Improved shear wave-front reconstruction method by aligning imaging beam angles with shear-wave polarization: Applied for shear compounding application

In shear compounding, shear waves are generated at various angles and individual elasticity maps are averaged to reduce noise and improve accuracy. The steered shear waves tilt the tissue motion direction therefore conventional plane wave tracking is not capable of capturing true shear wave amplitude and direction. The proposed method aligns the tracking beams with the shear wave angles, enables beam-axis in the direction of tissue motion to estimate true shear wave motion vector. In this experimental work, shear waves are produced at five different angles and motion is captured using proposed and conventional method. All the experiments are conducted using inclusion-based elasticity phantom. In the results, the displacement maps show that proposed method accurately captured the steered push-beam wave-fronts while conventional method produced push-beam direction artefacts. In the final compounded elasticity maps, the proposed method slightly improved background-to-inclusion elasticity ratio, CNR by 2 dB, and produced inclusion boundary shape sharper than the conventional tracking

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

Improved shear wave-front reconstruction method by aligning imaging beam angles with shear-wave polarization: Applied for shear compounding application

In shear compounding, shear waves are generated at various angles and individual elasticity maps are averaged to reduce noise and improve accuracy. The steered shear waves tilt the tissue motion direction therefore conventional plane wave tracking is not capable of capturing true shear wave amplitude and direction. The proposed method aligns the tracking beams with the shear wave angles, enables beam-axis in the direction of tissue motion to estimate true shear wave motion vector. In this experimental work, shear waves are produced at five different angles and motion is captured using proposed and conventional method. All the experiments are conducted using inclusion-based elasticity phantom. In the results, the displacement maps show that proposed method accurately captured the steered push-beam wave-fronts while conventional method produced push-beam direction artefacts. In the final compounded elasticity maps, the proposed method slightly improved background-to-inclusion elasticity ratio, CNR by 2 dB, and produced inclusion boundary shape sharper than the conventional tracking. © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

A Novel Two-Dimensional Displacement Estimation for Angled Shear Wave Elastography

This study aimed to estimate angled tissue motion for shear wave compounding applications. Shear wave elastography produces the quantitative elasticity biomarker for assessing the health status of tissues. In sheer wave compounding, steered shear waves are generated with different angles, and individual angle elasticity maps are averaged to improve tissue stiffness reconstruction. When shear waves are steered and the tissue motion is generated in multiple directions, traditional one dimensional (1D) displacement estimation fails in capturing actual shear wave amplitude and direction. This study investigated the use of two dimensional (2D) kernel to track angular shear wave motion, which resulted in the underestimation of displacement values. Consequently, a new method named as 2D proposed (2D-P) was used to calculate both axial and lateral motion components separately using 1D axial and lateral kernels. Final results indicated that, the proposed scheme produced an average improvement of 2.01 μm and 4.4 μm compared with the 1D axial cross correlation and 2D cross correlation based methods, respectively

Utility Of Shear Wave Elastography In Breast Cancer Diagnosis: A Systematic Review And Meta-Analysis

In the United States, breast cancer is one of the most diagnosed cancers in women. Early detection, often via mammography, and intervention have been shown to reduce mortality. However, not all cancers are mammographically evident in early stages, if at all. As a result, ultrasound has been increasingly used to supplement mammography for breast cancer detection and assessment, particularly in dense breasts. Recent advancements in ultrasonography include the ability to characterize the stiffness of biological tissues. Shear Wave Elastography (SWE) is one such development used to quantify tissue stiffness within a region of interest. The resistance of soft tissue to deformation depends on the molecular makeup of the tissue components as well as elements of tissue structure, such as stromal and connective tissue. As tumor growth often involves architectural changes that cause increased stiffness compared to normal neighboring tissue, SWE has the potential to compliment mammography and B-mode ultrasound for breast lesion characterization. Studies establishing the clinical value of SWE may aid in its incorporation into diagnostic guidelines. This study aimed to quantify the performance of 2D SWE for differentiating benign and malignant breast lesions in women with abnormal mammography via a systematic review of the literature and meta-analysis. A systematic search of PubMed, Scopus, Embase, Ovid-Medline, Cochrane Library and Web of Science was performed. Studies of diagnostic accuracy published prior to June 2021 using SWE to evaluate abnormal breast tissue with at least 50 lesions that reported quantitative shear wave speed (SWS) parameters (the mean (SWSmean), maximum (SWSmax), minimum (SWSmin), or standard deviation (SWSSD) of the SWS) and thresholds and included a reference standard of either biopsy or 2-year stability were included in the analysis. The QUADAS- 2 tool was used to assess possible bias within studies as well as their applicability. 87 studies of diagnostic accuracy were included, encompassing 17,810 women (47) with 19,043 lesions (7,623 malignant). A hierarchical summary receiver operating characteristic model produced the following summary sensitivities and specificities: 0.86 [0.83, 0.88] / 0.87 [0.84, 0.88] for SWSmean, 0.83 [0.80, 0.85]/ 0.88 [0.86, 0.90] for SWSmax, 0.86 [0.74, 0.93]/ 0.81 [0.69, 0.89] for SWSmin, and 0.82 [0.77, 0.86] / 0.88 [0.85, 0.91] for SWSSD, respectively. By calculating and utilizing the resulting likelihood ratios, SWE was shown capable of downgrading BI-RADS 4a and upgrading BI-RADS 3 lesions. Thus, SWE has the potential to provide increased discriminative power in the diagnosis of breast cancer if used synergistically with mammography and B-mode ultrasound. Current society guidelines do not provide definitive recommendations about the role of SWE in screening and diagnosis, nor its counterpart strain elastography (SE). The literature suggests that a combination of SE and SWE may provide better discriminatory power than SWE alone and serve as an adjunct to current diagnostic techniques, opening an avenue for future study

Multi-Foci Beamforming Using Curved Linear Array Transducer for Qualitative Identification of Lipids in Human Liver

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of liver chronic diseases in the U.S. and its prevalence is growing in the world. In the United States, it affects an estimate of 80 to 100 million people. In less than a decade, NAFLD will likely become the number one cause of liver transplants in the country. NAFLD cases have risen rapidly over the last three decades and is the most common liver disease in children. NAFLD encompasses a disease spectrum of a variety of liver conditions ranging from simple steatosis (SS) to nonalcoholic steatohepatitis (NASH). SS is a benign form of the disease, characterized by the accumulation of lipid in the liver. On the other hand, NASH is defined by hepatic steatosis with cell injury, hepatic ballooning and various degrees of fibrosis. NASH may further develop into cirrhosis, liver failure and hepatocellular carcinoma (HCC). A non-invasive, early detection and accurate staging of NAFLD may allow for a timely intervention and treatment to prevent the progression of the disease to cirrhosis and HCC. We hypothesized a new dual-modality ultrasound imaging combining acoustic radiation force impulse (ARFI) imaging and thermal strain imaging (TSI) implemented on a clinical ultrasound probe. ARFI imaging utilizes high intensity focused ultrasound to generate a push in a region of interest (ROI). The response of the tissue inside the region of excitation due to the acoustic radiation push is determined by estimating the displacement between the pre-push reference frames and the post-push tracking frames. TSI has been used in the field of medical imaging for detecting lipids in atherosclerotic plaques and quantification of liver fat in ob/ob mice. TSI is based on the fact that the speed of sound changes differently in respect to the increase in temperature for different tissue composition. Lipids register a decreasing sound speed with increasing temperature, whereas water-bearing tissue exhibit an increasing sound speed with increasing temperature. Development of the proposed multi-modality system will be a step towards a novel clinical system which would permit the creation of a single co-registered image featuring information regarding lipid content and liver stiffness

Evaluation of shear wave speed measurements using crawling waves sonoelastography and single tracking location acoustic radiation force impulse imaging

Many pathological conditions are closely related with an increase in tissue sti ness. For many years, experts performed manual palpation in order to measure elasticity changes, however, this method can only be applied on superficial areas of the human body and provides crude sti ness estimation. Elastography is a technique that attempts to characterize the elastic properties of tissue in order to provide additional and useful information for clinical diagnosis. For more than twenty years, di erent research groups have developed various elastography modalities with a strong interest for quantitative images during the last decade. Recently, comparative studies among di erent elastographic techniques have been performed in order to better characterize biomaterials, to cross-validate several shear wave elastographic modalities and to study the factors that influence their precision and accuracy. This comparison works may contribute to achieve standardization in quantitative elastography and their use in commercial equipment for their application in human patients. However, there is still a limited literature in the field of quantitative elastography modalities comparisons. This thesis focuses on the comparison between two elastographic techniques: crawling wave sonoelastography (CWS) and single tracking location-acoustic radiation force impulse (STL-ARFI). The comparison shows the estimation of the shear wave speed (SWS), lateral resolution, contrast and contrast-to-noise ratio (CNR) in homogeneous and inhomogeneous phantoms using both techniques. The SWS values obtained with both modalities are validated with mechanical measurements that are considered as ground truth. The SWS results for the three di erent homogeneous phantoms (10%, 13%, and 16% gelatin concentrations), show good agreement between CWS, STL-ARFI and mechanical measurements as a function of frequency. The maximum accuracy errors obtained with CWS were 2.52%, 1.63% and 2.26%. For STL-ARFI, the maximum errors were 6.22%, 5.63% and 4.08% for the 10%,13% and 16% gelatin phantom respectively. For lateral resolution, contrast and CNR estimated in the inhomogeneous phantoms, it can be seen that for vibration frequencies higher than 340 Hz, CWS presents better results than the obtained with STL-ARFI using distances between the push beams ( x) higher than 4 mm. However, using these vibration frequencies will not be feasible for in vivo tissues due to attenuation problems. It that sense, for lower vibration frequencies than 300 Hz and x among 3 mm and 6 mm, comparable lateral resolution, contrast and CNR was obtained. Finally, the results of this study contribute to the data currently available for comparing elastographic techniques. Moreover, the methodology implemented in this document may be helpful for future standardization for di erent elastographic modalities.Tesi

Ultrasound shear wave imaging for diagnosis of nonalcoholic fatty liver disease

Pour le diagnostic et la stratification de la fibrose hépatique, la rigidité du foie est un biomarqueur quantitatif estimé par des méthodes d'élastographie. L'élastographie par ondes de cisaillement (« shear wave », SW) utilise des ultrasons médicaux non invasifs pour évaluer les propriétés mécaniques du foie sur la base des propriétés de propagation des ondes de cisaillement. La vitesse des ondes de cisaillement (« shear wave speed », SWS) et l'atténuation des ondes de cisaillement (« shear wave attenuation », SWA) peuvent fournir une estimation de la viscoélasticité des tissus. Les tissus biologiques sont intrinsèquement viscoélastiques et un modèle mathématique complexe est généralement nécessaire pour calculer la viscoélasticité en imagerie SW. Le calcul précis de l'atténuation est essentiel, en particulier pour une estimation précise du module de perte et de la viscosité. Des études récentes ont tenté d'augmenter la précision de l'estimation du SWA, mais elles présentent encore certaines limites. Comme premier objectif de cette thèse, une méthode de décalage de fréquence revisitée a été développée pour améliorer les estimations fournies par la méthode originale de décalage en fréquence [Bernard et al 2017]. Dans la nouvelle méthode, l'hypothèse d'un paramètre de forme décrivant les caractéristiques spectrales des ondes de cisaillement, et assumé initialement constant pour tous les emplacements latéraux, a été abandonnée permettant un meilleur ajustement de la fonction gamma du spectre d'amplitude. En second lieu, un algorithme de consensus d'échantillons aléatoires adaptatifs (« adaptive random sample consensus », A-RANSAC) a été mis en œuvre pour estimer la pente du paramètre de taux variable de la distribution gamma afin d’améliorer la précision de la méthode. Pour valider ces changements algorithmiques, la méthode proposée a été comparée à trois méthodes récentes permettant d’estimer également l’atténuation des ondes de cisaillements (méthodes de décalage en fréquence, de décalage en fréquence en deux points et une méthode ayant comme acronyme anglophone AMUSE) à l'aide de données de simulations ou fantômes numériques. Également, des fantômes de gels homogènes in vitro et des données in vivo acquises sur le foie de canards ont été traités. Comme deuxième objectif, cette thèse porte également sur le diagnostic précoce de la stéatose hépatique non alcoolique (NAFLD) qui est nécessaire pour prévenir sa progression et réduire la mortalité globale. À cet effet, la méthode de décalage en fréquence revisitée a été testée sur des foies humains in vivo. La performance diagnostique de la nouvelle méthode a été étudiée sur des foies humains sains et atteints de la maladie du foie gras non alcoolique. Pour minimiser les sources de variabilité, une méthode d'analyse automatisée faisant la moyenne des mesures prises sous plusieurs angles a été mise au point. Les résultats de cette méthode ont été comparés à la fraction de graisse à densité de protons obtenue de l'imagerie par résonance magnétique (« magnetic resonance imaging proton density fat fraction », MRI-PDFF) et à la biopsie du foie. En outre, l’imagerie SWA a été utilisée pour classer la stéatose et des seuils de décision ont été établis pour la dichotomisation des différents grades de stéatose. Finalement, le dernier objectif de la thèse consiste en une étude de reproductibilité de six paramètres basés sur la technologie SW (vitesse, atténuation, dispersion, module de Young, viscosité et module de cisaillement). Cette étude a été réalisée chez des volontaires sains et des patients atteints de NAFLD à partir de données acquises lors de deux visites distinctes. En conclusion, une méthode robuste de calcul du SWA du foie a été développée et validée pour fournir une méthode de diagnostic de la NAFLD.For diagnosis and staging of liver fibrosis, liver stiffness is a quantitative biomarker estimated by elastography methods. Ultrasound shear wave (SW) elastography utilizes noninvasive medical ultrasound to assess the mechanical properties of the liver based on the monitoring of the SW propagation. SW speed (SWS) and SW attenuation (SWA) can provide an estimation of tissue viscoelasticity. Biological tissues are inherently viscoelastic in nature and a complex mathematical model is usually required to compute viscoelasticity in SW imaging. Accurate computation of attenuation is critical, especially for accurate loss modulus and viscosity estimation. Recent studies have made attempts to increase the precision of SWA estimation, but they still face some limitations. As a first objective of this thesis, a revisited frequency-shift method was developed to improve the estimates provided by the original implementation of the frequency-shift method [Bernard et al 2017]. In the new method, the assumption of a constant shape parameter of the gamma function describing the SW magnitude spectrum has been dropped for all lateral locations, allowing a better gamma fitting. Secondly, an adaptive random sample consensus algorithm (A-RANSAC) was implemented to estimate the slope of the varying rate parameter of the gamma distribution to improve the accuracy of the method. For the validation of these algorithmic changes, the proposed method was compared with three recent methods proposed to estimate SWA (frequency-shift, two-point frequency-shift and AMUSE methods) using simulation data or numerical phantoms. In addition, in vitro homogenous gel phantoms and in vivo animal (duck) liver data were processed. As a second objective, this thesis also aimed at improving the early diagnosis of nonalcoholic fatty liver disease (NAFLD), which is necessary to prevent its progression and decrease the overall mortality. For this purpose, the revisited frequency-shift method was tested on in vivo human livers. The new method's diagnosis performance was investigated with healthy and NAFLD human livers. To minimize sources of variability, an automated analysis method averaging measurements from several angles has been developed. The results of this method were compared to the magnetic resonance imaging proton density fat fraction (MRI-PDFF) and to liver biopsy. SWA imaging was used for grading steatosis and cut-off decision thresholds were established for dichotomization of different steatosis grades. As a third objective, this thesis is proposing a reproducibility study of six SW-based parameters (speed, attenuation, dispersion, Young’s modulus, viscosity and shear modulus). The assessment was performed in healthy volunteers and NAFLD patients using data acquired at two separate visits. In conclusion, a robust method for computing the liver’s SWA was developed and validated to provide a diagnostic method for NAFLD

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