Background-Native atherosclerosis and in-stent restenosis are focal and evolve independently. The endothelium controls local arterial responses by transduction of shear stress. Characterization of endothelial shear stress (ESS) may allow for prediction of progression of atherosclerosis and in-stent restenosis. Methods and Results-By using intracoronary ultrasound, biplane coronary angiography, and measurement of coronary blood flow, we represented the artery in accurate 3D space and determined detailed characteristics of ESS and arterial wall/plaque morphology. Patients who underwent stent implantation and who had another artery with luminal obstruction Ͻ50% underwent intravascular profiling initially and after 6-month follow-up. Twelve arteries in 8 patients were studied: 6 native and 6 stented arteries. In native arteries, regions of abnormally low baseline ESS exhibited a significant increase in plaque thickness and enlargement of the outer vessel wall, such that lumen radius remained unchanged (outward remodeling). Regions of physiological ESS showed little change. Regions with increased ESS exhibited outward remodeling with normalization of ESS. In stented arteries, there was an increase in intima-medial thickness, a decrease in lumen radius, and an increase in ESS at all levels of baseline ESS. Key Words: endothelium Ⅲ atherosclerosis Ⅲ coronary disease Ⅲ shear stress C oronary atherosclerosis is focal and eccentric, 1,2 and each coronary obstruction progresses or regresses in an independent manner, including areas after percutaneous revascularization. 3 Local hemodynamic factors are crucial to determine the evolution of coronary obstructions. 1,4 The vascular endothelium is in a pivotal position to respond to the dynamic forces acting on the vessel wall owing to the complex 3D geometry of the artery. 5 Fluid shear stresses elicit a large number of responses in endothelial cells. 4,5 The response of genes sensitive to local hemodynamic forces likely leads to creation of a raised plaque; subsequent hemodynamic forces created by the plaque may lead to a cycle of cellular recruitment and proliferation, lipid accumulation, and inflammation. 4,6 The pathobiology of restenosis after percutaneous coronary interventions may be due to 2 independent processes: geometric remodeling and neointimal hyperplasia. In segments undergoing angioplasty alone, late lumen loss is largely due to geometric remodeling, whereas in stented arteries, late lumen loss correlates primarily with intimal hyperplasia. 7 The effect of endothelial shear stress (ESS) within the stent or at the stent edges has not been fully explored as a mechanism contributing to in-stent restenosis. 8 Current methodologies cannot provide adequate information about the microenvironment of the coronary arteries. We developed a unique system by using coronary intravascular ultrasound (IVUS), biplane coronary angiography, and measurements of coronary blood flow to represent the artery in accurate 3D space and to produce detailed characteristics of ESS and arter...

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This paper describes an evaluation framework that allows a standardized and quantitative comparison of IVUS lumen and media segmentation algorithms. This framework has been introduced at the MICCAI 2011 Computing and Visualization for (Intra)Vascular Imaging (CVII) workshop, comparing the results of eight teams that participated. We describe the available data-base comprising of multi-center, multi-vendor and multi-frequency IVUS datasets, their acquisition, the creation of the reference standard and the evaluation measures. The approaches address segmentation of the lumen, the media, or both borders; semi- or fully-automatic operation; and 2-D vs. 3-D methodology. Three performance measures for quantitative analysis have been proposed. The results of the evaluation indicate that segmentation of the vessel lumen and media is possible with an accuracy that is comparable to manual annotation when semi-automatic methods are used, as well as encouraging results can be obtained also in case of fully-automatic segmentation. The analysis performed in this paper also highlights the challenges in IVUS segmentation that remains to be solved.

Plaque progresses in subsegments with low ESS, associated with either constrictive or expansive remodelling. Different mechanisms are likely responsible for expansive remodelling in different local vascular environments. Early in vivo identification of arterial subsegments likely to develop high-risk plaque characteristics may allow for selective interventions to avoid adverse cardiac outcomes.

Abstract-In the rapidly evolving field of intravascular ultrasound (IVUS), the assessment of vessel morphology still lacks a geometrically correct 3-D reconstruction. The IVUS frames are usually stacked up to form a straight vessel, neglecting curvature and the axial twisting of the catheter during the pullback. Our method combines the information about vessel cross-sections obtained from IVUS with the information about the vessel geometry derived from biplane angiography. First, the catheter path is reconstructed from its biplane projections, resulting in a spatial model. The locations of the IVUS frames are determined and their orientations relative to each other are calculated using a discrete approximation of the Frenet-Serret formulas known from differential geometry. The absolute orientation of the frame set is established utilizing the imaging catheter itself as an artificial landmark. The IVUS images are segmented using our previously developed algorithm. The fusion approach has been extensively validated in computer simulations, phantoms, and cadaveric pig hearts.

The relationships among vascular geometry, hemodynamics, and plaque development in the coronary arteries are complex and not yet well understood. This paper reports a methodology for the quantitative analysis of in vivo coronary morphology and hemodynamics, with particular emphasis placed on the critical issues of image segmentation and the automated classification of disease severity. We were motivated by the observation that plaque more often developed at the inner curvature of a vessel, presumably due to the relatively lower wall shear stress at these locations. The presented studies are based on our validated methodology for the three-dimensional fusion of intravascular ultrasound (IVUS) and X-ray angiography, introducing a novel approach for IVUS segmentation that incorporates a robust, knowledge-based cost function and a fully optimal, threedimensional segmentation algorithm. Our first study shows that circumferential plaque distribution depends on local vessel curvature in the majority of vessels. The second study analyzes the correlation between plaque distribution and wall shear stress in a set of 48 in vivo vessel segments. The results were conclusive for both studies, with a stronger correlation of circumferential plaque thickness with local curvature than with wall shear stress. The inverse relationship between local wall shear stress and plaque thickness was significantly more pronounced (p < 0.025) in vessel cross sections exhibiting compensatory enlargement (positive remodeling) without luminal narrowing than when the full spectrum of disease severity was considered. The inverse relationship was no longer observed in vessels where less than 35% of vessel cross sections remained without luminal narrowing. The findings of this study confirm, in vivo, the hypothesis that relatively lower wall shear stress is associated with early plaque development.

Quantitative evaluations on coronary vessel systems are of increasing importance in cardiovascular diagnosis, therapy planning, and surgical verification. Whereas local evaluations, such as stenosis analysis, are already available with sufficient accuracy, global evaluations of vessel segments or vessel subsystems are not yet common. Especially for the diagnosis of diffuse coronary artery diseases, the authors combined a 3D reconstruction system operating on biplane angiograms with a length/volume calculation. The 3D reconstruction results in a 3D model of the coronary vessel system, consisting of the vessel skeleton and a discrete number of contours. To obtain an utmost accurate model, the authors focussed on exact geometry determination. Several algorithms for calculating missing geometric parameters and correcting remaining geometry errors were implemented and verified. The length/volume evaluation can be performed either on single vessel segments, on a set of segments, or on subtrees. A volume model based on generalized elliptical conic sections is created for the selected segments. Volumes and lengths (measured along the vessel course) of those elements are summed up. In this way, the morphological parameters of a vessel subsystem can be set in relation to the parameters of the proximal segment supplying it. These relations allow objective assessments of diffuse coronary artery diseases.

PurposeA pilot study showed that prediction of individual Humphrey 24-2 visual field (HVF 24-2) sensitivity thresholds from optical coherence tomography (OCT) image analysis is possible. We evaluate performance of an improved approach as well as 3 other predictive algorithms on a new, fully independent set of glaucoma subjects.MethodsSubjects underwent HVF 24-2 and 9-field OCT (Heidelberg Spectralis) testing. Nerve fiber (NFL), and ganglion cell and inner plexiform (GCL+IPL) layers were cosegmented and partitioned into 52 sectors matching HVF 24-2 test locations. The Wilcoxon rank sum test was applied to test correlation R, root mean square error (RMSE), and limits of agreement (LoA) between actual and predicted thresholds for four prediction models. The training data consisted of the 9-field OCT and HVF 24-2 thresholds of 111 glaucoma patients from our pilot study.ResultsWe studied 112 subjects (112 eyes) with early, moderate, or advanced primary and secondary open angle glaucoma. Subjects with less than 9 scans (15/112) or insufficient quality segmentations (11/97) were excluded. Retinal ganglion cell axonal complex (RGC-AC) optimized had superior average R = 0.74 (95% confidence interval [CI], 0.67–0.76) and RMSE = 5.42 (95% CI, 5.1–5.7) dB, which was significantly better (P < 0.05/3) than the other three models: Naïve (R = 0.49; 95% CI, 0.44–0.54; RMSE = 7.24 dB; 95% CI, 6.6–7.8 dB), Garway-Heath (R = 0.66; 95% CI, 0.60–0.68; RMSE = 6.07 dB; 95% CI, 5.7–6.5 dB), and Donut (R = 0.67; 95% CI, 0.61–0.69; RMSE = 6.08 dB, 95% CI, 5.8–6.4 dB).ConclusionsThe proposed RGC-AC optimized predictive algorithm based on 9-field OCT image analysis and the RGC-AC concept is superior to previous methods and its performance is close to the reproducibility of HVF 24-2.