Prostate cancer is the most common cancer in men, but outcomes are poor once it spreads to other parts of the body. While local disease is highly treatable, up to 40% of patients will experience recurrence. Kaylee’s research focuses on improving outcomes for these men by unlocking the information contained in nuclear medicine scans.

Kaylee is investigating whether PET scans at the start of treatment can predict prognosis. By identifying patients at risk of poor outcomes early, doctors can intervene with more aggressive or targeted treatments, potentially improving survival and quality of life. She is also investigating another nuclear medicine modality called a SPECT scan, where patients are injected with a radiopharmaceutical that both targets and destroys cancer cells. Imaging afterwards shows exactly where the drug has travelled in the body, revealing valuable information about tumour behaviour. By developing AI tumour segmentation software, Kaylee aims to extract this additional patient information to predict outcomes and support personalised treatment strategies. This approach could help identify groups of patients with similar characteristics who benefit most from specific therapies.

Kaylee has a background in Software Engineering and Medical Physics, applying computer science and statistical techniques in her research.