705 research outputs found
Mapping Myocardial Elasticity with Intracardiac Acoustic Radiation Force Impulse Methods
<p>Implemented on an intracardiac echocardiography transducer, acoustic radiation force methods may provide a useful means of characterizing the heart's elastic properties. Elasticity imaging may be of benefit for diagnosis and characterization of infarction and heart failure, as well as for guidance of ablation therapy for the treatment of arrhythmias. This thesis tests the hypothesis that with appropriately designed imaging sequences, intracardiac acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) are viable tools for quantification of myocardial elasticity, both temporally and spatially. Multiple track location SWEI (MTL-SWEI) is used to show that, in healthy in vivo porcine ventricles, shear wave speeds follow the elasticity changes with contraction and relaxation of the myocardium, varying between 0.9 and 2.2 m/s in diastole and 2.6 and 5.1 m/s in systole. Infarcted tissue is less contractile following infarction, though not unilaterally stiffer. Single-track-location SWEI (STL-SWEI) is proven to provide suppression of speckle noise and enable improved resolution of structures smaller than 2 mm in diameter compared to ARFI and MTL-SWEI. Contrast to noise ratio and lateral edge resolution are shown to vary with selection of time step for ARFI and arrival time regression filter size for STL-SWEI and MTL-SWEI. </p><p>In 1.5 mm targets, STL-SWEI achieves alternately the tightest resolution (0.3 mm at CNR = 3.5 for a 0.17 mm filter) and highest CNR (8.5 with edge width = 0.7 mm for a 0.66 mm filter) of the modalities, followed by ARFI and then MTL-SWEI.</p><p>In larger, 6 mm targets, the CNR-resolution tradeoff curves for ARFI and STL-SWEI overlap for ARFI time steps up to 0.5 ms and kernels 1 mm for STL-SWEI. STL-SWEI can operate either with a 25 dB improvement over MTL-SWEI in CNR at the same resolution, or with edge widths 5 as narrow at equivalent CNR values, depending on the selection of regression filter size. Ex vivo ablations are used to demonstrate that ARFI, STL-SWEI and MTL-SWEI each resolve ablation lesions between 0.5 and 1 cm in diameter and gaps between lesions smaller than 5 mm in 3-D scans. Differences in contrast, noise, and resolution between the modalities are discussed. All three modalities are also shown to resolve ``x''-shaped ablations up to 22 mm in depth with good visual fidelity and correspondence to surface photographs, with STL-SWEI providing the highest quality images. Series of each type of image, registered using 3-D data from an electroanatomical mapping system, are used to build volumes that show ablations in in vivo canine atria. In vivo images are shown to be subject to increased noise due to tissue and transducer motion, and the challenges facing the proposed system are discussed. Ultimately, intracardiac acoustic radiation force methods are demonstrated to be promising tools for characterizing dynamic myocardial elasticity and imaging radiofrequency ablation lesions.</p>Dissertatio
COMPUTATIONAL ULTRASOUND ELASTOGRAPHY: A FEASIBILITY STUDY
Ultrasound Elastography (UE) is an emerging set of imaging modalities used to assess the biomechanical properties of soft tissues. UE has been applied to numerous clinical applications. Particularly, results from clinical trials of UE in breast lesion differentiation and staging liver fibrosis indicated that there was a lack of confidence in UE measurements or image interpretation. Confidence on UE measurements interpretation is critically important for improving the clinical utility of UE. The primary objective of my thesis is to develop a computational simulation platform based on open-source software packages including Field II, VTK, FEBio and Tetgen. The proposed virtual simulation platform can be used to simulate SE and acoustic radiation force based SWE simulations, including pSWE, SSI and ARFI.
To demonstrate its usefulness, in this thesis, examples for breast cancer detections were provided. The simulated results can reproduce what has been reported in the literature.
To statistically analyze the intrinsic variations of shear wave speed (SWS) in the fibrotic liver tissues, a probability density function (PDF) of the SWS distribution in conjunction with a lossless stochastic tissue model was derived using the principle of Maximum Entropy (ME). The performance of the proposed PDF was evaluated using Monte-Carlo (MC) simulated shear wave data and against three other commonly used PDFs. We theoretically demonstrated that SWS measurements follow a non-Gaussian distribution for the first time. One advantage of the proposed PDF is its physically meaningful parameters. Also, we conducted a case study of the relationship between shear wave measurements and the microstructure of fibrotic liver tissues. Three different virtual tissue models were used to represent underlying microstructures of fibrotic liver tissues.
Furthermore, another innovation of this thesis is the inclusion of “biologically-relevant” fibrotic liver tissue models for simulation of shear wave elastography. To link tissue structure, composition and architecture to the ultrasound measurements directly, a “biologically relevant” tissue model was established using Systems Biology. Our initial results demonstrated that the simulated virtual liver tissues qualitatively could reproduce histological results and wave speed measurements.
In conclusions, these computational tools and theoretical analysis can improve the confidence on UE image/measurements interpretation
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
Ultrasound Based Soft Tissue Elastic Modulus and Strain Measurement
Conventional B-mode ultrasound provides information on the anatomical features using acoustic impedance differences in the tissues. Ultrasound elastography uses a variety of techniques to map soft tissue elasticity. Tissue stiffness is a novel indicator of the tissue health, as many pathologies can alter the tissue stiffness such as cancer and fibrosis. Accurate and early detection of tissue elasticity can guide towards reliable diagnosis, and prognosis of diseases. The objectives of the research reported in this thesis are to implement strain and shear wave elastography techniques on the locally developed ultrasound systems, along with identifying current challenges in elastography and proposing solutions to develop ultrasound elastography as an accurate, and reliable clinical tool.
In the first study, strain elastography was implemented and novel strain estimation quality assessment approach was proposed to discard noisy strain images. The second study proposed a shear wave generation method, called Dual Push Beam (DPB) to address challenges of the current shear wave elastography techniques, such as to reduce data acquisition events and to improve imaging depth. Further, the thesis includes the study which introduced a new angle-aligned shear wave tracking method, which improved displacement estimation quality for shear compounding. Final study designed seven different elastography schemes and investigated variations in elasticity estimation across the image by changing shear waves generation beam parameters such as aperture size and focal depth and its implication for liver fibrosis and breast cancer diagnosis
Quantitative inverse problem in visco-acoustic media under attenuation model uncertainty
We consider the inverse problem of quantitative reconstruction of properties
(e.g., bulk modulus, density) of visco-acoustic materials based on measurements
of responding waves after stimulation of the medium. Numerical reconstruction
is performed by an iterative minimization algorithm. Firstly, we investigate
the robustness of the algorithm with respect to attenuation model uncertainty,
that is, when different attenuation models are used to simulate synthetic
observation data and for the inversion, respectively. Secondly, to handle
data-sets with multiple reflections generated by wall boundaries around the
domain, we perform inversion using complex frequencies, and show that it offers
a robust framework that alleviates the difficulties of multiple reflections. To
illustrate the efficiency of the algorithm, we perform numerical simulations of
ultrasound imaging experiments to reconstruct a synthetic breast sample that
contains an inclusion of high-contrast properties. We perform experiments in
two and three dimensions, where the latter also serves to demonstrate the
numerical feasibility in a large-scale configuration.Comment: 30 pages, 13 figure
Computational ultrasound tissue characterisation for brain tumour resection
In brain tumour resection, it is vital to know where critical neurovascular structuresand tumours are located to minimise surgical injuries and cancer recurrence. Theaim of this thesis was to improve intraoperative guidance during brain tumourresection by integrating both ultrasound standard imaging and elastography in thesurgical workflow. Brain tumour resection requires surgeons to identify the tumourboundaries to preserve healthy brain tissue and prevent cancer recurrence. Thisthesis proposes to use ultrasound elastography in combination with conventionalultrasound B-mode imaging to better characterise tumour tissue during surgery.Ultrasound elastography comprises a set of techniques that measure tissue stiffness,which is a known biomarker of brain tumours. The objectives of the researchreported in this thesis are to implement novel learning-based methods for ultrasoundelastography and to integrate them in an image-guided intervention framework.Accurate and real-time intraoperative estimation of tissue elasticity can guide towardsbetter delineation of brain tumours and improve the outcome of neurosurgery. We firstinvestigated current challenges in quasi-static elastography, which evaluates tissuedeformation (strain) by estimating the displacement between successive ultrasoundframes, acquired before and after applying manual compression. Recent approachesin ultrasound elastography have demonstrated that convolutional neural networkscan capture ultrasound high-frequency content and produce accurate strain estimates.We proposed a new unsupervised deep learning method for strain prediction, wherethe training of the network is driven by a regularised cost function, composed of asimilarity metric and a regularisation term that preserves displacement continuityby directly optimising the strain smoothness. We further improved the accuracy of our method by proposing a recurrent network architecture with convolutional long-short-term memory decoder blocks to improve displacement estimation and spatio-temporal continuity between time series ultrasound frames. We then demonstrateinitial results towards extending our ultrasound displacement estimation method toshear wave elastography, which provides a quantitative estimation of tissue stiffness.Furthermore, this thesis describes the development of an open-source image-guidedintervention platform, specifically designed to combine intra-operative ultrasoundimaging with a neuronavigation system and perform real-time ultrasound tissuecharacterisation. The integration was conducted using commercial hardware andvalidated on an anatomical phantom. Finally, preliminary results on the feasibilityand safety of the use of a novel intraoperative ultrasound probe designed for pituitarysurgery are presented. Prior to the clinical assessment of our image-guided platform,the ability of the ultrasound probe to be used alongside standard surgical equipmentwas demonstrated in 5 pituitary cases
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Free-breathing black-blood CINE fast-spin echo imaging for measuring abdominal aortic wall distensibility: a feasibility study.
The paper reports a free-breathing black-blood CINE fast-spin echo (FSE) technique for measuring abdominal aortic wall motion. The free-breathing CINE FSE includes the following MR techniques: (1) variable-density sampling with fast iterative reconstruction; (2) inner-volume imaging; and (3) a blood-suppression preparation pulse. The proposed technique was evaluated in eight healthy subjects. The inner-volume imaging significantly reduced the intraluminal artifacts of respiratory motion (p  =  0.015). The quantitative measurements were a diameter of 16.3  ±  2.8 mm and wall distensibility of 2.0  ±  0.4 mm (12.5  ±  3.4%) and 0.7  ±  0.3 mm (4.1  ±  1.0%) for the anterior and posterior walls, respectively. The cyclic cross-sectional distensibility was 35  ±  15% greater in the systolic phase than in the diastolic phase. In conclusion, we developed a feasible CINE FSE method to measure the motion of the abdominal aortic wall, which will enable clinical scientists to study the elasticity of the abdominal aorta
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