Smart Laparoscopic Surgery (Smart Lap)

• Research type

  Research Study

• Full title

  A proof of concept study that uses an AI-based model for visualization of critical structures and blood perfusion guidance in laparoscopic procedures.

• IRAS ID

  331933

• Sponsor organisation

  Imperial College London

• Clinicaltrials.gov Identifier

  23CX8365, DOCUMAS

• Duration of Study in the UK

  1 years, 8 months, 1 days

• Research summary

  The prevalence of gall-stone disease is 10–15% in the UK, EU and US. Laparoscopic cholecystectomy (LC) is the standard procedure to treat gallstones with 61,000 LCs being performed annually in the UK and 600,000 in the US. Common complications of LC include bile leakage (1%), bile duct Injury (0.22%), iatrogenic gallbladder perforation (17–37%) blood vessel injuries (1.22%). These complications lead to life-changing long-term adverse effects for patients, and can be life-threatening, as well as presenting a cost burden due to conversions to open surgery, re-admissions and reoperations.

  Moreover, 16 k [NBOCA, 2019] and 600 k [SAGES, 2015] laparoscopic colorectal
  surgeries are performed annually in the UK and the US, respectively. Anastomotic
  leak complication has been associated with:
  • 19.7% re-admission,
  • 19.3% post-operative infection and
  • 15.9% mortality rate [Wan et al. 2014].

  Complications in laparoscopy are often associated with improper intraoperative visualization. There is an unmet clinical need for better intra-operative visualisation in LC, as verified in our interviews with >20 practicing surgeons across six hospitals. We have developed an algorithm to enable estimation of hyperspectral imaging (images taken at handrends of wavelengths) and visualisation of blood perfusion and oxygen saturation from standard red-green-blue (RGB) images in laparoscopy. This has been tested in vivo in a porcine bowel, where oxygen saturation was visualised with <5% error, enabling the clear visualisation of restricted and unimpeded vessels.

  In this 19-month project, we will apply this algorithm to highlight critical structures (cystic duct and cystic artery) in LC and poor perfusion in colorectal surgery. This will provide the first evidence of this technology’s value in laparoscopy—enabling the surgeon to find the crtical structures at risk and poor perfusion, thus reducing complications and preventing associated costs.

• REC name

  Yorkshire & The Humber - Leeds West Research Ethics Committee

• REC reference

  24/YH/0088

• Date of REC Opinion

  5 Apr 2024

• REC opinion

  Favourable Opinion