Medical Physics Lunchtime Seminar: Matt Clarkson

Translational Challenges in Image-Guided Laparoscopic Liver Surgery

Abstract:

In the UK approximately 1800 liver resections are performed annually for primary or metastatic cancer. However this is a major global health problem and 150,000 patients per year could benefit from liver resection. Currently only about 10-20% of patients are considered suitable for laparoscopic liver resection, mainly those with small cancers on the periphery of the liver. Larger lesions and those close to major vascular/biliary structures are generally considered high risk for the laparoscopic approach. However, pre-operative imaging modalities such as computed tomography (CT) can clearly identify the location of vessels and tumours. We are developing an image-guidance system to present CT scan data, overlaid onto laparoscopic video, in real time, in order to guide the surgeon and enable safer laparoscopic procedures. In this talk I will describe the system as a whole, give an overview of the development of the project, and present the results to date. With the completion of 2 small clinical studies, with valuable feedback from surgeons, I will present the roadmap ahead as we seek to turn this system into a usable clinical product. 

Bio:

Matt Clarkson is a Lecturer in the Department of Medical Physics and Biomedical Engineering, and a member of the Translational Imaging Group (TIG) within the Centre for Medical Image Computing (CMIC). He holds a BSc in Computer Science from the University of Nottingham and was awarded a PhD from King’s College London in 2000. He then spent 8 years in a variety of commercial programming roles, mainly in the financial sector, before returning to academia in 2008. After a brief spell developing imaging bio-markers for Alzheimer’s disease, Matt was the technical lead for the NifTK programme, developing the infrastructure behind the Smart Liver, EpiNav and MIDAS desktop applications. Since 2012, Matt has led the Smart Liver project, and his research interest are now in image registration, computer vision, augmented reality and image-guided surgery.