Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images.

Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging-they are relatively invisible via angiography-and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images.

Automated Segmentation of Bioresorbable Vascular Scaffold Struts in Intracoronary Optical Coherence Tomography Images.

Bioresorbable vascular scaffolds (BVS), the next step in the continuum of minimally invasive vascular interventions present new opportunities for patients and clinicians but challenges as well. As they are comprised of polymeric materials standard imaging is challenging. This is especially problematic as modalities like optical coherence tomography (OCT) become more prevalent in cardiology. OCT, a light-based intracoronary imaging technique, provides cross-sectional images of plaque and luminal morphology. Until recently segmentation of OCT images for BVS struts was performed manually by experts. However, this process is time consuming and not tractable for large amounts of patient data. Several automated methods exist to segment metallic stents, which do not apply to the newer BVS. Given this current limitation coupled with the emerging popularity of the BVS technology, it is crucial to develop an automated methodology to segment BVS struts in OCT images. The objective of this paper is to develop a novel BVS strut detection method in intracoronary OCT images. First, we preprocess the image to remove imaging artifacts. Then, we use a K-means clustering algorithm to automatically segment the image. Finally, we isolate the stent struts from the rest of the image. The accuracy of the proposed method was evaluated using expert estimations on 658 annotated images acquired from 7 patients at the time of coronary arterial interventions. Our proposed methodology has a positive predictive value of 0.93, a Pearson Correlation coefficient of 0.94, and a F1 score of 0.92. The proposed methodology allows for rapid, accurate, and fully automated segmentation of BVS struts in OCT images.

Drug deposition in coronary arteries with overlapping drug-eluting stents.

Drug-eluting stents are accepted as mainstream endovascular therapy, yet concerns for their safety may be under-appreciated. While failure from restenosis has dropped to below 5%, the risk of stent thrombosis and associated mortality remain relatively high. Further optimization of drug release is required to minimize thrombosis risk while maintaining therapeutic dose. The complex three-dimensional geometry of deployed stents together with the combination of diffusive and advective drug transport render an intuitive understanding of the situation exceedingly difficult. In situations such as this, computational modeling has proven essential, helping define the limits of efficacy, determine the mode and mechanism of drug release, and identify alternatives to avoid toxicity. A particularly challenging conformation is encountered in coronary arteries with overlapping stents. To study hemodynamics and drug deposition in such vessels we combined high-resolution, multi-scale ex vivo computed tomography with a flow and mass transfer computational model. This approach ensures high geometric fidelity and precise, simultaneous calculation of blood flow velocity, shear stress and drug distribution. Our calculations show that drug uptake by the arterial tissue is dependent both on the patterns of flow disruption near the wall, as well as on the relative positioning of drug-eluting struts. Overlapping stent struts lead to localized peaks of drug concentration that may increase the risk of thrombosis. Such peaks could be avoided by anisotropic stent structure or asymmetric drug release designed to yield homogeneous drug distribution along the coronary artery and, at the least, suggest that these issues need to remain in the forefront of consideration in clinical practice.

The Systems Biocompatibility of Coronary Stenting.

The coronary stent has propelled our understanding of the term "biocompatibility." Stents are expanded at sites of arterial blockage and mechanically reestablish blood flow. This simplicity belies the complex reactions that occur when a stent contacts living substrates. Biocompatible seek to elicit the intended response; stents should perform rather than merely exist. Because performance is assessed in the patient, stent biocompatibility is the multiscale examination of material and cell, and of material, structure, and device in the context of cell, tissue, and organism. This review tracks major biomaterial advances in coronary stent design and discusses biocompatibility clinical performance.

Complementary X-ray tomography techniques for histology-validated 3D imaging of soft and hard tissues using plaque-containing blood vessels as examples.

A key problem in X-ray computed tomography is choosing photon energies for postmortem specimens containing both soft and hard tissues. Increasing X-ray energy reduces image artifacts from highly absorbing hard tissues including plaque, but it simultaneously decreases contrast in soft tissues including the endothelium. Therefore, identifying the lumen within plaque-containing vessels is challenging. Destructive histology, the gold standard for tissue evaluation, reaches submicron resolution in two dimensions, whereas slice thickness limits spatial resolution in the third. We present a protocol to systematically analyze heterogeneous tissues containing weakly and highly absorbing components in the original wet state, postmortem. Taking the example of atherosclerotic human coronary arteries, the successively acquired 3D data of benchtop and synchrotron radiation-based tomography are validated by histology. The entire protocol requires ∼20 working days, enables differentiation between plaque, muscle and fat tissues without using contrast agents and permits blood flow simulations in vessels with plaque-induced constrictions.

Hemodynamics in coronary arteries with overlapping stents.

Coronary artery stenosis is commonly treated by stent placement via percutaneous intervention, at times requiring multiple stents that may overlap. Stent overlap is associated with increased risk of adverse clinical outcome. While changes in local blood flow are suspected to play a role therein, hemodynamics in arteries with overlapping stents remain poorly understood. In this study we analyzed six cases of partially overlapping stents, placed ex vivo in porcine left coronary arteries and compared them to five cases with two non-overlapping stents. The stented vessel geometries were obtained by micro-computed tomography of corrosion casts. Flow and shear stress distribution were calculated using computational fluid dynamics. We observed a significant increase in the relative area exposed to low wall shear stress (WSS<0.5 Pa) in the overlapping stent segments compared both to areas without overlap in the same samples, as well as to non-overlapping stents. We further observed that the configuration of the overlapping stent struts relative to each other influenced the size of the low WSS area: positioning of the struts in the same axial location led to larger areas of low WSS compared to alternating struts. Our results indicate that the overlap geometry is by itself sufficient to cause unfavorable flow conditions that may worsen clinical outcome. While stent overlap cannot always be avoided, improved deployment strategies or stent designs could reduce the low WSS burden.

Compound ex vivo and in silico method for hemodynamic analysis of stented arteries.

Hemodynamic factors such as low wall shear stress have been shown to influence endothelial healing and atherogenesis in stent-free vessels. However, in stented vessels, a reliable quantitative analysis of such relations has not been possible due to the lack of a suitable method for the accurate acquisition of blood flow. The objective of this work was to develop a method for the precise reconstruction of hemodynamics and quantification of wall shear stress in stented vessels. We have developed such a method that can be applied to vessels stented in or ex vivo and processed ex vivo. Here we stented the coronary arteries of ex vivo porcine hearts, performed vascular corrosion casting, acquired the vessel geometry using micro-computed tomography and reconstructed blood flow and shear stress using computational fluid dynamics. The method yields accurate local flow information through anatomic fidelity, capturing in detail the stent geometry, arterial tissue prolapse, radial and axial arterial deformation as well as strut malapposition. This novel compound method may serve as a unique tool for spatially resolved analysis of the relationship between hemodynamic factors and vascular biology. It can further be employed to optimize stent design and stenting strategies.

Choosing the optimal wall shear parameter for the prediction of plaque location-A patient-specific computational study in human left coronary arteries.

OBJECTIVE: While the correlation of atherosclerotic plaque locations with local wall shear stress magnitude has been evaluated previously by other investigators in both right (RCA) and left coronary arteries (LCA), the relative performance of average wall shear stress (AWSS), average wall shear stress gradient (AWSSG), oscillatory shear index (OSI) and relative residence time (RRT) as indicators of potential atherosclerotic plaque locations has not been studied for the LCA. Here we determine the performance of said wall shear parameters in the LCA for the prediction of plaque development locations and compare these results to those previously found in the RCA. METHODS: We obtained 30 patient-specific geometries (mean age 67.1 (± 9.2) years, all with stable angina) of the LCA using dual-source computed tomography and virtually removed any plaque present. We then performed computational fluid dynamics simulations to calculate the wall shear parameters. RESULTS: For the 96 total plaques, AWSS had a higher sensitivity for the prediction of plaque locations (86 ± 25%) than AWSSG (65 ± 37%, p<0.05), OSI (67 ± 32%, p<0.01) or RRT (48 ± 38%, p<0.001). RRT had a higher PPV (49 ± 36%) than AWSS (31 ± 20%, p<0.05) or AWSSG (16 ± 12%, p<0.001). Segment 5 of the LCA presented with overall low values for sensitivity and PPV. Parameter performance in the remainder of the LCA was comparable to that in the RCA. CONCLUSIONS: AWSS features remarkably high sensitivity, but does not reach the PPV of RRT. This may indicate that while low wall shear stress is necessary for plaque formation, its presence alone is not sufficient to predict future plaque locations. Time dependent factors have to be taken into account as well.