The Institute for Cancer Genetics and Informatics receives funding from the Norwegian Cancer Society
Research funding from the Norwegian Cancer Society is raised by the Norwegian public and is an important contribution to Norwegian cancer research environments. The number of applications for the annual call for proposals was again numerous this year, and the competition is strong. Our project aims to use artificial intelligence (AI) to improve risk stratification in patients with colorectal cancer that has spread to the liver. We are grateful that the Norwegian Cancer Society has chosen to support our work and ambitions, which will enable the Institute to continue its work to guide in tailoring treatment options for patients with colorectal cancer.
About the project
An ageing population comes with an increase in cancer incidence. Despite the many advancements in diagnosis, surgical technique, screening, and molecular characterisation, colorectal cancer (CRC) remains a major global health problem, being the second most common cancer and the second most common cause of cancer death in Norway. About 20% of CRC patients are diagnosed with distant metastasis at primary diagnosis, and an additional 25% develop distant metastasis after surgery for localised colorectal cancer. Treatment of colorectal liver metastasis (CLRM) is inconsistent, but resection and chemotherapy are the standard treatment methods in patients who are eligible for surgery. Among patients undergoing liver resection, approximately 40% develop recurrences within one year after surgery, illustrating the need for better tools to identify the proper treatment for each patient.
Artificial intelligence (AI) radically transforms our society, including healthcare and medical diagnostics. Deep learning (DL) is a subfield of AI that is well-suited to perform complex visual recognition tasks and has proven particularly useful in medical image analysis. Based on long-term experience in digital pathology, the Institute for Cancer Genetics and Informatics (ICGI) at Oslo University Hospital has, over the last 8 years, built a competent computing environment for DL in medical image analysis. Deep learning has been used to predict patient outcomes from Whole Slide Images (WSIs) of routine haematoxylin and eosin (H&E)-stained tissue sections from cancers and similar methodology will be utilised in the current project. The project aims to develop deep learning models for predicting recurrence and survival in patients with colorectal liver metastases treated with surgery, to tailor adjuvant treatment and surveillance programmes which in turn will improve survival and quality of life. By linking these predictions with a characterisation of cells and tissue, including morphology and cell types, the project aims to reveal biological mechanisms involved in metastasis and poor patient outcomes. Overall, the project's objectives are to improve risk stratification and identify patients who will benefit from aggressive treatment or those who should not undergo surgery based on their frailty and treatment prospects.