Utilising Artificial Intelligence in Cancer Imaging To Improve Patient Outcomes

Cachexia is a devastating tumour-induced wasting disease affecting 30% of all cancerpatients. This initiative brings together clinical, computational (artifi cial intelligence),and laboratory research partners to work on the delivery of improved outcomes forpatients with cancer cachexia. Aims of the collaboration: Funding will provideopportunities to broaden digital research links and submit joint grant and conjoint PhDproposals.

Long-term objectives:

• 1. Developing non-invasive screening tools for cancercachexia, using AI-assisted imaging analysis approaches.
• 2. Developing a greaterunderstanding of molecular processes of cancer cachexia using animal models andpatient samples.
• 3. Increase knowledge and awareness about cachexia througheducational events for clinicians, patients and families on cachexia diagnosis andtreatment.

This multidisciplinary and diverse initiative builds on the expertise andexisting collaborations between researchers/clinicians across both universities (Bonn/Melbourne). The group consists of experts in radiology/ image analysis (Ko,Attenberger), computational science /AI (Albarqouni) and cancer biology/ metabolism(Cheng). This team of clinicians and researchers with deep knowledge of the fi eld ofcancer cachexia are ideally placed to educate clinicians, patients and families oncachexia and increase its awareness in the general community.

Partners:

• The Sir Peter MacCallum Dept of Oncology, Australia
• Albarqouni Lab, Germany