A new machine-learning analysis revealed that an algorithm can offer a decision on the appropriateness of coronary revascularization during pressure-wire pullback at least as well as expert consensus. The computer was non-inferior to the expert consensus decision for both appropriateness for PCI and for determining PCI strategy.
Dr. Justin Davies, presented the mentioned above findings at TCT 2018 in San Diego, CA, told TCTMD. He said, physicians want to make the right decisions for their patients, and all of our lives are too busy to be experts in every single area; how wonderful is it to essentially have every single time you make a measurement—whether you look at IVUS images, OCT, physiology—to essentially say, well, if you had a group of world experts doing it, how would they do it?”
Davies said his team included 1,008 instantaneous wave-free ratios (iFR) pullback traces, including 317 duplicates, and had both the computer algorithm and a multinational team of expert interventionalists analyze them for appropriateness of PCI and strategy.
Median distal and proximal IFR values were 0.87 and 0.99, respectively, and most vessels were in the left anterior descending artery (79.5%). Almost one-third (31.4%) of vessels had significant pressure-wire drift.
The team found that the computer was non-inferior to the expert consensus decision for both appropriateness for PCI and for determining PCI strategy. While humans tend to change their minds about both PCI appropriateness and strategy in roughly 10 cases, the computers never waver, Davies highlighted. In their analysis, the researchers found that 3.8% of cases where the experts recommended PCI were “actually negative when accounting for wire drift,” he said. Also, “27% of cases determined as nonsignificant for PCI were actually positive.”
Davies also said. “Generally speaking, we should always be very open to different opinions of how to treat patients, and actually most of the problems happen I think when people are not up to date on the latest technology, they’re not using the latest technology in the right way. When you’re very open and receptive to the latest research and technology, I think you probably treat patients better.”
The biggest challenge for these kinds of algorithms moving forward is going to be development, Sardar argued. “The limitation is that right now we don’t have that many specialists in medicine or cardiology who know what these things are and can do studies or trials on these things,” he said. “We need to develop that field. We’re pretty good at devices. We’re pretty good at medicines, trials, and studies. We have so many experts.
But with the new field of artificial intelligence (AI), we don’t have that many experts in medicine and cardiology, so we need that expert who’s going to do studies and trials to show that these things work and that sometimes it can be better than the cardiologist.
Davies J. CEREBRIA-1: machine learning vs expert human opinion to determine physiologically optimized coronary revascularization strategies. Presented at: TCT 2018. September 24, 2018. San Diego, CA.