Computer Vision News - November 2021

70 What happens is the visual perception illusion. The procedure is guided by 2D or 3D images and the human brain is wired in a way that it tends to see what it expects to see, so if the common bile duct is retracted towards the gallbladder, then the surgeon can think they’re cutting the cystic duct while actually dividing the common bile duct.” This complication happens three times more in minimally invasive surgery than it did in open surgery , where there would be haptic as well as visual feedback. Even though the incidence of this adverse event is low, at between 0.3% and 1.5%, given the high number of procedures performed each year, this translates to a huge number of patients. Patients experiencing a bile duct injury have a three-fold mortality increase at one year. This is devastating for surgeons too and is estimated to cost $1 billion every year in the US alone. “A solution already exists,” Pietro reveals. “In 1995, surgeon Steven Strasberg proposed a secure target identification technique often used in hunting – you don’t shoot an animal before you know for sure it’s an animal. The same type of concept applies in surgery. You don’t clip the cystic duct until you’re sure it’s the cystic duct.” Strasberg called it the critical view of safety (CVS) and it is defined by three anatomical landmarks. However, despite the fact there is a large surgical consensus around it, a recent review found the rate of bile duct injury was not decreasing. The reason for this lies in the fact it is a low-incidence problem, so it tends not to be a priority in the surgeon’s mind when operating. Video-based assessment shows CVS is achieved in only 9-20% of the cases. In 99% of cases, the procedure is still successful, but the error trap lies in the other 1%. Surgeons must perform CVS systematically so that it is there when they need it. “Moving continuously between the clinics and computer science labs has been the most exciting part of the work we’ve been doing,” Pietro tells us . “I must stress the ‘we’ because this is thework of a surgical data science team. On most of my publications I have co- first authors who are engineers and Computer Vision for Medical Imaging