TY - GEN
T1 - A new 3-D automated computational method to evaluate in-stent neointimal hyperplasia in in-vivo intravascular optical coherence tomography pullbacks
AU - Gurmeric, Serhan
AU - Isguder, Gozde Gul
AU - Carlier, Stéphane
AU - Unal, Gozde
PY - 2009
Y1 - 2009
N2 - 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±0.70mm 2 and for the stent cross-section area of 0.10±1.28mm2.
AB - 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±0.70mm 2 and for the stent cross-section area of 0.10±1.28mm2.
UR - http://www.scopus.com/inward/record.url?scp=80355142854&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04271-3_94
DO - 10.1007/978-3-642-04271-3_94
M3 - Conference contribution
C2 - 20426182
AN - SCOPUS:80355142854
SN - 3642042708
SN - 9783642042706
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 776
EP - 785
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI2009 - 12th International Conference, Proceedings
T2 - 12th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2009
Y2 - 20 September 2009 through 24 September 2009
ER -