Kristian Overduin

Radboudumc

In short, Kristian Overduin's research entails the following:

AI-IMAGINE - Automated Intraoperative assessment of IMAGINg Endpoints for first-time right liver thermal ablation

Thermal ablation is a minimally invasive treatment in early-stage primary and low-volume secondary liver tumors. Compared to surgery, ablation is safer, cheaper and associated with faster recovery, however local recurrence rates tend to be higher, leading to unwanted re-treatments and limiting its use as primary treatment.

Prior studies have demonstrated quantitative 3D treatment margins derived from intraprocedural computed tomography (CT) images to accurately predict the risk of local recurrence after thermal ablation of liver tumors. However, traditional manual image analysis methods to derive the treatment margin are subjective and time-consuming, limiting its generalizability and intra-operative applicability.

The AI-IMAGINE project will investigate AI to develop an automated method for intra-operative evaluation of treatment margins and prediction of treatment success in thermal ablation treatment of liver tumors. This empowers clinicians to better assess treatment success during the actual treatment itself and, in future patients, allow immediate corrective treatment. Hereby, we expect to reduce local recurrence rates and avoid unnecessary re-treatments. Ultimately, we aim at offering patients a minimally invasive treatment that is as effective as surgery, but is safer, cheaper and has less patient impact.

The AI-IMAGINE project is an international collaboration between the Minimally Invasive Image-guided Interventions (MAGIC) and Diagnostic Image Analysis (DIAG) group at Radboudumc and several academic institutions (Leiden UMC, Amsterdam UMC and Medical University Innsbruck, Fraunhofer MEVIS).