CNN-based tumor progression prediction after thermal ablation with CT imaging
In person: 23 February 2022 • 5:30 PM - 7:00 PM PST
For patients with advanced colorectal cancer, liver metastasis is the most common kind of distant spread. Resection of the metastasis is often not possible due to tumor size and location. As a result thermal ablation is now part of international guidelines. However, a significant number of patients experience regrowth. This is currently only identified 4 months after treatment (at the earliest). We have trained a CNN model that can predict regrowth using CT scans at baseline and directly after ablation therapy, which achieves an area under the receiver operating characteristic curve of 0.72 from a dataset containing 120 lesions.
The Netherlands Cancer Institute (Netherlands)
Postdoctoral researcher at the Netherlands Cancer Institute with a focus on AI development for treatment response prediction using clinical imaging. Sean is a particle physicist by training with more than 8 years of experience as part of an LHC collaboration where he developed AI models to process multi-modal detector data. Sean developed explainable AI models and data platforms as a Senior Data Scientist with the Advanced Analytics and Big Data team of KPMG before moving to work at the Netherlands Cancer Insititute in 2020.