Accurate and reproducible reconstruction of coronary arteries and endothelial shear stress calculation using 3D OCT: Comparative study to 3D IVUS and 3D QCA

Toutouzas, Konstantinos; Chatzizisis, Yiannis S.; Riga, Maria; Giannopoulos, Andreas A.; Antoniadis, Antonios; Tu, Shengxian; Fujino, Yusuke; Mitsouras, Dimitrios; Doulaverakis, Charalampos; Tsampoulatidis, Ioannis; Koutkias, Vassilis; Bouki, Konstantina P.; Li, Yingguang; Chouvarda, Ioanna; Cheimariotis, Grigorios-Aris; Maglaveras, Nicos; Kompatsiaris, Ioannis; Nakamura, Sunao; Reiber, Johan H. C.; Rybicki, Frank J.; Karvounis, Haralambos; Stefanadis, Christodoulos; Tousoulis, Dimitris; Giannoglou, George D.

doi:10.1016/j.atherosclerosis.2015.04.011

Cited by 62 publications

(32 citation statements)

References 39 publications

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“…Indeed, the implantation of a stent in a coronary artery alters the physiological blood flow and induces recirculation and low, oscillatory endothelial shear stresses that may lead to in-stent restenosis [39,40]. In several recent studies, hemodynamic simulations were performed in 3D geometries of coronary arteries, which were reconstructed by coupling the lumen contours, automatically detected from OCT images, with the vessel centerline, extracted from angiography or computed tomography [41–46]. However, both vessel lumen and stent geometries were reconstructed starting from OCT images for subsequent hemodynamic analyses only in few studies [47,48].…”

Section: Discussionmentioning

confidence: 99%

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

et al. 2017

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Optical coherence tomography (OCT) is an established catheter-based imaging modality for the assessment of coronary artery disease and the guidance of stent placement during percutaneous coronary intervention. Manual analysis of large OCT datasets for vessel contours or stent struts detection is time-consuming and unsuitable for real-time applications. In this study, a fully automatic method was developed for detection of both vessel contours and stent struts. The method was applied to in vitro OCT scans of eight stented silicone bifurcation phantoms for validation purposes. The proposed algorithm comprised four main steps, namely pre-processing, lumen border detection, stent strut detection, and three-dimensional point cloud creation. The algorithm was validated against manual segmentation performed by two independent image readers. Linear regression showed good agreement between automatic and manual segmentations in terms of lumen area (r>0.99). No statistically significant differences in the number of detected struts were found between the segmentations. Mean values of similarity indexes were >95% and >85% for the lumen and stent detection, respectively. Stent point clouds of two selected cases, obtained after OCT image processing, were compared to the centerline points of the corresponding stent reconstructions from micro computed tomography, used as ground-truth. Quantitative comparison between the corresponding stent points resulted in median values of ~150 μm and ~40 μm for the total and radial distances of both cases, respectively. The repeatability of the detection method was investigated by calculating the lumen volume and the mean number of detected struts per frame for seven repeated OCT scans of one selected case. Results showed low deviation of values from the median for both analyzed quantities. In conclusion, this study presents a robust automatic method for detection of lumen contours and stent struts from OCT as supported by focused validation against both manual segmentation and micro computed tomography and by good repeatability.

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Section: Discussionmentioning

confidence: 99%

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

et al. 2017

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“…Most coronary ESS studies have reconstructed the 3D coronary lumen from two or more invasive catheter angiography (ICA) projections to extract the vessel course, and either intravascular ultrasound (IVUS) or optical coherence tomography (OCT) data to extract the lumen contour around this course [14, 15]. The majority of studies thus focus on an individual “target” coronary artery segment where IVUS or OCT are clinically indicated, commonly omitting side branches in that segment [4, 7, 16].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the effect of side branches in endothelial shear stress estimates

et al. 2016

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Background and aims Low and high endothelial shear stress (ESS) is associated with coronary atherosclerosis progression and high-risk plaque features. Coronary ESS is currently assessed via computational fluid dynamic (CFD) simulation in the lumen geometry determined from invasive imaging such as intravascular ultrasound and optical coherence tomography. This process typically omits side branches of the target vessel in the CFD model as invasive imaging of those vessels is not clinically-indicated. The purpose of this study was to determine the extent to which this simplification affects the determination of those regions of the coronary endothelium subjected to pathologic ESS. Methods We determined the diagnostic accuracy of ESS profiling without side branches to detect pathologic ESS in the major coronary arteries of 5 hearts imaged ex vivo with CT angiography. ESS of the three major coronary arteries was calculated both without (test model), and with (reference model) inclusion of all side branches >1.5 mm in diameter, using previously-validated CFD approaches. Diagnostic test characteristics (accuracy, sensitivity, specificity and negative and positive predictive value [NPV/PPV]) with respect to the reference model were assessed for both the entire length as well as only the proximal portion of each major coronary artery, where the majority of high-risk plaques occur. Results Using the model without side branches overall accuracy, sensitivity, specificity, NPV and PPV were 83.4%, 54.0%, 96%, 95.9% and 55.1%, respectively to detect low ESS, and 87.0%, 67.7%, 90.7%, 93.7% and 57.5%, respectively to detect high ESS. When considering only the proximal arteries, test characteristics differed for low and high ESS, with low sensitivity (67.7%) and high specificity (90.7%) to detect low ESS, and low sensitivity (44.7%) and high specificity (95.5%) to detect high ESS. Conclusions The exclusion of side branches in ESS vascular profiling studies greatly reduces the ability to detect regions of the major coronary arteries subjected to pathologic ESS. Single-conduit models can in general only be used to rule out pathologic ESS.

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“…3D QCA is a technique that can rapidly and accurately reconstruct coronary arteries and can even potentially provide local hemodynamic and functional information. For instance, feasibility of 3D QCA derived assessment of ESS and fractional flow reserve has been demonstrated [10,32]. This fact makes our applied 3D reconstruction method a very useful tool since it requires only two biplane angiographies that need be acquired in any case in clinical practice.…”

Section: Advantage Of 3d Qca Analysismentioning

confidence: 94%

Association of stent‐induced changes in coronary geometry with late stent failure: Insights from three‐dimensional quantitative coronary angiographic analysis

Zhang

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et al. 2018

Cathet Cardio Intervent

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Accurate and reproducible reconstruction of coronary arteries and endothelial shear stress calculation using 3D OCT: Comparative study to 3D IVUS and 3D QCA

Abstract: Geometrically-correct 3D OCT is a feasible, accurate and reproducible 3D reconstruction technique that can perform reliable ESS calculations in coronary arteries.

Cited by 62 publications

References 39 publications

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method

Quantifying the effect of side branches in endothelial shear stress estimates

Association of stent‐induced changes in coronary geometry with late stent failure: Insights from three‐dimensional quantitative coronary angiographic analysis

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