enabling socially responsible AI innovations in healthcare.

The project is part of the Horizon Europe-funded ARTILLERY-consortium (Artificial Intelligence for early detection of non-communicable disease risk in people with breast cancer).

The Amsterdam UMC is one of the largest hospitals in the Netherlands and one of the prominent research institutes. The Department of Biomedical Engineering & Physics participates in numerous international research projects and studies.

This PhD project will be embedded in the qurAI group (https://qurai.amsterdam) at the Department of Biomedical Engineering & Physics and Informatics Institute at the University of Amsterdam. Image analysis researchers at the Department of Biomedical Engineering & Physics and qurAI group have ample experience in the development and validation of AI image analysis methods with a strong track record in cardiovascular imaging research.

You will be embedded in the group of PhD students and PostDocs developing AI methods for quantitative analysis of medical images and signals. Moreover, you will closely collaborate with other researchers and clinicians in the project consortium.