Preliminary observations using optical coherence tomography to assess neointimal coverage of a metal stent in a porcine model.
BACKGROUND: Concerns surrounding late stent thrombosis have prompted the development of novel imaging techniques to assess neointimal coverage. Recent clinical studies have evaluated optical coherence tomography (OCT) to evaluate neointimal coverage, but pathologic correlation in an animal model is lacking. We assessed the hypothesis that OCT could accurately assess early neointimal coverage in a porcine model. METHODS: OCT imaging of bare metal stents in each coronary artery was performed at implantation (n=6), Day 4 (n=3), and Day 20 (n=3), and images were evaluated at three cross-sections per stented segment. Neointimal strut coverage was categorized by OCT as covered or uncovered, and neointimal thickness was determined (Day 20). Pathological correlation was obtained using scanning electron microscopy (SEM) to assess strut coverage (Day 4) and histomorphometry to quantify neointimal thickness (Day 20). RESULTS: At Day 4, OCT imaging detected 28 (26%) of 109 uncovered struts, and the ratio of uncovered/total strut area by SEM was 31%. All imaging modalities showed complete coverage at Day 20. Mean (+/-SE) neointimal thickness at Day 20 was 109+/-6 microm by OCT (n=116 struts) and 93+/-5 microm by pathology (n=68). Mean neointimal thickness on a segment-by-segment basis determined by OCT correlated with mean histomorphometric analysis (Reviewer 1: r=.74, P=.092 and Reviewer 2: r=0.60, P=.212). CONCLUSIONS: Day 4 represents an important time point for the assessment of early neointimal coverage in the porcine model. OCT imaging accurately assesses the extent and thickness of early neointimal coverage with good pathologic correlation. OCT represents a promising imaging modality for the in vivo assessment of neointimal coverage.
Mills, JS; N'diaye, CS; Yow, E; Urtz, M; Povsic, TJ; Greenfield, JC; Phillips, HR
Volume / Issue
Start / End Page
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)