
In Scotland, a new robotic-assisted surgical technique is being developed to improve cancer surgical outcomes and patient care.

The robot-assisted surgery technique – developed by the National Robotarium, industry partners and Edinburgh-based clinicians – has been awarded £1.25 million from the Engineering and Physical Sciences Research Council. It will be used during robotic surgery to determine how much of the patient’s tissue is affected by cancer and needs to be removed. The new method will provide surgeons with real-time feedback, allowing for greater precision in distinguishing normal from abnormal tissue.
The outer margin of tissue that the surgeon wishes to remove is called the “surgical margin,” which is identified by the surgeon’s experience, preoperative visual perceptions with imaging and, in open surgery, the tactile “feel.” Another method is to send samples during surgery to the pathology lab for ‘frozen section’, which takes 15-20 minutes. In ‘keyhole surgery’ involving laparoscopic, endoscopic or robotic surgery, surgeons cannot use ‘feel’ to determine tissue characteristics.
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The new collaboration makes it possible to take mechanical measurements in and around the surgical target, which will be interpreted using a series of so-called ‘mechanical intelligence’ algorithms. According to the National Robotarium† the data will give clinicians a clear indication of a tissue’s disease status and determine how much tissue to remove during surgery.
The research team will work with industry partners IntelliPalp Dx and CMR Surgical, along with clinicians working at the Western General Hospital in Edinburgh.
In a statement, study leader Dr Yuhang Chen of the National Robotarium said: “This new technique will provide surgeons with a quantitative, real-time, reliable and evidence-based method to determine the optimal surgical margin to be made when removing a tumor.
“Surgeons operating through a ‘keyhole’ or using techniques for minimally invasive surgery need to identify different structures or diseased areas, even if they are very similar. Our work is focused on identifying the optimal margin in cancer surgery to allow for the removal of a tumor along with enough tissue to ensure complete removal of the cancer, but without wasting excess material.
“We are bringing together expertise from laser manufacturing, fiber optic sensors, micromechanical probing and computer modeling to create a mechanical ‘imaging probe’ that can detect cancerous tissue and can be used with a standard minimally invasive surgical instrument. In conjunction with this, we are building a ‘mechanically intelligent’ data modeling framework and integrating it into the probe operation for tumor identification and assessment of surgical margins. This will effectively eliminate the margin of error for surgeons, giving them confidence that they have removed the correct amount of tissue during the surgery itself and reducing the need for further invasive surgery for patients.”