Abstract. Detection of stent struts imaged in vivo by optical coherence tomography (OCT) after percutaneous coronary interventions (PCI) and quantifcation of in-stent neointimal hyperplasia (NIH) are important. In this paper, we present a new computational method to facilitate the physician in this endeavor to assess and compare new (drug-eluting) stents. We developed a new algorithm for stent strut detection and utilized splines to reconstruct the lumen and stent boundaries which provide automatic measurements of NIH thickness, lumen and stent area. Our original approach is based on the detection of stent struts unique characteristics: bright re ection and shadow behind. Furthermore, we present for the frst time to our knowledge a rotation correction method applied across OCT cross-section images for 3D reconstruction and visualization of reconstructed lumen and stent boundaries for further analysis in the longitudinal dimension of the coronary artery. Our experiments over OCT cross-sections taken from 7 patients presenting varying degrees of NIH after PCI illustrate a good agreement between the computer method and expert evaluations: Bland-Altmann analysis revealed a mean difference for lumen cross-section area of 0.11 +- 0.70mm2 and for the stent cross-section area of 0.10 +- 1.28mm2.
Medical Image Computing and Computer Assisted Intervention, MICCAI, 2009