Details of Grant 

EPSRC Reference:	EP/V047612/1
Title:	''Mechanically-intelligent'' Intra-operative Tissue Assessment for Robot-Assisted Surgery (MIRAS)
Principal Investigator:	Chen, Professor Y
Other Investigators:	Good, Mr D W Hand, Professor D Paterson, Mr HM Reuben, Professor RL MacPherson, Dr WN
Researcher Co-Investigators:
Project Partners:	CMR Surgical Limited IntelliPalp DX
Department:	Sch of Engineering and Physical Science
Organisation:	Heriot-Watt University
Scheme:	Standard Research
Starts:	01 March 2022	Ends:	31 January 2026	Value (£):	1,245,293
EPSRC Research Topic Classifications:	Artificial Intelligence Med.Instrument.Device& Equip.
EPSRC Industrial Sector Classifications:	Healthcare
Related Grants:
Panel History:	Panel Date Panel Name Outcome 17 Feb 2021 HIPs 2020 Panel Meeting Announced
Summary on Grant Application Form
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 the rectum and some pelvic organs, where wider surgical excision is constrained by close proximity of anatomical structures with high functional importance, e.g. nerves and vasculature supplying bladder, bowel, sexual organs and lower limbs. 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. Such developments are particularly useful in confined spaces such as the pelvis and rectum. 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 4 distinct and complementary engineering groups 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. The approach will be developed in a staged series of trials, including on ex vivo human tissue and in vivo animal models, with ultimate demonstration in a surgical environment. Through the work, the partnership expects to develop a unique and future-proof 'RAS-made-smarter' technology for applications in intra-operative identification of tumours and tumour margins and, by extension, in other surgical areas.
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Organisation Website:	http://www.hw.ac.uk