The objectives of this article are (i) to
utilize computer methods in detection of stent struts
imaged in vivo by optical coherence tomography
(OCT) during percutaneous coronary interventions
(PCI); (ii) to provide measurements for the assessment
and monitoring of in-stent restenosis by OCT post PCI.
Thirty-nine OCT cross-sections from seven pullbacks
from seven patients presenting varying degrees of
neointimal hyperplasia (NIH) are selected, and stent
struts are detected. Stent and lumen boundaries are
reconstructed and one experienced observer analyzed
the strut detection, the lumen and stent area measurements,
as well as the NIH thickness in comparison to
manual tracing using the reviewing software provided
by the OCT manufacturer (LightLab Imaging, MA,
USA). Very good agreements were found between
the computer methods and the expert evaluations
for lumen cross-section area (mean difference =
0.11 ± 0.70 mm2; r2 = 0.98, P\ 0.0001) and the
stent cross-section area (mean difference = 0.10 ±
1.28 mm2; r2 = 0.85, P value\ 0.0001). The average
number of detected struts was 10.4 ± 2.9 per crosssection
when the expert identified 10.5 ± 2.8
(r2 = 0.78, P value\0.0001). For the given patient
dataset: lumen cross-sectional area was on the average
(6.05 ± 1.87 mm2), stent cross-sectional area was
(6.26 ± 1.63 mm2), maximum angle between struts
was on the average (85.96 ± 54.23), maximum,
average, and minimum distance between the stent
and the lumen were (0.18 ± 0.13 mm), (0.08 ±
0.06 mm), and (0.01 ± 0.02 mm), respectively, and
stent eccentricity was (0.80 ± 0.08). Low variability
between the expert and automatic method was
observed in the computations of the most important
parameters assessing the degree of neointimal tissue
growth in stents imaged by OCT pullbacks. After
further extensive validation, the presented methods
might offer a robust automated tool that will improve
the evaluation and follow-up monitoring of in-stent
restenosis in patients