Abstract. Detection of stent struts imaged in vivo by optical coherence
tomography (OCT) after percutaneous coronary interventions (PCI) and
quantification 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 reflection and shadow behind. Furthermore, we present
for the first 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
