Using AI to detect lung cancer recurrence

Lung cancer is the most commonly diagnosed cancer in Canada. While the standard treatment for patients with early-stage lung cancer is surgery, up to half of these patients may develop a recurrence after their treatment. 

Jaryd Christie is a Master’s candidate working with Lawson Scientist, Dr. Sarah Mattonen. Together, they are working to develop a new software that uses artificial intelligence (AI) to identify which patients are likely to have recurring cancer. 

Currently, basic information like the size of the tumour is extracted from medical images such as a computed tomography (CT) scan to determine a patient’s cancer stage and prognosis. With the new technology, multiple sources of information about the patient will be extracted and used to increase accuracy for determining likelihood of recurrence. 

Christie is looking to integrate multi-modal imaging, including CT and positron emission tomography (PET) with a patient’s clinical, pathological and genomic information to build the software. The AI software will find patterns from the data that is extracted and identify imaging features that are associated with recurrence after treatment. 

The goal of this research is to improve the ability to identify which patients are likely to be cured. By being able to extract and combine additional information, physicians could provide aggressive treatment options for patients who need it. This would provide lung cancer patients with personalized treatments that could improve their outcomes. 

“We also want to look not only at the tumour, but other places like bone marrow and non-cancerous areas in the lung, to see if these additional areas can provide information on disease progression and prognosis,” says Christie, who is completing his Master’s degree in the Department of Medical Biophysics at the Schulich School of Medicine & Dentistry at Western University. “We hope that by combining these different sources of information, we can obtain better disease characterization to more accurately determine if a patient will be cured.” 

Christie received a Lawson Internal Research Fund (IRF) Studentship to conduct this research, which will be supervised by Dr. Mattonen.

“Lawson’s IRF is such an important funding opportunity for new investigators. This studentship allows me to support a student while building my research program,” adds Dr. Mattonen. “These funds will allow us to obtain preliminary data that we can use to apply for external funding.”