ANGIOCARE: an automated system for fast three-dimensional coronary reconstruction by integrating angiographic and intracoronary ultrasound data

Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data

BACKGROUND

The risk of cardiovascular disease (CVD) has traditionally been predicted via the assessment of carotid plaques. In the proposed study, AtheroEdge™ 3.0HDL (AtheroPoint™, Roseville, CA, USA) was designed to demonstrate how well the features obtained from carotid plaques determine the risk of CVD. We hypothesize that hybrid deep learning (HDL) will outperform unidirectional deep learning, bidirectional deep learning, and machine learning (ML) paradigms.

METHODOLOGY

500 people who had undergone targeted carotid B-mode ultrasonography and coronary angiography were included in the proposed study. ML feature selection was carried out using three different methods, namely principal component analysis (PCA) pooling, the chi-square test (CST), and the random forest regression (RFR) test. The unidirectional and bidirectional deep learning models were trained, and then six types of novel HDL-based models were designed for CVD risk stratification. The AtheroEdge™ 3.0HDL was scientifically validated using seen and unseen datasets while the reliability and statistical tests were conducted using CST along with p-value significance. The performance of AtheroEdge™ 3.0HDL was evaluated by measuring the p-value and area-under-the-curve for both seen and unseen data.

RESULTS

The HDL system showed an improvement of 30.20% (0.954 vs. 0.702) over the ML system using the seen datasets. The ML feature extraction analysis showed 70% of common features among all three methods. The generalization of AtheroEdge™ 3.0HDL showed less than 1% (p-value < 0.001) difference between seen and unseen data, complying with regulatory standards.

CONCLUSIONS

The hypothesis for AtheroEdge™ 3.0HDL was scientifically validated, and the model was tested for reliability and stability and is further adaptable clinically.

3D reconstruction of coronary artery bifurcations from intravascular ultrasound and angiography

Coronary bifurcation lesions represent a challenging anatomical subset, and the understanding of their 3D anatomy and plaque composition appears to play a key role in devising the optimal stenting strategy. This study proposes a new approach for the 3D reconstruction of coronary bifurcations and plaque materials by combining intravascular ultrasound (IVUS) and angiography. Three patient-specific silicone bifurcation models were 3D reconstructed and compared to micro-computed tomography (µCT) as the gold standard to test the accuracy and reproducibility of the proposed methodology. The clinical feasibility of the method was investigated in three diseased patient-specific bifurcations of varying anatomical complexity. The IVUS-based 3D reconstructed bifurcation models showed high agreement with the µCT reference models, with r2 values ranging from 0.88 to 0.99. The methodology successfully 3D reconstructed all the patient bifurcations, including plaque materials, in less than 60 min. Our proposed method is a simple, time-efficient, and user-friendly tool for accurate 3D reconstruction of coronary artery bifurcations. It can provide valuable information about bifurcation anatomy and plaque burden in the clinical setting, assisting in bifurcation stent planning and education.

Extraction of media adventitia and luminal intima borders by reconstructing intravascular ultrasound image sequences with vascular structural continuity

PURPOSE

Most published methods directly achieve vessel membrane border detection on cross-sectional intravascular ultrasound (IVUS) images. The vascular structural continuity that exists in entire IVUS image sequences has been overlooked. However, this continuity can have a helpful role in the delineation of vessel membrane contours. To achieve the vessel membrane segmentation more effectively through employing this continuity, a strategy, referred to as multiangle reconstruction, segmentation, and recovery (RSR), is proposed in this paper.

METHODS

Four main steps are contained in the multiangle-RSR: first, a combination of sampling and interpolation is employed to reconstruct long-axis-model IVUS frames, in which continuity information becomes available. Second, a clustering algorithm is conducted on long-axis-model IVUS frames to roughly extract the media-adventitia (MA) and lumen-intima (LI) boundaries. Third, the segmentation results of cross-sectional IVUS frames are recovered based on the rough results of long-axis-model IVUS frames, and an optimization process that combines downsampling, fitting and smoothing is designed to reduce the interference of bifurcation and side vessels.

RESULTS

Multiangle-RSR is tested on a public dataset, and the Hausdorff distance (HD), Jaccard measure (JM), and percentage of area difference (PAD) are utilized as quantitative evaluation metrics. Mean HDs of 0.34 and 0.29 mm are obtained for MA border detection and LI border detection, respectively, which decrease by 43.3% and 9.4%, respectively, compared with their counterparts in previously published approaches. Furthermore, the mean JM is 0.87 for both MA border detection and LI border detection. The mean PADs of the MA contour extraction and the LI contour extraction are 0.10 and 0.11, respectively.

CONCLUSION

The results indicate that the proposed strategy effectively introduces vascular structural continuity by reconstructing long-axis-model IVUS frames and achieves more precise extraction of MA and LI borders.

The effect of the degree and location of coronary stenosis on the hemodynamic status of a coronary vessel

The ongoing advances in the field of cardiovascular modelling during the past years have allowed for the creation of accurate three-dimensional models of the major coronary arteries. The aforementioned 3D models can accurately mimic the human coronary vasculature if they are combined with sophisticated computational fluid dynamics algorithms and shed light to non-trivial issues that concern the clinicians. One of these issues is to define whether a coronary lesion is more dangerous to present with ischemia if it is at a proximal or a distal part of the vessel. In this work, we aim to investigate the aforementioned issue by reconstructing in 3D a coronary arterial model from a healthy subject using Computed Tomography Coronary Angiography images and by editing it to create eight diseased arterial models that contain one or two lesions of different severities. After carrying out the appropriate blood flow simulations using the finite element method, we observed that the distal lesions are more dangerous than the proximal ones in terms of hemodynamic significance. Moreover, the distal severe stenosis (i.e. 70% diameter reduction) present with the highest peak Wall Shear Stress (WSS) values in comparison to the proximal ones.

The effect of the stenosis location at a coronary arterial bifurcation: a parametric study

The advances in cardiovascular modelling over the past two decades have given the opportunity to create accurate three dimensional models of the coronary vasculature which, combined with advanced computational fluid dynamics algorithms can shed light to intriguing matters that concern clinicians. One of these issues is the presence of a stenosis near bifurcations in one of the major coronary vessels. In this work, we try to shed light on the aforementioned matter by creating a healthy arterial bifurcation reconstructed using the fusion of Optical Coherence Tomography and X-Ray angiography images. The healthy model was edited by adding an artificial stenosis of 50% diameter reduction into three different locations after the bifurcation, thus creating three diseased models. After performing the appropriate blood flow simulations, we observed that the location of the stenosis affects the Wall Shear Stress (WSS) distribution but it does not affect the functional significance of the stenosis itself.

The Evolution of Data Fusion Methodologies Developed to Reconstruct Coronary Artery Geometry From Intravascular Imaging and Coronary Angiography Data: A Comprehensive Review

Understanding the mechanisms that regulate atherosclerotic plaque formation and evolution is a crucial step for developing treatment strategies that will prevent plaque progression and reduce cardiovascular events. Advances in signal processing and the miniaturization of medical devices have enabled the design of multimodality intravascular imaging catheters that allow complete and detailed assessment of plaque morphology and biology. However, a significant limitation of these novel imaging catheters is that they provide two-dimensional (2D) visualization of the lumen and vessel wall and thus they cannot portray vessel geometry and 3D lesion architecture. To address this limitation computer-based methodologies and user-friendly software have been developed. These are able to off-line process and fuse intravascular imaging data with X-ray or computed tomography coronary angiography (CTCA) to reconstruct coronary artery anatomy. The aim of this review article is to summarize the evolution in the field of coronary artery modeling; we thus present the first methodologies that were developed to model vessel geometry, highlight the modifications introduced in revised methods to overcome the limitations of the first approaches and discuss the challenges that need to be addressed, so these techniques can have broad application in clinical practice and research.

Detecting the Media-adventitia Border in Intravascular Ultrasound Images through a Classification-based Approach

The detection of the media-adventitia (MA) border in intravascular ultrasound (IVUS) images is essential for vessel assessment and disease diagnosis. However, it remains a challenging task, considering the existence of plaque, calcification, and various artifacts. In this article, an effective method based on classification is proposed to extract the MA border in IVUS images. First, a novel morphologic feature describing the relative position of each structure relative to the MA border, called RPES for short, is proposed. Then, the RPES feature and other features are employed in a multiclass extreme learning machine (ELM) to classify IVUS images into nine classes including the MA border and other structures. At last, a modified snake model is employed to effectively detect the MA border in the rectangular domain, in which a modified external force field is constructed on the basis of local border appearances and classification results. The proposed method is evaluated on a public dataset with 77 IVUS images by three indicators in eight situations, such as calcification and a guide wire artifact. With the proposed RPES feature, detection performances are improved by more than 39 percent, which shows an apparent advantage in comparative experiments. Furthermore, compared with two other existing methods used on the same dataset, the proposed method achieves 18 of the best indicators among 24, demonstrating its higher capability in detecting the MA border.

Optimal surface segmentation with convex priors in irregularly sampled space

Optimal surface segmentation is a state-of-the-art method used for segmentation of multiple globally optimal surfaces in volumetric datasets. The method is widely used in numerous medical image segmentation applications. However, nodes in the graph based optimal surface segmentation method typically encode uniformly distributed orthogonal voxels of the volume. Thus the segmentation cannot attain an accuracy greater than a single unit voxel, i.e. the distance between two adjoining nodes in graph space. Segmentation accuracy higher than a unit voxel is achievable by exploiting partial volume information in the voxels which shall result in non-equidistant spacing between adjoining graph nodes. This paper reports a generalized graph based multiple surface segmentation method with convex priors which can optimally segment the target surfaces in an irregularly sampled space. The proposed method allows non-equidistant spacing between the adjoining graph nodes to achieve subvoxel segmentation accuracy by utilizing the partial volume information in the voxels. The partial volume information in the voxels is exploited by computing a displacement field from the original volume data to identify the subvoxel-accurate centers within each voxel resulting in non-equidistant spacing between the adjoining graph nodes. The smoothness of each surface modeled as a convex constraint governs the connectivity and regularity of the surface. We employ an edge-based graph representation to incorporate the necessary constraints and the globally optimal solution is obtained by computing a minimum s-t cut. The proposed method was validated on 10 intravascular multi-frame ultrasound image datasets for subvoxel segmentation accuracy. In all cases, the approach yielded highly accurate results. Our approach can be readily extended to higher-dimensional segmentations.

A pragmatic approach to understand peripheral artery lumen surface stiffness due to plaque heterogeneity

The goal of this study was to develop a pragmatic approach to build patient-specific models of the peripheral artery that are aware of plaque inhomogeneity. Patient-specific models using element-specific material definition (to understand the role of plaque composition) and homogeneous material definition (to understand the role of artery diameter and thickness) were automatically built from intravascular ultrasound images of three artery segments classified with low, average, and high calcification. The element-specific material models had average surface stiffness values of 0.0735, 0.0826, and 0.0973 MPa/mm, whereas the homogeneous material models had average surface stiffness values of 0.1392, 0.1276, and 0.1922 MPa/mm for low, average, and high calcification, respectively. Localization of peak lumen stiffness and differences in patient-specific average surface stiffness for homogeneous and element-specific models suggest the role of plaque composition on surface stiffness in addition to local arterial diameter and thickness.

Computational estimation of the severity of coronary lesions with intravascular ultrasound images: a pilot study

The fast and accurate hemodynamic functional assessment of the coronary vasculature is of utmost importance in clinical practice due to the fact that Cardiovascular Diseases have become the leading cause of death globally. In this work we propose a novel method that combines two of the most efficient methods of hemodynamic status assessment of coronary arteries, Intravascular UtraSound and virtual Functional Assessment Index, an index that correlates well to the measured Fractional Flow Reserve. One Left Anterior Descending segment was reconstructed both in a straight manner (using only IVUS images) as well as using the actual 3D geometry of the vessel (using IvUS images combined with the respective coronary angiographic images [2]). The generated vFAI values were almost identical (Straight=0.80, 3D=0.79), presenting a relative error of 1.27%, thus proving the efficacy of the proposed method. We also calculated the Endothelial Shear Stress for the two models under rest (i.e. flow rate of 1 ml/s), observing a similar trend throughout the artery, but with a statistically important relative error of 13.49%, as expected.

Patient-Specific Computational Models of Coronary Arteries Using Monoplane X-Ray Angiograms

Coronary artery disease (CAD) is the most common type of heart disease in western countries. Early detection and diagnosis of CAD is quintessential to preventing mortality and subsequent complications. We believe hemodynamic data derived from patient-specific computational models could facilitate more accurate prediction of the risk of atherosclerosis. We introduce a semiautomated method to build 3D patient-specific coronary vessel models from 2D monoplane angiogram images. The main contribution of the method is a robust segmentation approach using dynamic programming combined with iterative 3D reconstruction to build 3D mesh models of the coronary vessels. Results indicate the accuracy and robustness of the proposed pipeline. In conclusion, patient-specific modelling of coronary vessels is of vital importance for developing accurate computational flow models and studying the hemodynamic effects of the presence of plaques on the arterial walls, resulting in lumen stenoses, as well as variations in the angulations of the coronary arteries.

Reconstruction of coronary arteries from X-ray angiography: A review

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research.

Validation study of a 3D-QCA coronary reconstruction method using a hybrid intravascular ultrasound and angiography reconstruction method and patient-specific Fractional Flow Reserve data

The estimation of the severity of coronary lesions is of utmost importance in today's clinical practice, since Cardiovascular diseases often have fatal consequences. The most efficient method to estimate the severity of a lesion is the calculation of the Fractional Flow Reserve. The necessary use of a pressure wire, however, makes this method invasive and strenuous for the patient. In this work, we present a novel 3-Dimensional Quantitative Coronary Analysis coronary reconstruction method and a framework for the computation of the virtual Functional Assessment Index (vFAI). In a dataset of 5 coronary arterial segments, we use the aforementioned method to reconstruct them in 3D, and compare them to the respective 3D models reconstructed from our already validated hybrid IVUS-angiography reconstruction method [2]. The obtained results indicate a high correlation between the two methods in terms of the calculated FFR values, presenting a difference of 3.19% in the worst case scenario. Furthermore, when compared to the actual FFR values that derive from a pressure wire, the differences were statistically insignificant.

Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

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.

Evolution of intravascular assessment of coronary anatomy and physiology: from ultrasound imaging to optical and flow assessment

The fact that coronary angiography has limitations in terms of precise estimation and progression of atherosclerosis has been partially overcome during the last years by the use of new techniques. Catheter-based invasive modalities are of a profound clinical importance in regard to accurate assessment of coronary anatomy and physiology and the choice of the appropriate treatment strategy for each patient. Also their potential in clinical investigation projects is of great interest. This current review summarizes the basic principles of these methodologies and evidently highlights not only their use in clinical practice but also their contribution in clinical outcomes.

A new methodology for accurate 3-dimensional coronary artery reconstruction using routine intravascular ultrasound and angiographic data: implications for widespread assessment of endothelial shear stress in humans

AIMS

To develop and validate a new methodology that allows accurate 3-dimensional (3-D) coronary artery reconstruction using standard, simple angiographic and intravascular ultrasound (IVUS) data acquired during routine catheterisation enabling reliable assessment of the endothelial shear stress (ESS) distribution.

METHODS AND RESULTS

Twenty-two patients (22 arteries: 7 LAD; 7 LCx; 8 RCA) who underwent angiography and IVUS examination were included. The acquired data were used for 3-D reconstruction using a conventional method and a new methodology that utilised the luminal 3-D centreline to place the detected IVUS borders and anatomical landmarks to estimate their orientation. The local ESS distribution was assessed by computational fluid dynamics. In corresponding consecutive 3 mm segments, lumen, plaque and ESS measurements in the 3-D models derived by the centreline approach were highly correlated to those derived from the conventional method (r>0.98 for all). The centreline methodology had a 99.5% diagnostic accuracy for identifying segments exposed to low ESS and provided similar estimations to the conventional method for the association between the change in plaque burden and ESS (centreline method: slope= -1.65%/Pa, p=0.078; conventional method: slope= -1.64%/Pa, p=0.084; p =0.69 for difference between the two methodologies).

CONCLUSIONS

The centreline methodology provides geometrically correct models and permits reliable ESS computation. The ability to utilise data acquired during routine coronary angiography and IVUS examination will facilitate clinical investigation of the role of local ESS patterns in the natural history of coronary atherosclerosis.

IVUSAngio tool: a publicly available software for fast and accurate 3D reconstruction of coronary arteries

There is an ongoing research and clinical interest in the development of reliable and easily accessible software for the 3D reconstruction of coronary arteries. In this work, we present the architecture and validation of IVUSAngio Tool, an application which performs fast and accurate 3D reconstruction of the coronary arteries by using intravascular ultrasound (IVUS) and biplane angiography data. The 3D reconstruction is based on the fusion of the detected arterial boundaries in IVUS images with the 3D IVUS catheter path derived from the biplane angiography. The IVUSAngio Tool suite integrates all the intermediate processing and computational steps and provides a user-friendly interface. It also offers additional functionality, such as automatic selection of the end-diastolic IVUS images, semi-automatic and automatic IVUS segmentation, vascular morphometric measurements, graphical visualization of the 3D model and export in a format compatible with other computer-aided design applications. Our software was applied and validated in 31 human coronary arteries yielding quite promising results. Collectively, the use of IVUSAngio Tool significantly reduces the total processing time for 3D coronary reconstruction. IVUSAngio Tool is distributed as free software, publicly available to download and use.

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.

Early detection and invasive passivation of future culprit lesions: a future potential or an unrealistic pursuit of chimeras?

New advances in image and signal processing have allowed the development of numerous invasive and noninvasive imaging modalities that have revealed details of plaque pathology and allowed us to study in vivo the atherosclerotic evolution. Recent natural history of atherosclerosis studies permitted us to evaluate changes in the compositional and morphological characteristics of the plaque and identify predictors of future events. The idea of being able to identify future culprit lesions and passivate these plaques has gradually matured, and small scale studies have provided proofs about the feasibility of this concept. This review article summarizes the recent advances in the study of atherosclerosis, cites the current evidence, highlights our limitations in understanding the evolution of the plaque and in predicting plaque destabilization, and discusses the potentiality of an early invasive sealing of future culprit lesions.

Computational assessment of the fractional flow reserve from intravascular ultrasound and coronary angiography data: a pilot study

Cardiovascular disease is one of the primary causes of morbidity and mortality around the globe. Thus, the diagnosis of critical lesions in coronary arteries is of utmost importance in clinical practice. One useful and efficient method to assess the functional severity of one or multiple lesions in a coronary artery is the calculation of the fractional flow reserve (FFR). In the current work, we present a method which allows the calculation of the FFR value computationally, without the use of a pressure wire and the induction of hyperemia, using intravascular ultrasound (IVUS) and biplane angiography images for three-dimensional (3D) coronary artery reconstruction and measurements of the volumetric flow rate derived from angiographic sequences. The simulated FFR values were compared to the invasively measured FFR values in 7 cases, presenting high correlation (r=0.85) and good agreement (mean difference=0.002). FFR assessment without employing a pressure wire and the induction of hyperemia is feasible using 3D reconstructed coronary artery models from angiographic and IVUS data coupled with computational fluid dynamics.

Endothelial shear stress in the evolution of coronary atherosclerotic plaque and vascular remodelling: current understanding and remaining questions

The heterogeneity of plaque formation, the vascular remodelling response to plaque formation, and the consequent phenotype of plaque instability attest to the extraordinarily complex pathobiology of plaque development and progression, culminating in different clinical coronary syndromes. Atherosclerotic plaques predominantly form in regions of low endothelial shear stress (ESS), whereas regions of moderate/physiological and high ESS are generally protected. Low ESS-induced compensatory expansive remodelling plays an important role in preserving lumen dimensions during plaque progression, but when the expansive remodelling becomes excessive promotes continued influx of lipids into the vessel wall, vulnerable plaque formation and potential precipitation of an acute coronary syndrome. Advanced plaques which start to encroach into the lumen experience high ESS at their most stenotic region, which appears to promote plaque destabilization. This review describes the role of ESS from early atherogenesis to early plaque formation, plaque progression to advanced high-risk stenotic or non-stenotic plaque, and plaque destabilization. The critical implication of the vascular remodelling response to plaque growth is also discussed. Current developments in technology to characterize local ESS and vascular remodelling in vivo may provide a rationale for innovative diagnostic and therapeutic strategies for coronary patients that aim to prevent clinical coronary syndromes.

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.

A novel semiautomated atherosclerotic plaque characterization method using grayscale intravascular ultrasound images: comparison with virtual histology

Intravascular ultrasound (IVUS) virtual histology (VH-IVUS) is a new technique, which provides automated plaque characterization in IVUS frames, using the ultrasound backscattered RF-signals. However, its computation can only be performed once per cardiac cycle (ECG-gated technique), which significantly decreases the number of characterized IVUS frames. Also atherosclerotic plaques in images that have been acquired by machines, which are not equipped with the VH software, cannot be characterized. To address these limitations, we have developed a plaque characterization technique that can be applied in grayscale IVUS images. Our semiautomated method is based on a three-step approach. In the first step, the plaque area [region of interest (ROI)] is detected semiautomatically. In the second step, a set of features is extracted for each pixel of the ROI and in the third step, a random forest classifier is used to classify these pixels into four classes: dense calcium, necrotic core, fibrotic tissue, and fibro-fatty tissue. In order to train and validate our method, we used 300 IVUS frames acquired from virtual histology examinations from ten patients. The overall accuracy of the proposed method was 85.65% suggesting that our approach is reliable and may be further investigated in the clinical and research arena.

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.

Focus on the research utility of intravascular ultrasound - comparison with other invasive modalities

Intravascular ultrasound (IVUS) is an invasive modality which provides cross-sectional images of a coronary artery. In these images both the lumen and outer vessel wall can be identified and accurate estimations of their dimensions and of the plaque burden can be obtained. In addition, further processing of the IVUS backscatter signal helps in the characterization of the type of the plaque and thus it has been used to study the natural history of the atherosclerotic evolution. On the other hand its indigenous limitations do not allow IVUS to assess accurately stent struts coverage, existence of thrombus or exact site of plaque rupture and to identify some of the features associated with increased plaque vulnerability. In order this information to be obtained, other modalities such as optical coherence tomography, angioscopy, near infrared spectroscopy and intravascular magnetic resonance imaging have either been utilized or are under evaluation. The aim of this review article is to present the current utilities of IVUS in research and to discuss its advantages and disadvantages over the other imaging techniques.

The effect of shear stress on neointimal response following sirolimus- and paclitaxel-eluting stent implantation compared with bare-metal stents in humans

OBJECTIVES

We aimed to explore the relationship of neointimal thickness (NT) to shear stress (SS) after implantation of sirolimus-eluting stents (SES) and paclitaxel-eluting stents (PES) compared with bare-metal stents (BMS). We then tested the hypothesis that drug elution attenuates the SS effect.

BACKGROUND

Neointimal thickness after BMS implantation has been associated with SS; pertinent data for drug-eluting stents (DES) are limited.

METHODS

Three-dimensional coronary artery and stent reconstruction was performed in 30 patients at 6-month follow-up after SES (n = 10), PES (n = 10), or BMS (n = 10) implantation. Baseline SS at the stent surface was calculated using computational fluid dynamics and NT at follow-up was computed in 3-dimensional space.

RESULTS

Neointimal thickness was lower in DES versus BMS (0.03 ± 0.07 mm vs. 0.16 ± 0.08 mm, p < 0.001) and maximum NT was reduced in SES versus PES (0.33 ± 0.13 mm vs. 0.46 ± 0.13 mm, p = 0.025). In the total population, both SS (slope: -0.05 mm/Pa, p < 0.001) and DES (coefficient for DES vs. BMS: -0.17 mm, p = 0.003) were independent predictors of NT. Subgroup analysis demonstrated a significant negative relationship of NT to SS in PES (slope: -0.05 mm/Pa, p = 0.016) and BMS (slope: -0.05 mm/Pa, p = 0.001). Sirolimus elution significantly attenuated the effect of SS on NT (interaction coefficient for SES vs. BMS: 0.04 mm/Pa, p = 0.023), whereas the SS effect remained unchanged in PES (interaction coefficient for PES vs. BMS: 0.01 mm/Pa, p = 0.71).

CONCLUSIONS

Neointimal thickness is significantly correlated (inversely) to SS in PES as in BMS. Sirolimus elution abrogates the SS effect on the neointimal response following stent implantation, whereas the SS effect is unchanged in PES.

Lossy JPEG compression in quantitative angiography: the role of X-ray quantum noise

In medical imaging, contrary to applications in the consumer market, the use of irreversible or lossy compression is still in its beginnings. This is due to the suspected risk of compromising the diagnostic content. Many studies have been performed, but it was not until 2008 that national activities in different countries resulted in recommendations for the safe use of irreversible image compression in clinical practice. Quantitative coronary angiography (QCA), however, poses a special problem, since here a large variation in published maximum compression factors has strengthened the general concerns about the use of lossy techniques. Up to now, the reason for the variation has not been thoroughly investigated. Reasons for the discrepancies in published compression factors are determined in this study. Since JPEG compression reduces the quantum noise of the X-ray images, the impact of compression is overestimated when interpreting any change in local diameter as an error. By taking into consideration the quantitative effect of quantum noise in QCA, it is shown that the influence of JPEG compression can be neglected for compression factors up to ten at clinically applicable X-ray doses. This limit is comparable to that found by visual analysis for aesthetic image quality. Future studies on image compression effects should take the interaction with quantum noise explicitly into consideration.

Quantitative coronary angiography in the current era: principles and applications

Coronary angiography, despite its inherent invasiveness and need for contrast media and radiographic exposure, is still routinely employed every year for the diagnostic and therapeutic management of millions of patients with or at risk for coronary artery disease. Whereas approximate visual estimation is the most common way to evaluate coronary angiography findings, since the late 1980s a number of investigators have developed and investigated methods of quantitative coronary angiography (QCA) analysis exploiting automated or semi-automated edge detection. Despite the inherent drawback of QCA due to its focus on the contrast-filled lumen of the vessel, QCA has offered and continues to offer important insights for clinical research and, in selected cases, clinical practice. This review aims thus to provide a comprehensive and updated viewpoint on the actual role of QCA.