Does artificial intelligence enhance physician interpretation of optical coherence tomography: insights from eye tracking
Giacomo Maria Cioffi, Natalia Pinilla‐Echeverri, Tej Sheth, Matthew Sibbald
Abstract
Background and objectives The adoption of optical coherence tomography (OCT) in percutaneous coronary intervention (PCI) is limited by need for real-time image interpretation expertise. Artificial intelligence (AI)-assisted Ultreon™ 2.0 software could address this barrier. We used eye tracking to understand how these software changes impact viewing efficiency and accuracy. Methods Eighteen interventional cardiologists and fellows at McMaster University, Canada, were included in the study and categorized as experienced or inexperienced based on lifetime OCT use. They were tasked with reviewing OCT images from both Ultreon™ 2.0 and AptiVue™ software platforms while their eye movements were recorded. Key metrics, such as time to first fixation on the area of interest, total task time, dwell time (time spent on the area of interest as a proportion of total task time), and interpretation accuracy, were evaluated using a mixed multivariate model. Results Physicians exhibited improved viewing efficiency with Ultreon™ 2.0, characterized by reduced time to first fixation (Ultreon™ 0.9 s vs. AptiVue™ 1.6 s, p = 0.007), reduced total task time (Ultreon™ 10.2 s vs. AptiVue™ 12.6 s, p = 0.006), and increased dwell time in the area of interest (Ultreon™ 58% vs. AptiVue™ 41%, p < 0.001). These effects were similar for experienced and inexperienced physicians. Accuracy of OCT image interpretation was preserved in both groups, with experienced physicians outperforming inexperienced physicians. Discussion Our study demonstrated that AI-enabled Ultreon™ 2.0 software can streamline the image interpretation process and improve viewing efficiency for both inexperienced and experienced physicians. Enhanced viewing efficiency implies reduced cognitive load potentially reducing the barriers for OCT adoption in PCI decision-making.