A "twisting and bending" model-based nonrigid image registration technique for 3-D ultrasound carotid images

Atherosclerosis at the carotid bifurcation resulting in cerebral emboli is a major cause of ischemic stroke. Most strokes associated with carotid atherosclerosis can be prevented by lifestyle/dietary changes and pharmacological treatments if identified early by monitoring carotid plaque changes. Registration of 3-D ultrasound (US) images of carotid plaque obtained at different time points is essential for sensitive monitoring of plaque changes in volume and surface morphology. This registration technique should be nonrigid, since different head positions during image acquisition sessions cause relative bending and torsion in the neck, producing nonlinear deformations between the images. We modeled the movement of the neck using a “twisting and bending” model with only six parameters for nonrigid registration. We evaluated the algorithm using 3-D US carotid images acquired at two different head positions to simulate images acquired at different times. We calculated the mean registration error (MRE) between the segmented vessel surfaces in the target image and the registered image using a distance-based error metric after applying our “twisting and bending” model-based nonrigid registration algorithm. We achieved an average registration error of $0.80 pm 0.26$ mm using our nonrigid registration technique, which was a significant improvement in registration accuracy over rigid registration, even with reduced degrees-of-freedom compared to the other nonrigid registration algorithms.      

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.     

Accuracy of carotid strain estimates from ultrasonic wall tracking: a study based on multiphysics simulations and in vivo data

We used a multiphysics model to assess the accuracy of carotid strain estimates derived from a 1-D ultrasonic wall tracking algorithm. The presented tool integrates fluid-structure interaction (FSI) simulations with an ultrasound simulator (Field II), which allows comparison of the ultrasound (US) images with a ground truth. Field II represents tissue as random points on which US waves reflect and whose position can be updated based on the flow field and vessel wall deformation from FSI. We simulated the RF-signal of a patient-specific carotid bifurcation, including the blood pool as well as the vessel wall and surrounding tissue. Distension estimates were obtained from a wall tracking algorithm using tracking points at various depths within the wall, and further processed to assess radial and circumferential strain. The simulated data demonstrated that circumferential strain can be estimated with reasonable accuracy (especially for the common carotid artery and at the lumen-intima and media-adventitia interface), but the technique does not allow to reliably assess intra-arterial radial strain. These findings were supported by in vivo data of 10 healthy adults, showing similar circumferential and radial strain profiles throughout the arterial wall. We concluded that these deviations are present due to the complex 3-D vessel wall deformation, the presence of specular reflections and, to a lesser extent, the spatially varying beam profile, with the error depending on the phase in the cardiac cycle and the scanning location.     

An integrated system for the segmentation of atherosclerotic carotid plaque.

In this paper, we propose and evaluate an integrated system for the segmentation of atherosclerotic plaque in ultrasound imaging of the carotid artery based on normalization, speckle reduction filtering, and four different snakes segmentation methods. These methods are the Williams and Shah, Balloon, Lai and Chin, and the gradient vector flow (GVF) snake. The performance of the four different plaque snakes segmentation methods was tested on 80 longitudinal ultrasound images of the carotid artery using receiver operating characteristic (ROC) analysis and the manual delineations of an expert. All four methods were very satisfactory and similar in all measures evaluated, with no significant differences between them; however, the Lai and Chin snakes segmentation method gave slightly better results. Concluding, it is proposed that the integrated system investigated in this study could be used successfully for the automated segmentation of the carotid plaque.     

Predictive haemodynamics in a one-dimensional human carotid artery bifurcation. Part II: Application to graft design

A Bayesian surrogate modeling technique is proposed that may be able to predict an optimal bypass graft configuration for patients suffering with stenosis in the internal carotid artery (ICA). At the outset, this statistical technique is considered as a means for identifying key geometric parameters influencing haemodynamics in the human carotid bifurcation. This methodology uses a design of experiments (DoE) technique to generate candidate geometries for flow analysis. A pulsatile one dimensional Navier-Stokes solver incorporating fluid-wall interactions for a Newtonian fluid which predicts pressure and flow in the carotid bifurcation (comprising a stenosed segment in the internal carotid artery) is used for the numerical simulations. Two metrics, pressure variation factor (PVF) and maximum pressure (p(*)(m)) are employed to directly compare the global and local effects, respectively, of variations in the geometry. The values of PVF and p(*)(m) are then used to construct two Bayesian surrogate models. These models are statistically analyzed to visualize how each geometric parameter influences PVF and p(*)(m). Percentage of stenosis is found to influence these pressure based metrics more than any other geometric parameter. Later, we identify bypass grafts with optimal geometric and material properties which have low values of PVF on five test cases with 70%, 75%, 80%, 85%, and 90% stenosis in the ICA, respectively.5%, 80%, 85%, and 90% stenosis in the ICA, 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.     

Computational geometry for patient-specific reconstruction and meshing of blood vessels from MR and CT angiography

Investigation of three-dimensional (3-D) geometry and fluid-dynamics in human arteries is an important issue in vascular disease characterization and assessment. Thanks to recent advances in magnetic resonance (MR) and computed tomography (CT), it is now possible to address the problem of patient-specific modeling of blood vessels, in order to take into account interindividual anatomic variability of vasculature. Generation of models suitable for computational fluid dynamics is still commonly performed by semiautomatic procedures, in general based on operator-dependent tasks, which cannot be easily extended to a significant number of clinical cases. In this paper, we overcome these limitations making use of computational geometry techniques. In particular, 3-D modeling was carried out by means of 3-D level sets approach. Model editing was also implemented ensuring harmonic mean curvature vectors distribution on the surface, and model geometric analysis was performed with a novel approach, based on solving Eikonal equation on Voronoi diagram. This approach provides calculation of central paths, maximum inscribed sphere estimation and geometric characterization of the surface. Generation of adaptive-thickness boundary layer finite elements is finally presented. The use of the techniques presented here makes it possible to introduce patient-specific modeling of blood vessels at clinical level.     

A 3-D Ultrasound-Based Framework to Characterize the Echo Morphology of Carotid Plaques

Carotid atherosclerosis is the main cause of brain stroke, which is the most common life-threatening neurological disease. Nearly all methods aiming at assessing the risk of plaque rupture are based on its characterization from 2-D ultrasound images, which depends on plaque geometry, degree of stenosis, and echo morphology (intensity and texture). The computation of these indicators is, however, usually affected by inaccuracy and subjectivity associated with data acquisition and operator-dependent image selection. To circumvent these limitations, a novel and simple method based on 3-D freehand ultrasound is proposed that does not require any expensive equipment except the common scanner. This method comprises the 3-D reconstruction of carotids and plaques to provide clinically meaningful parameters not available in 2-D ultrasound imaging, namely diagnostic views not usually accessible via conventional techniques and local 3-D characterization of plaque echo morphology. The labeling procedure, based on graph cuts, allows us to identify, locate, and quantify potentially vulnerable foci within the plaque. Validation of the characterization method was made with synthetic data. Results of plaque characterization with real data are encouraging and consistent with the results from conventional methods and after inspection of surgically removed plaques.      

Computational Patient-Specific Models Based on 3-D Ultrasound Data to Quantify Uterine Arterial Flow During Pregnancy

Information on uterine blood flow rate during pregnancy would widely improve our knowledge on feto-placental patho-physiology. Ultrasonographic flow rate evaluation requires the knowledge of the spatial velocity profiles throughout the investigated vessel; these data may be obtained from hemodynamic simulations with accurate computational models. Recently, computational models of superficial vessels have been created using 3-D ultrasound data; unfortunately, common reconstruction methods are unsuitable for the uterine arteries due to the low quality achievable of imaged deep vessels. In this paper a simplified spline-based technique was applied to create computational models for patient-specific simulations of uterine arterial heamodynamics. Moreover, a novel method to quantify the uterine flow rates was developed based on echo-Doppler measurements and computational data. Preliminary results obtained for four patients indicated a quite narrow range for the blood flow rate through the main uterine artery with large variability in the flow split between corporal and cervical branches. Furthermore, parabolic-like velocity profiles were obtained in the branching region of the different patients, suggesting a clinical use of averaged, not patient-specific, spatial velocity distribution coefficients for the blood flow rate calculation. The developed reconstruction method based on 3-D ultrasound imaging is efficient for creating realistic custom models of the uterine arteries. The results of the fluid dynamic simulations allowed us to quantify the uterine arterial flow and its repartition in normal pregnancies.      

Model-based quantitation of 3-D magnetic resonance angiographic images

Quantification of the degree of stenosis or vessel dimensions are important for diagnosis of vascular diseases and planning vascular interventions. Although diagnosis from three-dimensional (3-D) magnetic resonance angiograms (MRA's) is mainly performed on two-dimensional (2-D) maximum intensity projections, automated quantification of vascular segments directly from the 3-D dataset is desirable to provide accurate and objective measurements of the 3-D anatomy. A model-based method for quantitative 3-D MRA is proposed. Linear vessel segments are modeled with a central vessel axis curve coupled to a vessel wall surface. A novel image feature to guide the deformation of the central vessel axis is introduced. Subsequently, concepts of deformable models are combined with knowledge of the physics of the acquisition technique to accurately segment the vessel wall and compute the vessel diameter and other geometrical properties. The method is illustrated and validated on a carotid bifurcation phantom, with ground truth and medical experts as comparisons. Also, results on 3-D time-of-flight (TOF) MRA images of the carotids are shown. The approach is a promising technique to assess several geometrical vascular parameters directly on the source 3-D images, providing an objective mechanism for stenosis grading.     

A reconstruction method for gappy and noisy arterial flow data

Proper orthogonal decomposition (POD), Kriging interpolation, and smoothing are applied to reconstruct gappy and noisy data of blood flow in a carotid artery. While we have applied these techniques to clinical data, in this paper in order to rigorously evaluate their effectiveness we rely on data obtained by computational fluid dynamics (CFD). Specifically, gappy data sets are generated by removing nodal values from high-resolution 3-D CFD data (at random or in a fixed area) while noisy data sets are formed by superimposing speckle noise on the CFD results. A combined POD-Kriging procedure is applied to planar data sets mimicking coarse resolution "ultrasound-like" blood flow images. A method for locating the vessel wall boundary and for calculating the wall shear stress (WSS) is also proposed. The results show good agreement with the original CFD data. The combined POD-Kriging method, enhanced by proper smoothing if needed, holds great potential in dealing effectively with gappy and noisy data reconstruction of in vivo velocity measurements based on color Doppler ultrasound (CDUS) imaging or magnetic resonance angiography (MRA).     

Texture-based classification of atherosclerotic carotid plaques

There are indications that the morphology of atherosclerotic carotid plaques, obtained by high-resolution ultrasound imaging, has prognostic implications. The objective of this study was to develop a computer-aided system that will facilitate the characterization of carotid plaques for the identification of individuals with asymptomatic carotid stenosis at risk of stroke. A total of 230 plaque images were collected which were classified into two types: symptomatic because of ipsilateral hemispheric symptoms, or asymptomatic because they were not connected with ipsilateral hemispheric events. Ten different texture feature sets were extracted from the manually segmented plaque images using the following algorithms: first-order statistics, spatial gray level dependence matrices, gray level difference statistics, neighborhood gray tone difference matrix, statistical feature matrix, Laws texture energy measures, fractal dimension texture analysis, Fourier power spectrum and shape parameters. For the classification task a modular neural network composed of self-organizing map (SOM) classifiers, and combining techniques based on a confidence measure were used. Combining the classification results of the ten SOM classifiers inputted with the ten feature sets improved the classification rate of the individual classifiers, reaching an average diagnostic yield (DY) of 73.1%. The same modular system was implemented using the statistical k-nearest neighbor (KNN) classifier. The combined DY for the KNN system was 68.8%. The results of this paper show that it is possible to identify a group of patients at risk of stroke based on texture features extracted from ultrasound images of carotid plaques. This group of patients may benefit from a carotid endarterectomy whereas other patients may be spared from an unnecessary operation.     

Three-dimensional (3-D) reconstruction of the spine from a single X-ray image and prior vertebra models

The lateral bending test is routinely used by clinicians for the preoperative assessment of spinal mobility. The evaluation of bending motion is usually based on the qualitative analysis of a two-dimensional (2-D) antero-posterior X-ray image. The aim of this paper is to introduce a novel three-dimensional (3-D) reconstruction technique that is a prerequisite for the quantitative 3-D analysis of lateral bending motion. An algorithm was developed for the 3-D reconstruction of the spine from a single X-ray image. The X-ray is calibrated using a small calibration object and an explicit calibration algorithm. The information contained in the single X-ray is completed by registering a priori 3-D geometric models of individual vertebrae. Part of the error yielded by the 3-D/2-D registration is corrected by a vertebral alignment constraint that aims to minimize intervertebral dislocations. Three-dimensional models of 15 different scoliosis patients, obtained from a standard stereo-radiographic 3-D reconstruction, were used in simulation and validation experiments. Experimental results show that the new method is robust and accurate. With pessimistic levels of simulated noise, the average root mean square reconstruction error is 2.89 mm, which is appropriate for common clinical applications.     

In Vivo IVUS-Based 3-D Fluid–Structure Interaction Models With Cyclic Bending and Anisotropic Vessel Properties for Human Atherosclerotic Coronary Plaque Mechanical Analysis

In this paper, a modeling approach combining in vivo intravascular ultrasound (IVUS) imaging, computational modeling, angiography, and mechanical testing is proposed to perform mechanical analysis for human coronary atherosclerotic plaques for potential more accurate plaque vulnerability assessment. A 44-slice in vivo IVUS dataset of a coronary plaque was acquired from one patient, and four 3-D models with fluid-structure interactions (FSIs) based on the data were constructed to quantify effects of anisotropic vessel properties and cyclic bending of the coronary plaque on flow and plaque stress/strain conditions. Compared to the isotropic model (model 1, no bending, no axial stretch), maximum stress-P₁ (maximum principal stress) values on the cut surface with maximum bending (where applicable) from model 2 (anisotropic, no bending, no stretch), model 3 (anisotropic, with bending, no stretch), and model 4 (anisotropic with bending and stretch) were, respectively, 63%, 126%, and 345% higher than that from model 1. Effects of cyclic bending on flow behaviors were modest (5%-15%). Our preliminary results indicated that in vivo IVUS-based FSI models with cyclic bending and anisotropic material properties could improve the accuracies of plaque stress/strain predictions and plaque vulnerability assessment. Large-scale patient studies are needed to further validate our findings.     

Rayleigh mixture model for plaque characterization in intravascular ultrasound

Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology.     

Three-dimensional surface reconstruction using optical flow formedical imaging

The recovery of a three-dimensional (3-D) model from a sequence of two-dimensional (2-D) images is very useful in medical image analysis. Image sequences obtained from the relative motion between the object and the camera or the scanner contain more 3-D information than a single image. Methods to visualize the computed tomograms can be divided into two approaches: the surface rendering approach and the volume rendering approach. In this paper, a new surface rendering method using optical flow is proposed. Optical flow is the apparent motion in the image plane produced by the projection of real 3-D motion onto the 2-D image. The 3-D motion of an object can be recovered from the optical-flow field using additional constraints. By extracting the surface information from 3-D motion, it is possible to obtain an accurate 3-D model of the object. Both synthetic and real image sequences have been used to illustrate the feasibility of the proposed method. The experimental results suggest that the proposed method is suitable for the reconstruction of 3-D models from ultrasound medical images as well as other computed tomograms     

On geometric modeling of the human intracranial venous system

We describe a process aiming to construct a 3-D geometric model of the human normal intracranial venous system from MRA data. An analysis of geometric properties of the intracranial veins and sinuses results in proposing three models: circular, elliptic, and free-shape. We formulate a rule based on which a suitable geometric venous model can be selected. The cross-sectional shape of different parts of dural venous sinuses is found to be better approximated by ellipses and free shapes, while for veins the circular and elliptic models are comparable. An analysis of using splines for radii smoothing is also provided. The approach is useful for building venous models in education and clinical applications.     

ARTreat Project: three-dimensional numerical simulation of plaque formation and development in the arteries

Atherosclerosis is a progressive disease characterized by the accumulation of lipids and fibrous elements in arteries. It is characterized by dysfunction of endothelium and vasculitis, and accumulation of lipid, cholesterol, and cell elements inside blood vessel wall. In this study, a continuum-based approach for plaque formation and development in 3-D is presented. The blood flow is simulated by the 3-D Navier-Stokes equations, together with the continuity equation while low-density lipoprotein (LDL) transport in lumen of the vessel is coupled with Kedem-Katchalsky equations. The inflammatory process was solved using three additional reaction-diffusion partial differential equations. Transport of labeled LDL was fitted with our experiment on the rabbit animal model. Matching with histological data for LDL localization was achieved. Also, 3-D model of the straight artery with initial mild constriction of 30% plaque for formation and development is presented.     

Segmentation of intravascular ultrasound images: a knowledge-based approach

Intravascular ultrasound imaging of coronary arteries provides important information about coronary lumen, wall, and plaque characteristics. Quantitative studies of coronary atherosclerosis using intravascular ultrasound and manual identification of wall and plaque borders are limited by the need for observers with substantial experience and the tedious nature of manual border detection. We have developed a method for segmentation of intravascular ultrasound images that identifies the internal and external elastic laminae and the plaque-lumen interface. The border detection algorithm was evaluated in a set of 38 intravascular ultrasound images acquired from fresh cadaveric hearts using a 30 MHz imaging catheter. To assess the performance of our border detection method we compared five quantitative measures of arterial anatomy derived from computer-detected borders with measures derived from borders manually defined by expert observers. Computer-detected and observer-defined lumen areas correlated very well (r=0.96, y=1.02x+0.52), as did plaque areas (r=0.95, y=1.07x-0.48), and percent area stenosis (r=0.93, y=0.99x-1.34.) Computer-derived segmental plaque thickness measurements were highly accurate. Our knowledge-based intravascular ultrasound segmentation method shows substantial promise for the quantitative analysis of in vivo intravascular ultrasound image data.     

Reconstruction of coronary arteries from a single rotational X-ray projection sequence

Cardiovascular diseases remain the primary cause of death in developed countries. In most cases, exploration of possibly underlying coronary artery pathologies is performed using X-ray coronary angiography. Current clinical routine in coronary angiography is directly conducted in two-dimensional projection images from several static viewing angles. However, for diagnosis and treatment purposes, coronary artery reconstruction is highly suitable. The purpose of this study is to provide physicians with a three-dimensional (3-D) model of coronary arteries, e.g., for absolute 3-D measures for lesion assessment, instead of direct projective measures deduced from the images, which are highly dependent on the viewing angle. In this paper, we propose a novel method to reconstruct coronary arteries from one single rotational X-ray projection sequence. As a side result, we also obtain an estimation of the coronary artery motion. Our method consists of three main consecutive steps: 1) 3-D reconstruction of coronary artery centerlines, including respiratory motion compensation; 2) coronary artery four-dimensional motion computation; 3) 3-D tomographic reconstruction of coronary arteries, involving compensation for respiratory and cardiac motions. We present some experiments on clinical datasets, and the feasibility of a true 3-D Quantitative Coronary Analysis is demonstrated.