Automatic IVUS segmentation of atherosclerotic plaque with Stop & Go snake

Since the upturn of intravascular ultrasound (IVUS)as an imaging technique for the coronary artery system, much research has been done to simplify the complicated analysis of the resulting images. In this study, an attempt to develop an automatic tissue characterization algorithm for IVUS images was done. We concentrated on the segmentation of calcium and soft plaque, because these structures predict the extension and the vulnerability of the atherosclerotic disease, respectively. The first step in the procedure was the extraction of texture features like local binary patterns, co-occurrence matrices and Gabor filter banks. After dimensionality reduction, the resulting feature space was used for classification, constructing a likelihood map to represent different coronary plaques. The information in this map was organized using a recently developed geodesic snake formulation,the so-called Stop & Go snake. The novelty of our study lies in this last step, as it was the first time to apply the Stop & Go snake to segment IVUS images

Thin Cap Fibroatheroma Detection in Virtual Histology Images Using Geometric and Texture Features

Atherosclerotic plaque rupture is the most common mechanism responsible for a majority of sudden coronary deaths. The precursor lesion of plaque rupture is thought to be a thin cap fibroatheroma (TCFA), or “vulnerable plaque”. Virtual Histology-Intravascular Ultrasound (VH-IVUS) images are clinically available for visualising colour-coded coronary artery tissue. However, it has limitations in terms of providing clinically relevant information for identifying vulnerable plaque. The aim of this research is to improve the identification of TCFA using VH-IVUS images. To more accurately segment VH-IVUS images, a semi-supervised model is developed by means of hybrid K-means with Particle Swarm Optimisation (PSO) and a minimum Euclidean distance algorithm (KMPSO-mED). Another novelty of the proposed method is fusion of different geometric and informative texture features to capture the varying heterogeneity of plaque components and compute a discriminative index for TCFA plaque, while the existing research on TCFA detection has only focused on the geometric features. Three commonly used statistical texture features are extracted from VH-IVUS images: Local Binary Patterns (LBP), Grey Level Co-occurrence Matrix (GLCM), and Modified Run Length (MRL). Geometric and texture features are concatenated in order to generate complex descriptors. Finally, Back Propagation Neural Network (BPNN), kNN (K-Nearest Neighbour), and Support Vector Machine (SVM) classifiers are applied to select the best classifier for classifying plaque into TCFA and Non-TCFA. The present study proposes a fast and accurate computer-aided method for plaque type classification. The proposed method is applied to 588 VH-IVUS images obtained from 10 patients. The results prove the superiority of the proposed method, with accuracy rates of 98.61% for TCFA plaque.This research was funded by Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-02G31, and the Ministry of Higher Education Malaysia (MOHE) under the Fundamental Research Grant Scheme (FRGS Vot-4F551) for the completion of the research. The work and the contribution were also supported by the project Smart Solutions in Ubiquitous Computing Environments, Grant Agency of Excellence, University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (under ID: UHK-FIM-GE-2018). Furthermore, the research is also partially supported by the Spanish Ministry of Science, Innovation and Universities with FEDER funds in the project TIN2016-75850-R

Carotid Atheroma Rupture Observed In Vivo and FSI-Predicted Stress Distribution Based on Pre-rupture Imaging

Atherosclerosis at the carotid bifurcation is a major risk factor for stroke. As mechanical forces may impact lesion stability, finite element studies have been conducted on models of diseased vessels to elucidate the effects of lesion characteristics on the stresses within plaque materials. It is hoped that patient-specific biomechanical analyses may serve clinically to assess the rupture potential for any particular lesion, allowing better stratification of patients into the most appropriate treatments. Due to a sparsity of in vivo plaque rupture data, the relationship between various mechanical descriptors such as stresses or strains and rupture vulnerability is incompletely known, and the patient-specific utility of biomechanical analyses is unclear. In this article, we present a comparison between carotid atheroma rupture observed in vivo and the plaque stress distribution from fluid–structure interaction analysis based on pre-rupture medical imaging. The effects of image resolution are explored and the calculated stress fields are shown to vary by as much as 50% with sub-pixel geometric uncertainty. Within these bounds, we find a region of pronounced elevation in stress within the fibrous plaque layer of the lesion with a location and extent corresponding to that of the observed site of plaque rupture

Carotid plaque stress analysis by fluid structure interaction based on in-vivo MRI: Implications to plaque vulnerability assessment

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 2010.Stroke is one of the leading causes of death in the world, resulting mostly from the sudden rupture of atherosclerotic plaques. From a biomechanical view, plaque rupture can be considered as a mechanical failure caused by extremely high plaque stress. In this PhD project, we are aiming to predict 3D plaque stress based on in-vivo MRI by using fluid structure interaction (FSI) method, and provide information for plaque rupture risk assessment. Fluid structure interaction was implemented with ANSYS 11.0, followed by a parameter study on fibrous cap thickness and lipid core size with realistic carotid plaque geometry. Twenty patients with carotid plaques imaged by in-vivo MRI were provided in the project. A framework of reconstructing 3D plaque geometry from in-vivo multispectral MRI was designed. The followed reproducibility study on plaque geometry reconstruction procedure and its effect on plaque stress analysis filled the gap in the literature on imaging based plaque stress modeling. The results demonstrated that current MRI technology can provide sufficient information for plaque structure characterization; however stress analysis result is highly affected by MRI resolution and quality. The application of FSI stress analysis to 4 patients with different plaque burdens has showed that the whole procedure from plaque geometry reconstruction to FSI stress analysis was applicable. In the study, plaque geometries from three patients with recent transient ischemic attack were reconstructed by repairing ruptured fibrous cap. The well correlated relationship between local stress concentrations and plaque rupture sites indicated that extremely high plaque stress could be a factor responsible for plaque rupture. Based on the 20 reconstructed carotid plaques from two groups (symptomatic and asymptomatic), fully coupled fluid structure interaction was performed. It was found that there is a significant difference between symptomatic and asymptomatic patients in plaque stress levels, indicating plaque stress could be used as one of the factors for plaque vulnerability assessment. A corresponding plaque morphological feature study showed that plaque stress is significantly affected by fibrous cap thickness, lipid core size and fibrous cap surface irregularities (curvedness). A procedure was proposed for predicting plaque stress by using fibrous cap thickness and curvedness, which requires much less computational time, and has the potential for clinical routine application. The effects of residual stress on plaque stress analysis and arterial wall material property characterization by using in-vivo MRI data were also discussed for patient specific modeling. As the further development, histological study of plaque sample has been combined with conventional plaque stress analysis by assigning material properties to each computational element, based on the data from histological analysis. This method could bridge the gap between biochemistry and biomechanical study of atherosclerosis plaques. In conclusion, extreme stress distributions in the plaque region can be predicted by modern numerical methods, and used for plaque rupture risk assessment, which will be helpful in clinical practice. The combination of plaque MR imaging analysis, computational modelling, and clinical study/ validation would advance our understandings of plaque rupture, prediction of future rupture, and establish new procedures for patient diagnose, management, and treatment.Financial Support was obtained from British Heart Foundation, Brunel Institute for Bioengineering and Brunel Graduate School

A review of computational methods applied for identification and quantification of atherosclerotic plaques in images

Evaluation of the composition of atherosclerotic plaques in images is an important task to determine their pathophysiology. Visual analysis is still as the most basic and often approach to determine the morphology of the atherosclerotic plaques. In addition, computer-aided methods have also been developed for identification of features such as echogenicity, texture and surface in such plaques. In this article, a review of the most important methodologies that have been developed to identify the main components of atherosclerotic plaques in images is presented. Hence, computational algorithms that take into consideration the analysis of the plaques echogenicity, image processing techniques, clustering algorithms and supervised classification used for segmentation, i.e. identification, of the atherosclerotic plaque components in ultrasound, computerized tomography and magnetic resonance images are introduced. The main contribution of this paper is to provide a categorization of the most important studies related to the segmentation of atherosclerotic plaques and its components in images acquired by the most used imaging modalities. In addition, the effectiveness and drawbacks of each methodology as well as future researches concerning the segmentation and classification of the atherosclerotic lesions are also discussed

Carotid atherosclerotic plaque characterisation by measurement of ultrasound sound speed in vitro at high frequency, 20 MHz

PhDThe first part of the study was to characterise the acoustic properties of an IEC agar-based tissue mimicking material (TMM) at ultrasound frequencies centred around 20 MHz. The TMM acoustic properties measured were the amplitude attenuation coefficient (dB cm-1MHz-1), the sound speed (ms-1) and the backscattered power spectral density characteristics of spectral slope (dB MHz-1), y-axis intercept (dB) and reflected power (dB). The acoustic properties were measured over a temperature range of 22 - 37oC. Both the attenuation coefficient and sound speed, both group and phase, showed good agreement with the expected values of 0.5 dB cm-1 MHz-1 and 1540 ms-1 respectively with average values of 0.49 dB cm-1MHz-1 (st.dev. ± 0.03) and 1541.9 ms-1 (st.dev. ± 8.5). Overall, this non-commercial agar-based TMM was shown to perform as expected at the higher frequency range of 17-23 MHz and was seen to retain its acoustic properties of attenuation and speed of sound over a three year period. For the second part of the study, composite sound speed was measured in carotid plaque embedded in TMM. The IEC TMM was adapted to a clear agar gel. The contour maps from the attenuation plots were used to match the composite sound speed data to the photographic mask of plaque outline and thus the histological data. By solution of sets of simultaneous equations using a matrix inversion, the individual speed values for five plaque components were derived; TMM, elastin, fibrous/collagen, calcification and lipid. The results for derived sound speed in the adapted TMM were consistently close to the expected value of soft tissue, 1540 ms-1. The fibrous tissue showed a mean value of 1584 ms-1 at body temperature, 37oC. The derived sound speeds for elastic and lipid exhibited large inter-quartile ranges. The calcification had a significantly higher sound speed than the other plaque components at 1760 - 2000 ms-1

Quantification of atherosclerotic plaque in the elderly with positron emission tomography/computed tomography

L'athérosclérose est une maladie cardiovasculaire inflammatoire qui est devenue la première cause de morbidité et de mortalité dans les pays développés et parmi les principales causes d’invalidité au monde. Elle se caractérise par l’épaississement de la paroi vasculaire artérielle suite à l'accumulation de lipides et le dépôt d'autres substances au niveau de l’intima (endothélium) pour former la plaque d’athérome. Avec l'âge, cette plaque peut grossir, se calcifier et ainsi rétrécir le calibre de l'artère pour diminuer son débit et à un stade avancé de la maladie, elle peut se rompre et obstruer les petites artères dans n'importe quelle partie du corps causant des complications aigues, y compris la mort soudaine. L'objectif de cette thèse est de pouvoir détecter l'inflammation de la plaque athérosclérotique quantitativement avec la TEP/TDM dans le but de prévenir son détachement. Les mesures avec la TDM et la TEP avec le 18F-FDG ont été acquises chez des sujets humains âgés de 65 à 85 ans. Des analyses quantitatives ont été conduites sur les images de TDM en fonction de l'intensité et des étendues des calcifications, et sur les images de la TEP pour évaluer le métabolisme des plaques. L'effet des traitements par les statines a aussi été étudié. Au-delà la couverture de cette étude de façon détaillée au niveau physiologique en corrélant différents paramètres des plaques, et au niveau méthodologique en utilisant de nouvelles approches pour l'analyse pharmacocinétique, il en ressort principalement la suggestion de la détection de la vulnérabilité de la plaque artérielle par la TDM, plus disponible et moins coûteuse, en remplacement des analyses biochimiques, surtout la protéine C-réactive (CRP) considérée être la méthode standard.Abstract : Atherosclerosis is an inflammatory cardiovascular disease considered the leading cause of morbidity and mortality in developed countries and among the leading causes of disability worldwide. It is characterized by the thickening of the arterial vascular wall due to the accumulation of lipids and the deposition of other substances in the intima (endothelium) to form atheroma plaque. With age, this plaque can grow larger, calcify and thus narrow the size of the artery to decrease blood flow and at an advanced stage of the disease, it can rupture, be transported by blood and block the small arteries in any part of the body causing acute complications, including sudden death. The objective of this thesis was to be able to detect the inflammation of the atherosclerotic plaque quantitatively with PET/CT in order to prevent its detachment. Measurements with CT and PET with 18F-FDG were acquired in human subjects aged 65 to 85 years. Quantitative analyzes were performed on CT images based on the intensity and extent of calcifications, and on PET images to assess plaque metabolism. The effect of statin treatments has also been studied. Beyond the coverage of this study in a detailed manner at the physiological level by correlating different parameters of the plaques, and at the methodological level by using new approaches for pharmacokinetic analysis, it mainly emerges the suggestion for the detection of the vulnerability of the arterial plaque by CT alone, more available and less expensive, replacing biochemical analyzes, especially Creactive protein (CRP) considered to be the standard method