PhD Defence Karin Olthof | Image-guided navigation in liver surgery

Image-guided navigation in liver surgery

Karin Olthof is a PhD student in the department Temporary - Nanobiophysics. (Co)Promotors are prof.dr. T.J.M. Ruers from the faculty of Science & Technology (TNW, University of Twente. Dr. M. Fusaglia & dr. K.F.D. Kuhlmann from Netherlands Cancer Institute (NKI).

In liver surgery, accurate intraoperative tumor localization and detailed knowledge of patient-specific anatomy are essential to ensure procedural safety and optimal patient outcomes. These requirements become increasingly challenging in the context of parenchyma-sparing strategies, treatment of small or vanishing lesions, and during minimally invasive procedures. Surgical navigation aims to address these challenges by providing the surgeon with a live, virtual representation of the surgical scene, in which tracked instruments are visualized in relation to a patient-specific 3D model of the liver. Despite its clinical promise, broader adoption of surgical navigation remains limited by several technical and practical barriers, including workflow complexity, registration accuracy, and the need for further automation. This thesis aimed to further clinically validate surgical navigation, refine its associated workflows, and extend its application across different surgical indications.

Surgical navigation was clinically evaluated in complex open liver procedures, demonstrating reduced perceived procedural complexity and providing additional intraoperative guidance. The technique enabled accurate localization and treatment of vanishing colorectal liver metastases. Automated segmentation of hepatic anatomy using deep learning substantially reduced the time required to generate patient-specific 3D models. In addition, a novel navigation approach based solely on intraoperative ultrasound imaging was developed to guide liver resection without the need for registration to preoperative imaging. Finally, surgical navigation was translated to minimally invasive liver surgery by integrating augmented reality to support intraoperative orientation and tumor localization. Taken together, these developments advance the integration of surgical liver navigation into routine clinical practice, enabling more precise, image-guided, and patient-specific procedures.