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Image Guided Surgery (IGS) has been successfully utilised when the organ of interest can be reasonably approximated by a rigid body. Commercial IGS systems exist for brain surgery and orthopaedics for example. In areas such as the abdomen, many challenges still remain, as the organs are naturally deformable and undergo deformation due to pneumoperitoneum, breathing and the physical contact of surgical tools.
The Smart Liver Surgery programme has delivered a prototype laparoscopic guidance system to the Royal Free Hospital, and used it on 20+ patients. This system, and that of a current commercial competitor (CASCination AG) still use the rigid body assumption, even with its well-known limitations. The focus of both systems has been to deliver something to the clinic, and establish a working relationship with surgeons.
However, in order to be effective, deformation of the liver must be tackled.
The aim of this project could include:
- Develop a PCA type model of liver to model its natural variation, and investigate its use in statistically based registration of CT to laparoscopic video.
- Investigate Position-Based Dynamics using the NVIDIA Flex library, to model particle based deformations, and assess their suitability for liver surgery.
- Investigate different methods to to estimate biologically plausible deformations of the liver, from mesh deformation to Finite Elements by assuming healthy liver tissue to be homogeneous, isotropic and elastic, as reported in [https://www.ncbi.nlm.nih.gov/pubmed/21811013]
- Collect liver data to inform biomechanical model and to build a database for cancerous liver tissue in order to account for disease and potentially, disease progression.
- The project could be either a comparison of methods, or focussing on a particular approach. A key requirement would be something near real-time, so we could leverage local GPU processing or out-source to Cloud based GPU clusters.
If successful, the project will:
- Deliver a state of the art platform for liver surgery in real time
- Provide a model for image-guided surgery that takes into account liver deformation and is strongly anchored in physical properties of the liver, making the element of interpretation strong.
Supervisors:
Matt Clarkson/Vanessa Diaz
Kurinchi Gurusamy / Brian Davidson