Smart laparoscopic liver resection: integrated image guidance and tissue discrimination (360G-Wellcome-097911_Z_11_A)

£211,297

Liver cancers can be removed using key-hole surgery with less pain, tissue damage, and blood loss and faster recovery times than traditional open surgery. However few cancers are removed by this method because of the difficulty in identifying and dividing blood vessels within the liver using key-hole surgery techniques. In addition, the position of the tumour and major vessels in the liver alters during the surgery due to patient breathing and liver traction. A research group headed by Professor Brian Davidson and Professor David Hawkes at University College London proposes to use the CT scan taken prior to surgery to identify the precise location of the cancer to the surrounding vessels and bile ducts and hence build a computer model of the liver for each individual patient. They will use this to monitor the position of the cancer and the major structures to the liver during the course of the key-hole surgery. This will be combined with a new method of detecting what kind of tissue is directly in front of the cutting instrument. This system is likely to result in a significant increase in the proportion of patients who undergo liver resection using key-hole surgery. The system will be validated on pigs and then evaluated on at least 25 patients. The system developed will also be applicable to operations on the pancreas, kidney and gallbladder.

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Grant Details

Amount Awarded 211297
Applicant Surname Davidson
Award Date 2015-09-30T00:00:00+00:00
Financial Year 2014/15
Grant Programme: Title Health Innovation Challenge Fund Award
Internal ID 097911/Z/11/A
Lead Applicant Prof Brian Davidson
Other Applicant(s) Dr Adrien Desjardins, Dr Dean Barratt, Prof Danail Stoyanov, Prof David Hawkes, Prof Kurinchi Gurusamy, Prof Stephen Morris
Partnership Value 211297
Planned Dates: End Date 2017-08-07T00:00:00+00:00
Planned Dates: Start Date 2015-11-01T00:00:00+00:00
Recipient Org: Country United Kingdom
Region Greater London