Reproducibility of an artificial intelligence optical coherence tomography software for tissue characterization: Implications for the design of longitudinal studies

Background To assess the reproducibility of coronary tissue characterization by an Artificial Intelligence Optical Coherence Tomography software (OctPlus, Shanghai Pulse Medical Imaging Technology Inc.). Methods 74 patients presenting with multivessel ST-segment elevation myocardial infarction (STEMI) underwent optical coherence tomography (OCT) of the infarct-related artery at the end of primary percutaneous coronary intervention (PPCI) and during staged PCI (SPCI) within 7 days thereafter in the MATRIX (Minimizing Adverse Hemorrhagic Events by Transradial Access Site and angioX) Treatment-Duration study (ClinicalTrials.gov, NCT01433627). OCT films were run through the OctPlus software. The same region of interest between either side of the stent and the first branch was identified on OCT films for each patient at PPCI and SPCI, thus generating 94 pairs of segments. 42 pairs of segments were re-analyzed for intra-software difference. Five plaque characteristics including cholesterol crystal, fibrous tissue, calcium, lipid, and macrophage content were analyzed for various parameters (span angle, thickness, and area). Results There was no statistically significant inter-catheter (between PPCI and SPCI) or intra-software difference in the mean values of all the parameters. Inter-catheter correlation for area was best seen for calcification [intraclass correlation coefficient (ICC) 0.86], followed by fibrous tissue (ICC 0.87), lipid (ICC 0.62), and macrophage (ICC 0.43). Some of the inter-catheter relative differences for area measurements were large: calcification 9.75 %; cholesterol crystal 74.10 %; fibrous tissue 5.90 %; lipid 4.66 %; and macrophage 1.23 %. By the intra-software measurements, there was an excellent correlation (ICC > 0.9) for all tissue types. The relative differences for area measurements were: calcification 0.64 %; cholesterol crystal 5.34 %; fibrous tissue 0.19 %; lipid 1.07 %; and macrophage 0.60 %. Features of vulnerable plaque, minimum fibrous cap thickness and lipid area showed acceptable reproducibility. Conclusion The present study demonstrates an overall good reproducibility of tissue characterization by the Artificial Intelligence Optical Coherence Tomography software. In future longitudinal studies, investigators may use discretion in selecting the imaging endpoints and sample size, accounting for the observed relative differences in this study.