Characterization of carotid artery plaques using noninvasive vascular ultrasound elastography

L'athérosclérose est une maladie vasculaire complexe qui affecte la paroi des artères (par l'épaississement) et les lumières (par la formation de plaques). La rupture d'une plaque de l'artère carotide peut également provoquer un accident vasculaire cérébral ischémique et des complications. Bien que plusieurs modalités d'imagerie médicale soient actuellement utilisées pour évaluer la stabilité d'une plaque, elles présentent des limitations telles que l'irradiation, les propriétés invasives, une faible disponibilité clinique et un coût élevé. L'échographie est une méthode d'imagerie sûre qui permet une analyse en temps réel pour l'évaluation des tissus biologiques. Il est intéressant et prometteur d’appliquer une échographie vasculaire pour le dépistage et le diagnostic précoces des plaques d’artère carotide. Cependant, les ultrasons vasculaires actuels identifient uniquement la morphologie d'une plaque en termes de luminosité d'écho ou l’impact de cette plaque sur les caractéristiques de l’écoulement sanguin, ce qui peut ne pas être suffisant pour diagnostiquer l’importance de la plaque. La technique d’élastographie vasculaire non-intrusive (« noninvasive vascular elastography (NIVE) ») a montré le potentiel de détermination de la stabilité d'une plaque. NIVE peut déterminer le champ de déformation de la paroi vasculaire en mouvement d’une artère carotide provoqué par la pulsation cardiaque naturelle. En raison des différences de module de Young entre les différents tissus des vaisseaux, différents composants d’une plaque devraient présenter différentes déformations, caractérisant ainsi la stabilité de la plaque. Actuellement, les performances et l’efficacité numérique sous-optimales limitent l’acceptation clinique de NIVE en tant que méthode rapide et efficace pour le diagnostic précoce des plaques vulnérables. Par conséquent, il est nécessaire de développer NIVE en tant qu’outil d’imagerie non invasif, rapide et économique afin de mieux caractériser la vulnérabilité liée à la plaque. La procédure à suivre pour effectuer l’analyse NIVE consiste en des étapes de formation et de post-traitement d’images. Cette thèse vise à améliorer systématiquement la précision de ces deux aspects de NIVE afin de faciliter la prédiction de la vulnérabilité de la plaque carotidienne. Le premier effort de cette thèse a été dédié à la formation d'images (Chapitre 5). L'imagerie par oscillations transversales a été introduite dans NIVE. Les performances de l’imagerie par oscillations transversales couplées à deux estimateurs de contrainte fondés sur un modèle de déformation fine, soit l’ « affine phase-based estimator (APBE) » et le « Lagrangian speckle model estimator (LSME) », ont été évaluées. Pour toutes les études de simulation et in vitro de ce travail, le LSME sans imagerie par oscillation transversale a surperformé par rapport à l'APBE avec imagerie par oscillations transversales. Néanmoins, des estimations de contrainte principales comparables ou meilleures pourraient être obtenues avec le LSME en utilisant une imagerie par oscillations transversales dans le cas de structures tissulaires complexes et hétérogènes. Lors de l'acquisition de signaux ultrasonores pour la formation d'images, des mouvements hors du plan perpendiculaire au plan de balayage bidimensionnel (2-D) existent. Le deuxième objectif de cette thèse était d'évaluer l'influence des mouvements hors plan sur les performances du NIVE 2-D (Chapitre 6). À cette fin, nous avons conçu un dispositif expérimental in vitro permettant de simuler des mouvements hors plan de 1 mm, 2 mm et 3 mm. Les résultats in vitro ont montré plus d'artefacts d'estimation de contrainte pour le LSME avec des amplitudes croissantes de mouvements hors du plan principal de l’image. Malgré tout, nous avons néanmoins obtenu des estimations de déformations robustes avec un mouvement hors plan de 2.0 mm (coefficients de corrélation supérieurs à 0.85). Pour un jeu de données cliniques de 18 participants présentant une sténose de l'artère carotide, nous avons proposé d'utiliser deux jeux de données d'analyses sur la même plaque carotidienne, soit des images transversales et longitudinales, afin de déduire les mouvements hors plan (qui se sont avérés de 0.25 mm à 1.04 mm). Les résultats cliniques ont montré que les estimations de déformations restaient reproductibles pour toutes les amplitudes de mouvement, puisque les coefficients de corrélation inter-images étaient supérieurs à 0.70 et que les corrélations croisées normalisées entre les images radiofréquences étaient supérieures à 0.93, ce qui a permis de démontrer une plus grande confiance lors de l'analyse de jeu de données cliniques de plaques carotides à l'aide du LSME. Enfin, en ce qui concerne le post-traitement des images, les algorithmes NIVE doivent estimer les déformations des parois des vaisseaux à partir d’images reconstituées dans le but d’identifier les tissus mous et durs. Ainsi, le dernier objectif de cette thèse était de développer un algorithme d'estimation de contrainte avec une résolution de la taille d’un pixel ainsi qu'une efficacité de calcul élevée pour l'amélioration de la précision de NIVE (Chapitre 7). Nous avons proposé un estimateur de déformation de modèle fragmenté (SMSE) avec lequel le champ de déformation dense est paramétré avec des descriptions de transformées en cosinus discret, générant ainsi des composantes de déformations affines (déformations axiales et latérales et en cisaillement) sans opération mathématique de dérivées. En comparant avec le LSME, le SMSE a réduit les erreurs d'estimation lors des tests de simulations, ainsi que pour les mesures in vitro et in vivo. De plus, la faible mise en oeuvre de la méthode SMSE réduit de 4 à 25 fois le temps de traitement par rapport à la méthode LSME pour les simulations, les études in vitro et in vivo, ce qui pourrait permettre une implémentation possible de NIVE en temps réel.Atherosclerosis is a complex vascular disease that affects artery walls (by thickening) and lumens (by plaque formation). The rupture of a carotid artery plaque may also induce ischemic stroke and complications. Despite the use of several medical imaging modalities to evaluate the stability of a plaque, they present limitations such as irradiation, invasive property, low clinical availability and high cost. Ultrasound is a safe imaging method with a real time capability for assessment of biological tissues. It is clinically used for early screening and diagnosis of carotid artery plaques. However, current vascular ultrasound technologies only identify the morphology of a plaque in terms of echo brightness or the impact of the vessel narrowing on flow properties, which may not be sufficient for optimum diagnosis. Noninvasive vascular elastography (NIVE) has been shown of interest for determining the stability of a plaque. Specifically, NIVE can determine the strain field of the moving vessel wall of a carotid artery caused by the natural cardiac pulsation. Due to Young’s modulus differences among different vessel tissues, different components of a plaque can be detected as they present different strains thereby potentially helping in characterizing the plaque stability. Currently, sub-optimum performance and computational efficiency limit the clinical acceptance of NIVE as a fast and efficient method for the early diagnosis of vulnerable plaques. Therefore, there is a need to further develop NIVE as a non-invasive, fast and low computational cost imaging tool to better characterize the plaque vulnerability. The procedure to perform NIVE analysis consists in image formation and image post-processing steps. This thesis aimed to systematically improve the accuracy of these two aspects of NIVE to facilitate predicting carotid plaque vulnerability. The first effort of this thesis has been targeted on improving the image formation (Chapter 5). Transverse oscillation beamforming was introduced into NIVE. The performance of transverse oscillation imaging coupled with two model-based strain estimators, the affine phase-based estimator (APBE) and the Lagrangian speckle model estimator (LSME), were evaluated. For all simulations and in vitro studies, the LSME without transverse oscillation imaging outperformed the APBE with transverse oscillation imaging. Nonetheless, comparable or better principal strain estimates could be obtained with the LSME using transverse oscillation imaging in the case of complex and heterogeneous tissue structures. During the acquisition of ultrasound signals for image formation, out-of-plane motions which are perpendicular to the two-dimensional (2-D) scan plane are existing. The second objective of this thesis was to evaluate the influence of out-of-plane motions on the performance of 2-D NIVE (Chapter 6). For this purpose, we designed an in vitro experimental setup to simulate out-of-plane motions of 1 mm, 2 mm and 3 mm. The in vitro results showed more strain estimation artifacts for the LSME with increasing magnitudes of out-of-plane motions. Even so, robust strain estimations were nevertheless obtained with 2.0 mm out-of-plane motion (correlation coefficients higher than 0.85). For a clinical dataset of 18 participants with carotid artery stenosis, we proposed to use two datasets of scans on the same carotid plaque, one cross-sectional and the other in a longitudinal view, to deduce the out-of-plane motions (estimated to be ranging from 0.25 mm to 1.04 mm). Clinical results showed that strain estimations remained reproducible for all motion magnitudes since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations between radiofrequency images were above 0.93, which indicated that confident motion estimations can be obtained when analyzing clinical dataset of carotid plaques using the LSME. Finally, regarding the image post-processing component of NIVE algorithms to estimate strains of vessel walls from reconstructed images with the objective of identifying soft and hard tissues, we developed a strain estimation method with a pixel-wise resolution as well as a high computation efficiency for improving NIVE (Chapter 7). We proposed a sparse model strain estimator (SMSE) for which the dense strain field is parameterized with Discrete Cosine Transform descriptions, thereby deriving affine strain components (axial and lateral strains and shears) without mathematical derivative operations. Compared with the LSME, the SMSE reduced estimation errors in simulations, in vitro and in vivo tests. Moreover, the sparse implementation of the SMSE reduced the processing time by a factor of 4 to 25 compared with the LSME based on simulations, in vitro and in vivo results, which is suggesting a possible implementation of NIVE in real time

Novel ultrasound features for the identification of the vulnerable carotid plaque

Background: The identification of the vulnerable carotid plaque is of paramount importance in order to prevent the significant stroke-related mortality and morbidity. Currently the clinical decision-making around this condition is based on the traditional ultrasound evaluation of the degree of stenosis. However, there is emerging evidence supporting that this is not sufficient for all patients. Aim of this thesis: The evaluation of novel carotid plaque features for the characterisation of plaque composition, volume and motion using 2 and 3 dimensional ultrasound technology. The ultimate goal is to identify novel sensitive imaging markers for carotid plaque characterisation and stroke-risk stratification. Methods: The Asymptomatic Carotid Stenosis and Risk of Stroke (ACSRS) Study was a large prospective multicentre trial that was recently completed. A post-hoc analysis of the sonographic and clinical data from this study was performed in order to evaluate the effectiveness of novel ultrasound texture features, such as second order statics, on stroke-risk prediction. In addition, the change of specific texture features and degree of stenosis during the ACSRS follow-up time (8 years) and their importance for stroke prediction was evaluated. In order to assess the potential of 3D ultrasound carotid imaging we also developed a special methodology using a 3D broadband, linear array probe and the Q-lab software. This methodology was then applied in a clinical, cross-sectional study of patients with symptomatic and asymptomatic carotid disease. Finally we developed a carotid plaque motion analysis methodology that we tested on a feasibility study. Results: The post-hoc analysis of more than 1, 000 patients from the ACSRS database showed that there are novel ultrasound features of plaque homogeneity that can contribute to plaque characterisation and improve stroke-risk prediction. Similarly our results suggest that the change of degree of stenosis or plaque’s composition through time might have significant predictive value when combined with the above novel features. The study in 3D ultrasound prospectively assessed more than 80 people with symptomatic and asymptomatic carotid disease with both 2 and 3D carotid ultrasound without, though, revealing any significant benefit from the use of 3D imaging in terms of stroke-risk prediction. Finally, our feasibility study on plaque motion analysis showed that it is possible to objectively characterise plaque motion, using ultrasound and dedicated software without complicated reconstructions. Conclusion: The use of novel 2D ultrasound texture features in combination with traditional ones can improve the stroke-risk stratification. 3D ultrasound is a promising new approach, however, the current technology does not appear to offer a significant benefit in comparison to cheaper traditional 2D ultrasound for carotid plaque evaluation. Further research is warranted on this issue.Open Acces

Linking quantitative radiology to molecular mechanism for improved vascular disease therapy selection and follow-up

Objective: Therapeutic advancements in atherosclerotic cardiovascular disease have improved the prevention of ischemic stroke and myocardial infarction. However, diagnostic methods for atherosclerotic plaque phenotyping to aid individualized therapy are lacking. In this thesis, we aimed to elucidate plaque biology through the analysis of computed-tomography angiography (CTA) with sufficient sensitivity and specificity to capture the differentiated drivers of the disease. We then aimed to use such data to calibrate a systems biology model of atherosclerosis with adequate granularity to be clinically relevant. Such development may be possible with computational modeling, but given, the multifactorial biology of atherosclerosis, modeling must be based on complete biological networks that capture protein-protein interactions estimated to drive disease progression. Approach and Results: We employed machine intelligence using CTA paired with a molecular assay to determine cohort-level associations and individual patient predictions. Examples of predicted transcripts included ion transporters, cytokine receptors, and a number of microRNAs. Pathway analyses elucidated enrichment of several biological processes relevant to atherosclerosis and plaque pathophysiology. The ability of the models to predict plaque gene expression from CTAs was demonstrated using sequestered patients with transcriptomes of corresponding lesions. We further performed a case study exploring the relationship between biomechanical quantities and plaque morphology, indicating the ability to determine stress and strain from tissue characteristics. Further, we used a uniquely constituted plaque proteomic dataset to create a comprehensive systems biology disease model, which was finally used to simulate responses to different drug categories in individual patients. Individual patient response was simulated for intensive lipid-lowering, anti-inflammatory drugs, anti-diabetic, and combination therapy. Plaque tissue was collected from 18 patients with 6735 proteins at two locations per patient. 113 pathways were identified and included in the systems biology model of endothelial cells, vascular smooth muscle cells, macrophages, lymphocytes, and the integrated intima, altogether spanning 4411 proteins, demonstrating a range of 39-96% plaque instability. Simulations of drug responses varied in patients with initially unstable lesions from high (20%, on combination therapy) to marginal improvement, whereas patients with initially stable plaques showed generally less improvement, but importantly, variation across patients. Conclusion: The results of this thesis show that atherosclerotic plaque phenotyping by multi-scale image analysis of conventional CTA can elucidate the molecular signatures that reflect atherosclerosis. We further showed that calibrated system biology models may be used to simulate drug response in terms of atherosclerotic plaque instability at the individual level, providing a potential strategy for improved personalized management of patients with cardiovascular disease. These results hold promise for optimized and personalized therapy in the prevention of myocardial infarction and ischemic stroke, which warrants further investigations in larger cohorts

Computer aided diagnosis of coronary artery disease, myocardial infarction and carotid atherosclerosis using ultrasound images: a review

The diagnosis of Coronary Artery Disease (CAD), Myocardial Infarction (MI) and carotid atherosclerosis is of paramount importance, as these cardiovascular diseases may cause medical complications and large number of death. Ultrasound (US) is a widely used imaging modality, as it captures moving images and image features correlate well with results obtained from other imaging methods. Furthermore, US does not use ionizing radiation and it is economical when compared to other imaging modalities. However, reading US images takes time and the relationship between image and tissue composition is complex. Therefore, the diagnostic accuracy depends on both time taken to read the images and experience of the screening practitioner. Computer support tools can reduce the inter-operator variability with lower subject specific expertise, when appropriate processing methods are used. In the current review, we analysed automatic detection methods for the diagnosis of CAD, MI and carotid atherosclerosis based on thoracic and Intravascular Ultrasound (IVUS). We found that IVUS is more often used than thoracic US for CAD. But for MI and carotid atherosclerosis IVUS is still in the experimental stage. Furthermore, thoracic US is more often used than IVUS for computer aided diagnosis systems

Nonrigid Registration of 3-Dimensional Images of the Carotid Arteries

Atherosclerosis at the carotid bifurcation can result in cerebral emboli, which in turn can block the blood supply to the brain causing ischemic strokes. Non-invasive imaging tools that characterize arterial wall, and atherosclerotic plaque structure and composition may help to determine the factors, which lead to the development of unstable lesions, and identify patients at risk of plaque disruption. Registration of 3D ultrasound (US) images of carotid plaque obtained at different time points, and with Magnetic Resonance (MR) images are required for monitoring of plaque changes in volume and surface morphology, and combining the complementary information of the two modalities for better understanding of factors that define plaque vulnerability. These registration techniques should be nonrigid, to remove deformations caused by bending and torsion in the neck during image acquisition sessions. The high degrees of freedom and large number of parameters associated with nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, high computational complexity, and low reliability. Thus, we used a “twisting and bending” model with only six parameters to model the natural movement of the neck for nonrigid registration. We calculated the Mean Registration Error (MRE) between the segmented vessel surfaces in the target and the registered images using the distance between “matched points” to evaluate registration results. We registered 3D US carotid images acquired at different head positions to simulate images acquired at different times, and obtained an average MRE of 0.8±0.3mm for nonrigid registration. We registered 3D US and MR carotid images at field strengths, 1.5T and 3.0T, of the same subject acquired on the same day, and obtained an average MRE of 1.4±0.3mm for 1.5T and 1.5±0.4mm for 3.0T, using nonrigid registration. Furthermore, we showed that the error metric used here was not significantly different from the widely accepted Target Registration Error (TRE)

Association entre l'élastographie vasculaire non invasive et l'indice de masse corporelle chez les enfants

Sachant que l’Athérosclérose commence durant l’enfance par des marqueurs subcliniques, cette étude explore l’association entre l’indice de masse corporelle (IMC) et l’élastographie vasculaire non-invasive (NIVE) des artères carotides communes chez les enfants. On compare aussi les techniques de mesure de l’intima-média (IMT) des artères carotides en se basant sur le mode-B et la radiofréquence (RF) chez les enfants avec IMC normal et élevé. Il s’agit d’une étude prospective effectuée entre 2005 et 2011. Les paramètres de « NIVE » ont été comparés pour deux groupes d’IMC (normal et élevé) de 60 enfants respectivement, faisant tous partie de la cohorte de l’étude QUebec Adipose and Lifestyle Investigation in Youth (QUALITY). Les paramètres de NIVE incluent la contrainte axiale cumulative (CAS) en %, la translation axiale cumulative (CAT) en mm. L’épaisseur de l’intima-média est calculée selon trois méthodes : logiciel «M’ath-Std» (mode-B), « echotracking » des signaux de RF et probabilité de distribution des signaux de RF sur la plateforme NIVE. Une analyse ANOVA et corrélation Pearson ont été effectuées sur le logiciel SAS version 9.3. Une corrélation intra-class (ICC) a été effectuée sur un logiciel MedCalc version 17.2. L’âge moyen était 11,4 ans pour le groupe IMC normal et 12 pour le groupe IMC élevé. Cinquante-huit pourcent étaient des garçons dans le groupe IMC normal et 63% dans le groupe IMC élevé. Les deux groupes étaient différents selon l’âge, stade de Tanner, tension artérielle (systolique et diastolique), et LDL mais similaire pour le sexe. En contrôlant pour les variables confondantes, la CAS n’est pas différente entre les deux groupes. La CAT est plus basse chez les enfants avec IMC normal (CAT=0.51 +/-0.17 mm pour le groupe « IMC normal » et 0.67+/-0.24 mm pour le groupe « IMC élevé » (p<0.001)). Il y a une très faible corrélation entre les trois techniques de mesure d’IMT ICC=0,34 (95% intervalle de confiance 0,27-0,39). L’IMT est significativement plus élevé dans le groupe d’enfants « IMC élevé ». Mode-B (0.55 mm « IMC normal » vs. 0.57 mm « IMC élevé »; p=0.02); IMT RF (0.45 mm « IMC normal » vs. 0.48 mm « IMC élevé »; p=0.03) et IMT probabilité de distribution des signaux RF (0.32 mm « IMC normal » vs. 0.35 mm « IMC élevé »; p=0.010). La NIVE montre une différence significative dans la CAT de l'artère carotide commune des enfants avec un IMC normal par rapport à l'IMC élevé. Des variations significatives de la mesure des IMT ont été observées entre les différentes techniques. Cependant, les enfants avec IMC élevé ont des valeurs IMT plus élevées, indépendamment de la méthode utilisée. Les deux marqueurs subcliniques peuvent être utilisés pour la stratification des enfants à risque de maladies cardiovasculaires. La même méthode devrait toujours être utilisée.Knowing that cardiovascular disease risk factors are present in asymptomatic children, this study explores the association between non-invasive vascular elastography (NIVE) as a subclinical marker of atherosclerosis and obesity in children. In the absence of a gold standard, we also compare B-mode and Radiofrequency (RF) based ultrasound measurements of intima-media thickness (IMT) in children with normal and increased body mass index (BMI). This is a prospective study between 2005 and 2011. NIVE parameters and IMT of the common carotid artery were compared between 60 children with normal BMI and 60 children with increased BMI enrolled in the QUebec Adipose and Lifestyle Investigation in Youth cohort (QUALITY). NIVE parameters included cumulated axial strain (CAS) (%) and cumulated axial translation (CAT) in mm. The three methods of IMT measurements included M’ath Std (B-mode), RF echotracking system and RF probability distribution using NIVE platform. ANOVA analysis and Pearson correlation were calculated using SAS version 9.3. Intra-class correlation coefficient (ICC) and regression analysis was done on MedCalc software version 17.2. The mean age was 11.4 years for the normal BMI group and 12 years for the increased BMI group. Fifty-eight percent were boys in the normal BMI group and 63% in the increased BMI group. The two groups were significantly different with respect to age, Tanner stage, systolic and diastolic blood pressure and were similar with respect to sex. After controlling for confounders, the results show no difference in CAS between the two groups and a significantly lower CAT in the normal BMI group (CAT=0.51+/-0.17 mm for the normal BMI group and 0.67+/-0.24 mm for the increased BMI group (p<0.001)). There is a weak correlation among the three techniques. ICC=0.34 (95% confidence interval (CI): 0.27-0.39). There is however significantly increased IMT in children with increased BMI according to all three techniques. The results were as follow: for B-mode IMT (0.55 mm (normal BMI group) vs. 0.57 mm (increased BMI group); p=0.02); for RF echotracking IMT (0.45 mm (normal BMI group) vs. 0.48 mm (increased BMI group); p=0.03) and for RF probability distribution IMT (0.32 mm (normal BMI group) vs. 0.35 mm (increased BMI group); p=0.010).NIVE is a one-step technique for IMT and CAT measurement in children at risk. Significant IMT measurement variation is observed between the three techniques. However, children with increased BMI tend to have higher IMT values regardless of the technique. Both subclinical markers can be used for optimal stratification of children with cardiovascular disease risk factors. The same technique should be used throughout

The Ultrasound Window Into Vascular Ageing: A Technology Review by the VascAgeNet COST Action

Arteriosclerosis; Ultrasound; Vascular ageingArteriosclerosi; Ecografia; Envelliment vascularArteriosclerosis; Ecografía; Envejecimiento vascularNon-invasive ultrasound (US) imaging enables the assessment of the properties of superficial blood vessels. Various modes can be used for vascular characteristics analysis, ranging from radiofrequency (RF) data, Doppler- and standard B/M-mode imaging, to more recent ultra-high frequency and ultrafast techniques. The aim of the present work was to provide an overview of the current state-of-the-art non-invasive US technologies and corresponding vascular ageing characteristics from a technological perspective. Following an introduction about the basic concepts of the US technique, the characteristics considered in this review are clustered into: 1) vessel wall structure; 2) dynamic elastic properties, and 3) reactive vessel properties. The overview shows that ultrasound is a versatile, non-invasive, and safe imaging technique that can be adopted for obtaining information about function, structure, and reactivity in superficial arteries. The most suitable setting for a specific application must be selected according to spatial and temporal resolution requirements. The usefulness of standardization in the validation process and performance metric adoption emerges. Computer-based techniques should always be preferred to manual measures, as long as the algorithms and learning procedures are transparent and well described, and the performance leads to better results. Identification of a minimal clinically important difference is a crucial point for drawing conclusions regarding robustness of the techniques and for the translation into practice of any biomarker.This article is based upon work from COST Action CA18216 VascAgeNet, supported by COST (European Cooperation in Science and Technology, www.cost.eu). A.G. has received funding from “La Caixa” Foundation (LCF/BQ/PR22/11920008). R.E.C is supported by the National Health and Medical Research Council of Australia (reference: 2009005) and by a National Heart Foundation Future Leader Fellowship (reference: 105636). J.A. acknowledges support from the British Heart Foundation [PG/15/104/31913], the Wellcome EPSRC Centre for Medical Engineering at King's College London [WT 203148/Z/16/Z], and the Cardiovascular MedTech Co-operative at Guy's and St Thomas' NHS Foundation Trust [MIC-2016-019]

Anisotropic behaviour of human gallbladder walls

Inverse estimation of biomechanical parameters of soft tissues from non-invasive measurements has clinical significance in patient-specific modelling and disease diagnosis. In this paper, we propose a fully nonlinear approach to estimate the mechanical properties of the human gallbladder wall muscles from in vivo ultrasound images. The iteration method consists of a forward approach, in which the constitutive equation is based on a modified Hozapfel–Gasser–Ogden law initially developed for arteries. Five constitutive parameters describing the two orthogonal families of fibres and the matrix material are determined by comparing the computed displacements with medical images. The optimisation process is carried out using the MATLAB toolbox, a Python code, and the ABAQUS solver. The proposed method is validated with published artery data and subsequently applied to ten human gallbladder samples. Results show that the human gallbladder wall is anisotropic during the passive refilling phase, and that the peak stress is 1.6 times greater than that calculated using linear mechanics. This discrepancy arises because the wall thickness reduces by 1.6 times during the deformation, which is not predicted by conventional linear elasticity. If the change of wall thickness is accounted for, then the linear model can used to predict the gallbladder stress and its correlation with pain. This work provides further understanding of the nonlinear characteristics of human gallbladder

Ultrasound Imaging

In this book, we present a dozen state of the art developments for ultrasound imaging, for example, hardware implementation, transducer, beamforming, signal processing, measurement of elasticity and diagnosis. The editors would like to thank all the chapter authors, who focused on the publication of this book