Toronto doctor develops AI prototype to help reduce surgical complications

When Dr. Amin Madani isn't removing burst appendixes or excising cancerous cells from his patients, he's thinking about how to improve the performance of surgeons in the operating room.

That's because up to 25 per cent of the millions of people who undergo inpatientoperations each year around the world experience negative complications either during or after surgery,according to the World Health Organization. These adverse effects can range fromsoreness at the incision siteto internal bleeding to death.

Although not all ofthese adverse events are caused by the actions of surgeons, some are,and Madani a general surgeon with the SprottDepartment of Surgery at the University Health Network (UHN) in Toronto wants to reduce that risk.

He was researching the techniques and thought processes used by the most elite, highest-skilled surgeons, when a group of data and computer scientists suggestedhe could use artificial intelligence (AI) to mimictheir minds.

"I was a big skeptic, actually, for the longest time," Madani said. "That's a big statement to make."

The resulting collaboration produced aprototype that uses computer vision a field of AI that trains computers to interpret and understand images toidentifyin real time areas of an organ that aresafe to dissect, and those where it is dangerous to do so.

WATCH | How artificial intelligenceidentifiessafe dissection areas during gallbladder surgery:

Toronto doctor develops AI prototype to guide surgeons during gallbladder surgery

3 years ago

Duration 2:05

Dr. Amin Madani, a general surgeon with the Sprott Department of Surgery at the University Health Network, developed a prototype that uses artificial intelligence to identify in real time areas where it is safe for a surgeon to dissect, and where it is not.

It's part of a flurry of activity in recent years among researchers, health-care workers and companies who are attempting to harness the power of digital technology to provide better medical care.

Madani's technology is still in theearly stages, and currently only applicable to gallbladder surgeries. But, hesays it has the potential to improve surgery around the world, particularly in rural communities, remote areas and lower-income countries that lack surgical expertise.

Other experts agree, although they say there are still challenges to overcome before its potential can be realized.

How the technology helps guide surgeons

When surgeons performgallbladder removal surgery, they make"keyhole incisions" in the patient's belly area,inserta camera into theabdomen and usespecialized tools to cut away and remove the organ.

Madani's technology projectscoloured areasonto the video monitor the surgeon uses to see inside the patient's body. Green means that area of the organ issafe to cut, red means it's not.

Another variation uses a heatmap-style projection that changes colour based on the model's confidenceas to where thesafearea is.

WATCH | Dr. Amin Madani explains how the prototype could help guide surgeons:

This Toronto doctor is using artificial intelligence to help guide surgeons during gallbladder surgery

3 years ago

Duration 1:22

Dr. Amin Madani, a general surgeon with the Sprott Department of Surgery at the University Health Network, demonstrates how his prototype uses artificial intelligence to help surgeons identify go zones where it is safe to dissect, and no go zones where doing so could be dangerous.

The prototype was developed by feeding hundreds of hours of videos of gallbladder surgeries into a softwareprogram and integrating annotations from expert surgeons identifying where they would dissect. After analyzing the data frame by frame, the algorithm starts to recognizepatterns and develops the ability to make independent decisions.

The algorithm was able to consistently identify"go" and "no-go" zones as well as theliver, gallbladder andhepatocystic triangle with an accuracy ranging from93 to 95 per cent, according to a 2020 study of 290videos from 153 surgeons that was published in the academic journalAnnals of Surgery.Madaniwas the lead author.

"It's like I have a panel of experts standing, watching me over my shoulder, guiding me, navigating me and helping me not get into trouble during that operation,"said Madani.

Dr. Daniel Hashimoto, a surgery instructor at University Hospitals and Case Western Reserve University in Cleveland, Oh.,who collaborated with Madani on the study, said the real promise of the technology lies in its ability to help surgeons better understand what they are perceiving when making surgical decisions.

"The hope is to say, well, can we bring in a second pair of eyes into the operating room in this case, machine eyes toensure the surgeon is seeing what they think they're seeing?" said Hashimoto.

The next question is: will it actually improve the performance of surgeons in the operating room and reduce complications?

That's a difficult question to answer from a research perspective, according to Hashimoto, because clinical trials studying adverse events requirelarge numbers of patients to participate. But Madaniis determined to find out.

His team has already tested the prototype during live surgery to make sure it works properly, and now they are seeking approval from UHN's ethics board to conduct further research.

The AI needs more data, videos

Anotherchallenge lies in expanding the technologyto other surgical procedures.

Gallbladder surgery is one of the most common operations, so it was relatively easy for the researchersto procurevideos of successful surgeries. But tracking down useful videos could become more difficult with less common procedures.

"Most modern machine learning fundamentally depends entirely on the data," saidFrank Rudzicz, a computer science professor at the University of Toronto and an expert in artificial intelligence in health care.

"If it has very few examples of something,it just won't learn the characteristics of that thing, and it'll ... perform very poorly."

WATCH | The challenges of integrating artificial intelligence into healthcare:

Expert discusses the challenges of integrating artificial intelligence into surgery

3 years ago

Duration 0:45

Frank Rudzicz, a computer science professor at the University of Toronto, says one of the challenges with integrating artificial intelligence into surgery is replicating its performance outside the setting where it is tested.

Rudziczsaid another challenge is designing the technology so that it augments the surgeon's performance, without causing a distraction.

"One thing we don't want is the surgeon to be looking at this video and everything's lighting up like a Christmas tree,"Rudziczsaid.

Madani said he's well aware of the need for data and is already in talks with other experts about creating a global repository of surgical videos.

Next, pending research approval, Madani plans to test whether the technology actually improves the performance of other surgeons, thus reducing negative surgical complications.