“Mechanically-intelligent” Intra-operative Tissue Assessment for Robot-Assisted Surgery (MIRAS)

Point of contact: Dr Bill MacPherson

Intra-operational tissue assessment is a key enabling technology for minimally invasive surgery. Surgeons operating along a “keyhole” or similar means of access for minimally invasive surgery need to identify different structures or diseased areas, even when these all may look similar. This work is aimed at identifying the resection margin in cancer surgery, to allow the removal of a tumour together with a margin which is just enough to ensure complete cancer excision, but without unnecessary excess tissue removal. Currently, such a surgical margin is identified using a combination of the surgeon’s experience, images of various kinds taken prior to the operation coupled with any visual observations, or tactile ‘feel’ in the scenario of open surgery, that the surgeon can make during the operation.

Ultimate confirmation of the surgical margin relies on post-operative histopathology, where the removed tissue is assessed microscopically. Only then, will it be known if the removal has been successful or if further surgery and/or more aggressive post-operative treatment is required. These challenges are particularly acute in surgical removal of tumours from within the body.

The development of minimally invasive techniques (such as laparoscopy or operations along body ducts, such as in the rectum or colon) have removed surgical ‘feel’ for tissue characteristics, including assessment of surgical margin. This highlights an unmet clinical need for a quantitative, robust, reliable and evidence-based method of determining the optimal surgical margin and providing feedback to the surgeon in a way that it can be used to make decisions during the operation.

Robot-Assisted Surgery (RAS) is the next development in minimally invasive surgery and has seen rapid development in treatment of a wide variety of conditions. It offers improved clinical accuracy by giving surgeons better control of instruments and providing features such as 3D visualisation. So far, RAS has found limited application in oncological surgery, mostly because current RAS systems rely almost entirely on visual feedback, and do not provide support for clinical decision making. This work aims to provide a novel function in RAS to enhance intra-operative clinical decision making. This technology would accelerate development of RAS in many types of visceral and solid-organ surgery where visual feedback is limited or inadequate to determine surgical margins reliably.

This partnership brings together engineering researchers with two clinical specialisms and is supported by two industries, an SME in the medical sensors area and a manufacturer of surgical robots. The group will focus on two principal aims:

1. to devise a microfabricated probe deployable via a standard minimally invasive surgery instrument capable of making intra-operative mechanical measurements on the tissue surface.
2. to establish data modelling methods in order to process the real-time measurement data to produce quantitative assessment of surgical margin as intra-operative feedback to the surgeon.

This is a 3-year EPSRC funded project with researcher affiliated with: The AOP group and the Institute of Mechanical, Process and Energy Engineering (Heriot-Watt University), Edinburgh Cancer Research Centre and College of Medicine & Vet Medicine (University of Edinburgh). (EP/V047612/1 £1.2 M)

Collaborators: Dr Yuhang Chen (PI), Mr Hugh Paterson (UoE), Prof. Bob Reuben, Mr Daniel Good (UoE), CMR Surgical, and IntelliPalp DX.