Antonis I. Sakellarios

3D reconstruction of coronary arteries using Frequency Domain Optical Coherence Tomography images and biplane angiography

The aim of this study is to describe a new method for three-dimensional (3D) reconstruction of coronary arteries using Frequency Domain Optical Coherence Tomography (FD-OCT) images. The rationale is to fuse the information about the curvature of the artery, derived from biplane angiographies, with the information regarding the lumen wall, which is produced from the FD-OCT examination. The method is based on a three step approach. In the first step the lumen borders in FD-OCT images are detected. In the second step a 3D curve is produced using the center line of the vessel from the two biplane projections. Finally in the third step the detected lumen borders are placed perpendicularly onto the path based on the centroid of each lumen border. The result is a 3D reconstructed artery produced by all the lumen borders of the FD-OCT pullback representing the 3D arterial geometry of the vessel.

Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images

Abstract. Optical coherence tomography (OCT) is a light-based intracoronary imaging modality that provides high-resolution cross-sectional images of the luminal and plaque morphology. Currently, the segmentation of OCT images and identification of the composition of plaque are mainly performed manually by expert observers. However, this process is laborious and time consuming and its accuracy relies on the expertise of the observer. To address these limitations, we present a methodology that is able to process the OCT data in a fully automated fashion. The proposed methodology is able to detect the lumen borders in the OCT frames, identify the plaque region, and detect four tissue types: calcium (CA), lipid tissue (LT), fibrous tissue (FT), and mixed tissue (MT). The efficiency of the developed methodology was evaluated using annotations from 27 OCT pullbacks acquired from 22 patients. High Pearson’s correlation coefficients were obtained between the output of the developed methodology and the manual annotations (from 0.96 to 0.99), while no significant bias with good limits of agreement was shown in the Bland-Altman analysis. The overlapping areas ratio between experts’ annotations and methodology in detecting CA, LT, FT, and MT was 0.81, 0.71, 0.87, and 0.81, respectively.

Patient-Specific Prediction of Coronary Plaque Growth From CTA Angiography: A Multiscale Model for Plaque Formation and Progression

Computational fluid dynamics methods based on in vivo 3-D vessel reconstructions have recently been identified the influence of wall shear stress on endothelial cells as well as on vascular smooth muscle cells, resulting in different events such as flow mediated vasodilatation, atherosclerosis, and vascular remodeling. Development of image-based modeling technologies for simulating patient-specific local blood flows is introducing a novel approach to risk prediction for coronary plaque growth and progression. In this study, we developed 3-D model of plaque formation and progression that was tested in a set of patients who underwent coronary computed tomography angiography (CTA) for anginal symptoms. The 3-D blood flow is described by the Navier-Stokes equations, together with the continuity equation. Mass transfer within the blood lumen and through the arterial wall is coupled with the blood flow and is modeled by a convection-diffusion equation. The low density lipoprotein (LDL) transports in lumen of the vessel and through the vessel tissue (which has a mass consumption term) are coupled by Kedem-Katchalsky equations. The inflammatory process is modeled using three additional reaction-diffusion partial differential equations. A full 3-D model was created. It includes blood flow and LDL concentration, as well as plaque formation and progression. Furthermore, features potentially affecting plaque growth, such as patient risk score, circulating biomarkers, localization and composition of the initial plaque, and coronary vasodilating capability were also investigated. The proof of concept of the model effectiveness was assessed by repetition of CTA, six months after the baseline evaluation. Besides the low values of local shear stress, plaque characteristics, risk profile, pattern of circulating adhesion molecules, and reduced coronary flow reserve at baseline appeared to affect plaque progression toward flow-limiting lesions at follow-up evaluation. Although preliminary, our multidisciplinary approach to a “personalized” prediction of coronary plaque progression suggests that incorporation in atherosclerotic models of systemic and local hemodynamic features may better predict evolution of plaques in coronary artery disease stable patients.

Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors

Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation. Furthermore, we implemented a new model for LDL penetration across the endothelial membrane, assuming that endothelial permeability depends on the local lumen LDL concentration. The results showed that the presence of the stenosis had a dramatic effect on the local ESS distribution and LDL accumulation along the artery, and areas of increased LDL accumulation were observed in the downstream region where flow recirculation and low ESS were present. Of the studied factors influencing LDL accumulation, 1) hypertension, 2) increased endothelial permeability (a surrogate of endothelial dysfunction), and 3) increased serum LDL levels, especially when the new model of variable endothelial permeability was applied, had the largest effects, thereby supporting their role as major cardiovascular risk factors.

Multiscale - Patient-Specific Artery and Atherogenesis Models

In this work, we present a platform for the development of multiscale patient-specific artery and atherogenesis models. The platform, called ARTool, integrates technologies of 3-D image reconstruction from various image modalities, blood flow and biological models of mass transfer, plaque characterization, and plaque growth. Patient images are acquired for the development of the 3-D model of the patient specific arteries. Then, blood flow is modeled within the arterial models for the calculation of the wall shear stress distribution (WSS). WSS is combined with other patient-specific parameters for the development of the plaque progression models. Real-time simulation can be performed for same cases in grid environment. The platform is evaluated using both animal and human data.

Three-dimensional reconstruction of coronary arteries and plaque morphology using CT angiography – comparison and registration with IVUS

BackgroundThe aim of this study is to present a new methodology for three-dimensional (3D) reconstruction of coronary arteries and plaque morphology using Computed Tomography Angiography (CTA).MethodsThe methodology is summarized in six stages: 1) pre-processing of the initial raw images, 2) rough estimation of the lumen and outer vessel wall borders and approximation of the vessel’s centerline, 3) manual adaptation of plaque parameters, 4) accurate extraction of the luminal centerline, 5) detection of the lumen - outer vessel wall borders and calcium plaque region, and 6) finally 3D surface construction.ResultsThe methodology was compared to the estimations of a recently presented Intravascular Ultrasound (IVUS) plaque characterization method. The correlation coefficients for calcium volume, surface area, length and angle vessel were 0.79, 0.86, 0.95 and 0.88, respectively. Additionally, when comparing the inner and outer vessel wall volumes of the reconstructed arteries produced by IVUS and CTA the observed correlation was 0.87 and 0.83, respectively.ConclusionsThe results indicated that the proposed methodology is fast and accurate and thus it is likely in the future to have applications in research and clinical arena.

Novel methodology for 3D reconstruction of carotid arteries and plaque characterization based upon magnetic resonance imaging carotid angiography data

In this study, we present a novel methodology that allows reliable segmentation of the magnetic resonance images (MRIs) for accurate fully automated three-dimensional (3D) reconstruction of the carotid arteries and semiautomated characterization of plaque type. Our approach uses active contours to detect the luminal borders in the time-of-flight images and the outer vessel wall borders in the T(1)-weighted images. The methodology incorporates the connecting components theory for the automated identification of the bifurcation region and a knowledge-based algorithm for the accurate characterization of the plaque components. The proposed segmentation method was validated in randomly selected MRI frames analyzed offline by two expert observers. The interobserver variability of the method for the lumen and outer vessel wall was -1.60%±6.70% and 0.56%±6.28%, respectively, while the Williams Index for all metrics was close to unity. The methodology implemented to identify the composition of the plaque was also validated in 591 images acquired from 24 patients. The obtained Cohens k was 0.68 (0.60-0.76) for lipid plaques, while the time needed to process an MRI sequence for 3D reconstruction was only 30 s. The obtained results indicate that the proposed methodology allows reliable and automated detection of the luminal and vessel wall borders and fast and accurate characterization of plaque type in carotid MRI sequences. These features render the currently presented methodology a useful tool in the clinical and research arena.

Impact of local endothelial shear stress on neointima and plaque following stent implantation in patients with ST-elevation myocardial infarction: A subgroup-analysis of the COMFORTABLE AMI-IBIS 4 trial

BACKGROUND Numerous studies have demonstrated an association between endothelial shear stress (ESS) and neointimal formation after stent implantation. However, the role of ESS on the composition of neointima and underlying plaque remains unclear. METHODS Patients recruited in the Comfortable AMI-IBIS 4 study implanted with bare metal stents (BMS) or biolimus eluting stents (BES) that had biplane coronary angiography at 13 month follow-up were included in the analysis. The intravascular ultrasound virtual-histology (IVUS-VH) and the angiographic data were used to reconstruct the luminal surface, and the stent in the stented segments. Blood flow simulation was performed in the stent surface, which was assumed to represent the luminal surface at baseline, to assess the association between ESS and neointima thickness. The predominant ESS was estimated in 3-mm segments and was correlated with the amount of neointima, neointimal tissue composition, and with the changes in the underlying plaque burden and composition. RESULTS Forty three patients (18 implanted with BMS and 25 with BES) were studied. In both stent groups negative correlations were noted between ESS and neointima thickness in BMS (P < 0.001) and BES (P = 0.002). In BMS there was a negative correlation between predominant ESS and the percentage of the neointimal necrotic core component (P = 0.015). In BES group, the limited neointima formation did not allow evaluation of the effect of ESS on its tissue characteristics. ESS did not affect vessel wall remodeling and the plaque burden and composition behind BMS (P > 0.10) and BES (P > 0.45). CONCLUSIONS ESS determines neointimal formation in both BMS and BES and affects the composition of the neointima in BMS. Conversely, ESS does not impact the plaque behind struts irrespective of stent type throughout 13 months of follow-up.

Noninvasive Prediction of Atherosclerotic Progression: The PROSPECT-MSCT Study

Intravascular imaging-based natural history studies of atherosclerosis have provided insight into atherosclerotic evolution and demonstrated that local hemodynamic factors, plaque burden, and the composition of the atheroma regulate plaque growth and determine vulnerable plaque formation [(1,2)][1

Prediction of atherosclerotic disease progression using LDL transport modelling: a serial computed tomographic coronary angiographic study

Aim To investigate the efficacy of low-density lipoprotein (LDL) transport simulation in reconstructed arteries derived from computed tomography coronary angiography (CTCA) to predict coronary segments that are prone to progress. Methods and results Thirty-two patients admitted with an acute coronary event who underwent 64-slice CTCA after percutaneous coronary intervention and at 3-year follow-up were included in the analysis. The CTCA data were used to reconstruct the coronary anatomy of the untreated vessels at baseline and follow-up, and LDL transport simulation was performed in the baseline models. The computed endothelial shear stress (ESS), LDL concentration, and CTCA-derived plaque characteristics were used to identify predictors of substantial disease progression (defined as an increase in the plaque burden at follow-up higher than two standard deviations of the intra-observer variability of the expert who performed the analysis). Fifty-eight vessels were analysed. High LDL concentration [odds ratio (OR): 2.16; 95% confidence interval (CI): 1.64–2.84; P = 0.0054], plaque burden (OR: 1.40; 95% CI: 1.13–1.72; P = 0.0017), and plaque area (OR: 3.46; 95% CI: 2.20–5.44; P⩽ 0.0001) were independent predictors of a substantial disease progression at follow-up. The ESS appears as a predictor of disease progression in univariate analysis but was not an independent predictor when the LDL concentration was entered into the multivariate model. The accuracy of the model that included the LDL concentration was higher than the accuracy of the model that included the ESS (65.1 vs. 62.5%). Conclusions LDL transport modelling appears a better predictor of atherosclerotic disease progression than the ESS, and combined with the atheroma characteristics provided by CTCA is able to detect with a moderate accuracy segments that will exhibit a significant plaque burden increase at mid-term follow-up.