Pub Date : 2024-06-19DOI: 10.1109/TUFFC.2024.3416512
Mostafa Amin Naji, Iman Taghavi, Erik Vilain Thomsen, Niels Bent Larsen, Jorgen Arendt Jensen
Velocity estimation in ultrasound imaging is a technique to measure the speed and direction of blood flow. The flow velocity in small blood vessels, i.e., arterioles, venules, and capillaries, can be estimated using super-resolution ultrasound imaging (SRUS). However, the vessel width in SRUS is relatively small compared with the full-width-half-maximum of the ultrasound beam in the elevation direction (FWHMy), which directly impacts the velocity estimation. By taking into consideration the small vessel widths in SRUS, it is hypothesized that the velocity is underestimated in 2-D super-resolution ultrasound imaging when the vessel diameter is smaller than the FWHMy. A theoretical model is introduced to show that the velocity of a 3-D parabolic velocity profile is underestimated by up to 33% in 2-D SRUS, if the width of the vessel is smaller than the FWHMy. This model was tested using Field II simulations and 3-D printed micro-flow hydrogel phantom measurements. A Verasonics Vantage 256™ scanner and a GE L8-18i-D linear array transducer with FWHMy of approximately 770 μm at the elevation focus were used in the simulations and measurements. Simulations of different parabolic velocity profiles showed that the velocity underestimation was 36.8%±1.5% (mean±standard deviation). The measurements showed that the velocity was underestimated by 30%±6.9%. Moreover, the results of vessel diameters, ranging from 0.125×FWHMy to 3×FWHMy, indicate that velocities are estimated according to the theoretical model. The theoretical model can, therefore, be used for the compensation of velocity estimates under these circumstances.
超声成像中的速度估算是一种测量血流速度和方向的技术。超分辨率超声成像（SRUS）可估算小血管（即动脉、静脉和毛细血管）中的流速。然而，与超声波束在仰角方向的全宽-半最大值（FWHMy）相比，SRUS 中的血管宽度相对较小，这直接影响了流速的估算。考虑到 SRUS 中的血管宽度较小，假设当血管直径小于 FWHMy 时，二维超分辨率超声成像中的速度会被低估。引入的理论模型表明，如果血管宽度小于 FWHMy，二维 SRUS 中三维抛物线速度曲线的速度会被低估 33%。该模型通过 Field II 仿真和三维打印微流水凝胶模型测量进行了测试。模拟和测量中使用了 Verasonics Vantage 256™ 扫描仪和 GE L8-18i-D 线性阵列换能器，在仰角焦点处的 FWHMy 约为 770 μm。对不同抛物线速度剖面的模拟显示，速度低估率为 36.8%±1.5%（平均值±标准偏差）。测量结果显示，速度被低估了 30%±6.9%。此外，血管直径从 0.125×FWHMy 到 3×FWHMy 的结果表明，速度是根据理论模型估算的。因此，在这种情况下，理论模型可用于补偿速度估计值。
{"title":"Underestimation of Flow Velocity in 2-D Super-Resolution Ultrasound Imaging.","authors":"Mostafa Amin Naji, Iman Taghavi, Erik Vilain Thomsen, Niels Bent Larsen, Jorgen Arendt Jensen","doi":"10.1109/TUFFC.2024.3416512","DOIUrl":"10.1109/TUFFC.2024.3416512","url":null,"abstract":"<p><p>Velocity estimation in ultrasound imaging is a technique to measure the speed and direction of blood flow. The flow velocity in small blood vessels, i.e., arterioles, venules, and capillaries, can be estimated using super-resolution ultrasound imaging (SRUS). However, the vessel width in SRUS is relatively small compared with the full-width-half-maximum of the ultrasound beam in the elevation direction (FWHM<sub>y</sub>), which directly impacts the velocity estimation. By taking into consideration the small vessel widths in SRUS, it is hypothesized that the velocity is underestimated in 2-D super-resolution ultrasound imaging when the vessel diameter is smaller than the FWHM<sub>y</sub>. A theoretical model is introduced to show that the velocity of a 3-D parabolic velocity profile is underestimated by up to 33% in 2-D SRUS, if the width of the vessel is smaller than the FWHM<sub>y</sub>. This model was tested using Field II simulations and 3-D printed micro-flow hydrogel phantom measurements. A Verasonics Vantage 256™ scanner and a GE L8-18i-D linear array transducer with FWHM<sub>y</sub> of approximately 770 μm at the elevation focus were used in the simulations and measurements. Simulations of different parabolic velocity profiles showed that the velocity underestimation was 36.8%±1.5% (mean±standard deviation). The measurements showed that the velocity was underestimated by 30%±6.9%. Moreover, the results of vessel diameters, ranging from 0.125×FWHM<sub>y</sub> to 3×FWHM<sub>y</sub>, indicate that velocities are estimated according to the theoretical model. The theoretical model can, therefore, be used for the compensation of velocity estimates under these circumstances.</p>","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141426796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zebrafish has been considered as an essential small-animal model for investigating the mechanism of heart regeneration. Due to the small size of zebrafish heart, high-frequency ultrasound (HFUS) imaging is often required for in vivo evaluations of its dynamic functions. Although commercial HFUS systems are available for myocardial velocity and strain measurement, only the outer myocardial region can be quantified due to the complex structure of zebrafish heart. In this study, a high-resolution 2-D myocardial tissue Doppler and strain imaging based on ultrafast HFUS imaging was developed for zebrafish heart imaging during heart regeneration. The cardiac flow region was first extracted to recognize the myocardial region, and the myocardial velocity and strain were then determined through vector Doppler estimation. Adult AB-line zebrafish was used for in vivo experiments, and cryoinjury was induced in the apical region of the heart. Both the myocardial velocity and strain of the whole ventricle after cryoinjury were directly visualized over 28 days. Myocardial velocity (during later diastolic motion) and strain, respectively, were significantly decreased (anterior wall: −2.0 mm/s and −3.3%; apical region: −2.0 mm/s and −4.5%; and posterior wall (PW): −1.7 mm/s and −4.3%) at the first three days after cryoinjury, which indicates weak myocardial beating due to heart injury. However, these all returned to the baseline values at 14 days after cryoinjury. All of the experimental results indicate that the proposed method is a useful tool for heart regeneration studies in adult zebrafish. In particular, it allows for the noninvasive evaluation of regional dynamic heart function.
{"title":"High-Resolution Tissue Doppler and Strain Imaging for Adult Zebrafish Myocardial Tissue Through Ultrafast High-Frequency Ultrasound Vector Doppler Estimation","authors":"Hsin Huang;Alexander Machikhin;De-Quan Chen;Chih-Chung Huang","doi":"10.1109/TUFFC.2024.3414856","DOIUrl":"10.1109/TUFFC.2024.3414856","url":null,"abstract":"Zebrafish has been considered as an essential small-animal model for investigating the mechanism of heart regeneration. Due to the small size of zebrafish heart, high-frequency ultrasound (HFUS) imaging is often required for in vivo evaluations of its dynamic functions. Although commercial HFUS systems are available for myocardial velocity and strain measurement, only the outer myocardial region can be quantified due to the complex structure of zebrafish heart. In this study, a high-resolution 2-D myocardial tissue Doppler and strain imaging based on ultrafast HFUS imaging was developed for zebrafish heart imaging during heart regeneration. The cardiac flow region was first extracted to recognize the myocardial region, and the myocardial velocity and strain were then determined through vector Doppler estimation. Adult AB-line zebrafish was used for in vivo experiments, and cryoinjury was induced in the apical region of the heart. Both the myocardial velocity and strain of the whole ventricle after cryoinjury were directly visualized over 28 days. Myocardial velocity (during later diastolic motion) and strain, respectively, were significantly decreased (anterior wall: −2.0 mm/s and −3.3%; apical region: −2.0 mm/s and −4.5%; and posterior wall (PW): −1.7 mm/s and −4.3%) at the first three days after cryoinjury, which indicates weak myocardial beating due to heart injury. However, these all returned to the baseline values at 14 days after cryoinjury. All of the experimental results indicate that the proposed method is a useful tool for heart regeneration studies in adult zebrafish. In particular, it allows for the noninvasive evaluation of regional dynamic heart function.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"1006-1018"},"PeriodicalIF":3.0,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141320779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-10DOI: 10.1109/TUFFC.2024.3411718
Hang Jung Ling, Salome Bru, Julia Puig, Florian Vixege, Simon Mendez, Franck Nicoud, Pierre-Yves Courand, Olivier Bernard, Damien Garcia
Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images derived from a patient-specific computational fluid dynamics model and in vivo Doppler acquisitions, both approaches demonstrate comparable reconstruction performance to the original iVFM algorithm. The efficiency of PINNs is boosted through dual-stage optimization and pre-optimized weights. On the other hand, the nnU-Net method excels in generalizability and real-time capabilities. Notably, nnU-Net shows superior robustness on sparse and truncated Doppler data while maintaining independence from explicit boundary conditions. Overall, our results highlight the effectiveness of these methods in reconstructing intraventricular vector blood flow. The study also suggests potential applications of PINNs in ultrafast color Doppler imaging and the incorporation of fluid dynamics equations to derive biomarkers for cardiovascular diseases based on blood flow.
{"title":"Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping.","authors":"Hang Jung Ling, Salome Bru, Julia Puig, Florian Vixege, Simon Mendez, Franck Nicoud, Pierre-Yves Courand, Olivier Bernard, Damien Garcia","doi":"10.1109/TUFFC.2024.3411718","DOIUrl":"10.1109/TUFFC.2024.3411718","url":null,"abstract":"<p><p>Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images derived from a patient-specific computational fluid dynamics model and in vivo Doppler acquisitions, both approaches demonstrate comparable reconstruction performance to the original iVFM algorithm. The efficiency of PINNs is boosted through dual-stage optimization and pre-optimized weights. On the other hand, the nnU-Net method excels in generalizability and real-time capabilities. Notably, nnU-Net shows superior robustness on sparse and truncated Doppler data while maintaining independence from explicit boundary conditions. Overall, our results highlight the effectiveness of these methods in reconstructing intraventricular vector blood flow. The study also suggests potential applications of PINNs in ultrafast color Doppler imaging and the incorporation of fluid dynamics equations to derive biomarkers for cardiovascular diseases based on blood flow.</p>","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"PP ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141300544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Super-resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared with several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time; however, the tracking of uncorrelated and high-density scatterers is quite challenging. This article hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture (SA) imaging, motion estimation, echo canceling, peak detection, and recursive nearest-neighbor (NN) tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125–25- $mu text { m}$ wall-to-wall tube distances, as well as a 3-D printed hydrogel micr-flow phantom with 100–60- $mu text { m}$ wall-to-wall channel distances. The comparison of an in vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-computed tomography (CT) scans with voxel sizes of 26.5 and $5~mu text { m}$ demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.
{"title":"Super-Resolution Ultrasound Imaging Using the Erythrocytes—Part II: Velocity Images","authors":"Mostafa Amin Naji;Iman Taghavi;Mikkel Schou;Sebastian Kazmarek PræSius;Lauge Naur Hansen;Nathalie Sarup Panduro;Sofie Bech Andersen;Stinne Byrholdt Søgaard;Carsten Gundlach;Hans Martin Kjer;Borislav Gueorguiev Tomov;Erik Vilain Thomsen;Michael Bachmann Nielsen;Niels Bent Larsen;Anders Bjorholm Dahl;Charlotte Mehlin Sørensen;Jørgen Arendt Jensen","doi":"10.1109/TUFFC.2024.3411795","DOIUrl":"10.1109/TUFFC.2024.3411795","url":null,"abstract":"Super-resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared with several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time; however, the tracking of uncorrelated and high-density scatterers is quite challenging. This article hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture (SA) imaging, motion estimation, echo canceling, peak detection, and recursive nearest-neighbor (NN) tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125–25-\u0000<inline-formula> <tex-math>$mu text { m}$ </tex-math></inline-formula>\u0000 wall-to-wall tube distances, as well as a 3-D printed hydrogel micr-flow phantom with 100–60-\u0000<inline-formula> <tex-math>$mu text { m}$ </tex-math></inline-formula>\u0000 wall-to-wall channel distances. The comparison of an in vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-computed tomography (CT) scans with voxel sizes of 26.5 and \u0000<inline-formula> <tex-math>$5~mu text { m}$ </tex-math></inline-formula>\u0000 demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"945-959"},"PeriodicalIF":3.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10552297","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141300546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A new approach for vascular super-resolution (SR) imaging using the erythrocytes as targets (SUper-Resolution ultrasound imaging of Erythrocytes (SURE) imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index (MI) for ultrasound scanning for an increased penetration depth. A synthetic aperture (SA) ultrasound sequence was employed with 12 virtual sources (VSs) using a 10-MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was ${1.20}lambda ~text {(185.0}~mu $ m) and the lateral resolution was ${1.50}lambda ~text {(231.3}~mu $ m). Field IIpro simulations were conducted on 12.5- $mu $ m radius vessel pairs with varying separations. A vessel pair with a separation of $70~mu $ m could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging and for 46.8 s for SR imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-computed tomography (CT) contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6- $mu $ m voxel size for 11 h and for 20 h in a 5- $mu $ m voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of $28~mu $ m, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 and 10 s. The vessel structure in the cortex was also similar to the SURE and SR images. Fourier ring correlation (FRC) indicated a resolution capability of $29~mu $ m. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.
{"title":"Super-Resolution Ultrasound Imaging Using the Erythrocytes—Part I: Density Images","authors":"Jørgen Arendt Jensen;Mostafa Amin Naji;Sebastian Kazmarek Præsius;Iman Taghavi;Mikkel Schou;Lauge Naur Hansen;Sofie Bech Andersen;Stinne Byrholdt Søgaard;Nathalie Sarup Panduro;Charlotte Mehlin Sørensen;Michael Bachmann Nielsen;Carsten Gundlach;Hans Martin Kjer;Anders Bjorholm Dahl;Borislav Gueorguiev Tomov;Martin Lind Ommen;Niels Bent Larsen;Erik Vilain Thomsen","doi":"10.1109/TUFFC.2024.3411711","DOIUrl":"10.1109/TUFFC.2024.3411711","url":null,"abstract":"A new approach for vascular super-resolution (SR) imaging using the erythrocytes as targets (SUper-Resolution ultrasound imaging of Erythrocytes (SURE) imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index (MI) for ultrasound scanning for an increased penetration depth. A synthetic aperture (SA) ultrasound sequence was employed with 12 virtual sources (VSs) using a 10-MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was \u0000<inline-formula> <tex-math>${1.20}lambda ~text {(185.0}~mu $ </tex-math></inline-formula>\u0000m) and the lateral resolution was \u0000<inline-formula> <tex-math>${1.50}lambda ~text {(231.3}~mu $ </tex-math></inline-formula>\u0000m). Field IIpro simulations were conducted on 12.5-\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000m radius vessel pairs with varying separations. A vessel pair with a separation of \u0000<inline-formula> <tex-math>$70~mu $ </tex-math></inline-formula>\u0000m could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging and for 46.8 s for SR imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-computed tomography (CT) contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6-\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000m voxel size for 11 h and for 20 h in a 5-\u0000<inline-formula> <tex-math>$mu $ </tex-math></inline-formula>\u0000m voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of \u0000<inline-formula> <tex-math>$28~mu $ </tex-math></inline-formula>\u0000m, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 and 10 s. The vessel structure in the cortex was also similar to the SURE and SR images. Fourier ring correlation (FRC) indicated a resolution capability of \u0000<inline-formula> <tex-math>$29~mu $ </tex-math></inline-formula>\u0000m. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"925-944"},"PeriodicalIF":3.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10552252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141300545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-10DOI: 10.1109/TUFFC.2024.3406071
{"title":"IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Publication Information","authors":"","doi":"10.1109/TUFFC.2024.3406071","DOIUrl":"https://doi.org/10.1109/TUFFC.2024.3406071","url":null,"abstract":"","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 6","pages":"C2-C2"},"PeriodicalIF":3.6,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10552445","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ultrasound elastography is a noninvasive medical imaging technique that maps viscoelastic properties to characterize tissues and diseases. Elastography can be divided into two classes in a broad sense: strain elastography (SE), which relies on Hooke’s law to delineate strain as a surrogate for elasticity, and shear-wave elastography (SWE), which tracks the propagation of shear waves (SWs) in tissues to estimate the elasticity. As tracking the displacement field in the temporal or spatial domain is an inevitable step of both SE and SWE, the success is contingent on the displacement estimation accuracy. Recent reviews mostly focused on clinical applications of elastography, disregarding advances in displacement tracking algorithms. Here, we comprehensively review the recently proposed displacement estimation algorithms applied to both SE and SWE. In addition to cross correlation, block-matching-based (i.e., window-based), model-based, energy-based, and deep learning-based tracking techniques, we review large and lateral displacement tracking, adaptive beamforming, data enhancement, and noise-suppression algorithms facilitating better displacement estimation. We also discuss the simulation models for displacement tracking validation, clinical translation and validation of displacement tracking methods, performance evaluation metrics, and publicly available codes and data for displacement tracking in elastography. Finally, we provide experiential opinions on different tracking algorithms, list the limitations of the current state of elastographic tracking, and comment on possible future research.
超声弹性成像技术是一种非侵入性医学成像技术，通过绘制粘弹性特性图来描述组织和疾病的特征。从广义上讲，弹性成像可分为两类：应变弹性成像（SE）和剪切波弹性成像（SWE），前者依靠胡克定律来确定应变，作为弹性的代用指标；后者则跟踪剪切波在组织中的传播来估计弹性。由于在时间或空间域跟踪位移场是 SE 和 SWE 的必然步骤，因此其成功与否取决于位移估计的准确性。近期的综述大多集中于弹性成像的临床应用，而忽略了位移跟踪算法的进展。在此，我们全面回顾了最近提出的应用于 SE 和 SWE 的位移估计算法。除了交叉相关、块匹配（即基于窗口）、基于模型、基于能量和基于深度学习的跟踪技术外，我们还综述了大位移和横向位移跟踪、自适应波束成形、数据增强和噪声抑制算法，以促进更好的位移估计。我们还讨论了位移跟踪验证的模拟模型、位移跟踪方法的临床转化和验证、性能评估指标以及弹性成像中位移跟踪的公开可用代码和数据。最后，我们就不同的跟踪算法提供了经验意见，列出了弹性成像跟踪现状的局限性，并对未来可能的研究发表了评论。
{"title":"Displacement Tracking Techniques in Ultrasound Elastography: From Cross Correlation to Deep Learning","authors":"Md Ashikuzzaman;Arnaud Héroux;An Tang;Guy Cloutier;Hassan Rivaz","doi":"10.1109/TUFFC.2024.3410671","DOIUrl":"10.1109/TUFFC.2024.3410671","url":null,"abstract":"Ultrasound elastography is a noninvasive medical imaging technique that maps viscoelastic properties to characterize tissues and diseases. Elastography can be divided into two classes in a broad sense: strain elastography (SE), which relies on Hooke’s law to delineate strain as a surrogate for elasticity, and shear-wave elastography (SWE), which tracks the propagation of shear waves (SWs) in tissues to estimate the elasticity. As tracking the displacement field in the temporal or spatial domain is an inevitable step of both SE and SWE, the success is contingent on the displacement estimation accuracy. Recent reviews mostly focused on clinical applications of elastography, disregarding advances in displacement tracking algorithms. Here, we comprehensively review the recently proposed displacement estimation algorithms applied to both SE and SWE. In addition to cross correlation, block-matching-based (i.e., window-based), model-based, energy-based, and deep learning-based tracking techniques, we review large and lateral displacement tracking, adaptive beamforming, data enhancement, and noise-suppression algorithms facilitating better displacement estimation. We also discuss the simulation models for displacement tracking validation, clinical translation and validation of displacement tracking methods, performance evaluation metrics, and publicly available codes and data for displacement tracking in elastography. Finally, we provide experiential opinions on different tracking algorithms, list the limitations of the current state of elastographic tracking, and comment on possible future research.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 7","pages":"842-871"},"PeriodicalIF":3.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10551279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141283555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-05DOI: 10.1109/TUFFC.2024.3409638
Ellen Yeats;Ning Lu;Greyson Stocker;Mahmoud Komaiha;Jonathan R. Sukovich;Zhen Xu;Timothy L. Hall
Histotripsy is a noninvasive ablation technique that focuses ultrasound pulses into the body to destroy tissues via cavitation. Heterogeneous acoustic paths through tissue introduce phase errors that distort and weaken the focus, requiring additional power output from the histotripsy transducer to perform therapy. This effect, termed phase aberration, limits the safety and efficacy of histotripsy ablation. It has been shown in vitro that the phase errors from aberration can be corrected by receiving the acoustic signals emitted by cavitation. For transabdominal histotripsy in vivo, however, cavitation-based aberration correction (AC) is complicated by acoustic signal clutter and respiratory motion. This study develops a method that enables robust, effective cavitation-based AC in vivo and evaluates its efficacy in the swine liver. The method begins with a high-speed pulsing procedure to minimize the effects of respiratory motion. Then, an optimal phase correction is obtained in the presence of acoustic clutter by filtering with the singular value decomposition (SVD). This AC method reduced the power required to generate cavitation in the liver by 26% on average (range: 0%–52%) and required ~2 s for signal acquisition and processing per focus location. These results suggest that the cavitation-based method could enable fast and effective AC for transabdominal histotripsy.
{"title":"In Vivo Cavitation-Based Aberration Correction of Histotripsy in Porcine Liver","authors":"Ellen Yeats;Ning Lu;Greyson Stocker;Mahmoud Komaiha;Jonathan R. Sukovich;Zhen Xu;Timothy L. Hall","doi":"10.1109/TUFFC.2024.3409638","DOIUrl":"10.1109/TUFFC.2024.3409638","url":null,"abstract":"Histotripsy is a noninvasive ablation technique that focuses ultrasound pulses into the body to destroy tissues via cavitation. Heterogeneous acoustic paths through tissue introduce phase errors that distort and weaken the focus, requiring additional power output from the histotripsy transducer to perform therapy. This effect, termed phase aberration, limits the safety and efficacy of histotripsy ablation. It has been shown in vitro that the phase errors from aberration can be corrected by receiving the acoustic signals emitted by cavitation. For transabdominal histotripsy in vivo, however, cavitation-based aberration correction (AC) is complicated by acoustic signal clutter and respiratory motion. This study develops a method that enables robust, effective cavitation-based AC in vivo and evaluates its efficacy in the swine liver. The method begins with a high-speed pulsing procedure to minimize the effects of respiratory motion. Then, an optimal phase correction is obtained in the presence of acoustic clutter by filtering with the singular value decomposition (SVD). This AC method reduced the power required to generate cavitation in the liver by 26% on average (range: 0%–52%) and required ~2 s for signal acquisition and processing per focus location. These results suggest that the cavitation-based method could enable fast and effective AC for transabdominal histotripsy.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"1019-1029"},"PeriodicalIF":3.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-04DOI: 10.1109/TUFFC.2024.3409518
Hanyue Shangguan;Billy Y. S. Yiu;Adrian J. Y. Chee;Alfred C. H. Yu
In the development of ultrasound localization microscopy (ULM) methods, appropriate test beds are needed to facilitate algorithmic performance calibration. Here, we present the design of a new ULM-compatible microvascular phantom with a forked, V-shaped wall-less flow channel pair ( $250~mu $ m channel width) that is bifurcated at a separation rate of $50~mu $ m/mm. The lumen core was fabricated using additive manufacturing, and it was molded within a polyvinyl alcohol (PVA) tissue-mimicking slab using the lost-core casting method. Measured using optical microscopy, the lumen core’s flow channel width was found to be $252~pm ~15~mu $ m with a regression-derived flow channel separation gradient of $50.89~mu $ m/mm. The new phantom’s applicability in ULM performance analysis was demonstrated by feeding microbubble (MB) contrast flow (1.67 to $167~mu $ L/s flow rates) through the phantom’s inlet and generating ULM images with a previously reported method. Results showed that, with longer acquisition times (10 s or longer), ULM image quality was expectedly improved, and the variance of ULM-derived flow channel measurements was reduced. Also, at axial depths near the lumen’s bifurcation point, the current ULM algorithm showed difficulty in properly discerning between the two flow channels because of the narrow channel-to-channel separation distance. Overall, the new phantom serves well as a calibration tool to test the performance of ULM methods in resolving small vasculature.
{"title":"A Forked Microvascular Phantom for Ultrasound Localization Microscopy Investigations","authors":"Hanyue Shangguan;Billy Y. S. Yiu;Adrian J. Y. Chee;Alfred C. H. Yu","doi":"10.1109/TUFFC.2024.3409518","DOIUrl":"10.1109/TUFFC.2024.3409518","url":null,"abstract":"In the development of ultrasound localization microscopy (ULM) methods, appropriate test beds are needed to facilitate algorithmic performance calibration. Here, we present the design of a new ULM-compatible microvascular phantom with a forked, V-shaped wall-less flow channel pair (\u0000<inline-formula> <tex-math>$250~mu $ </tex-math></inline-formula>\u0000m channel width) that is bifurcated at a separation rate of \u0000<inline-formula> <tex-math>$50~mu $ </tex-math></inline-formula>\u0000m/mm. The lumen core was fabricated using additive manufacturing, and it was molded within a polyvinyl alcohol (PVA) tissue-mimicking slab using the lost-core casting method. Measured using optical microscopy, the lumen core’s flow channel width was found to be \u0000<inline-formula> <tex-math>$252~pm ~15~mu $ </tex-math></inline-formula>\u0000m with a regression-derived flow channel separation gradient of \u0000<inline-formula> <tex-math>$50.89~mu $ </tex-math></inline-formula>\u0000m/mm. The new phantom’s applicability in ULM performance analysis was demonstrated by feeding microbubble (MB) contrast flow (1.67 to \u0000<inline-formula> <tex-math>$167~mu $ </tex-math></inline-formula>\u0000L/s flow rates) through the phantom’s inlet and generating ULM images with a previously reported method. Results showed that, with longer acquisition times (10 s or longer), ULM image quality was expectedly improved, and the variance of ULM-derived flow channel measurements was reduced. Also, at axial depths near the lumen’s bifurcation point, the current ULM algorithm showed difficulty in properly discerning between the two flow channels because of the narrow channel-to-channel separation distance. Overall, the new phantom serves well as a calibration tool to test the performance of ULM methods in resolving small vasculature.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 7","pages":"887-896"},"PeriodicalIF":3.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10547348","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141247750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1109/TUFFC.2024.3408314
Shaun McKnight;Vedran Tunukovic;S. Gareth Pierce;Ehsan Mohseni;Richard Pyle;Charles N. MacLeod;Tom O’Hare
In nondestructive evaluation (NDE), accurately characterizing defects within components relies on accurate sizing and localization to evaluate the severity or criticality of defects. This study presents for the first time a deep learning (DL) methodology using 3-D U-Net to localize and size defects in carbon fiber reinforced polymer (CFRP) composites through volumetric segmentation of ultrasonic testing (UT) data. Using a previously developed approach, synthetic training data, closely representative of experimental data, was used for the automatic generation of ground truth segmentation masks. The model’s performance was compared to the conventional amplitude 6 dB drop analysis method used in the industry against ultrasonic defect responses from 40 defects fabricated in CFRP components. The results showed good agreement with the 6 dB drop method for in-plane localization and excellent through-thickness localization, with mean absolute errors (MAEs) of 0.57 and 0.08 mm, respectively. Initial sizing results consistently oversized defects with a 55% higher mean average error than the 6 dB drop method. However, when a correction factor was applied to account for variation between the experimental and synthetic domains, the final sizing accuracy resulted in a 35% reduction in MAE compared to the 6 dB drop technique. By working with volumetric ultrasonic data (as opposed to 2-D images), this approach reduces preprocessing (such as signal gating) and allows for the generation of 3-D defect masks which can be used for the generation of computer-aided design files; greatly reducing the qualification reporting burden of NDE operators.
在无损检测（NDE）中，要准确表征部件内的缺陷，就必须进行准确的尺寸和定位，以评估缺陷的严重性或关键性。本研究首次提出了一种使用三维（3D）U-Net 的深度学习方法，通过对超声波测试数据进行体积分割来定位和确定碳纤维增强聚合物（CFRP）复合材料的缺陷大小。利用之前开发的一种方法，使用与实验数据密切相关的合成训练数据自动生成地面实况分割掩模。针对 CFRP 组件中 40 个缺陷的超声波缺陷响应，将该模型的性能与工业中使用的传统振幅 6 dB 跌落分析方法进行了比较。结果表明，平面内定位与 6 dB 跌落分析法具有良好的一致性，厚度内定位也非常出色，平均绝对误差（MAE）分别为 0.57 毫米和 0.08 毫米。与 6 dB 跌落法相比，初始尺寸测定结果始终过大缺陷，平均误差高出 55%。然而，当应用校正因子来考虑实验域和合成域之间的差异时，最终的尺寸精度比 6 dB 跌落技术的 MAE 降低了 35%。通过使用体积超声波数据（而不是二维图像），这种方法减少了预处理（如信号门控），并允许生成三维缺陷掩模，这些掩模可用于生成计算机辅助设计文件，从而大大减轻了无损检测操作员的鉴定报告负担。
{"title":"Advancing Carbon Fiber Composite Inspection: Deep Learning-Enabled Defect Localization and Sizing via 3-D U-Net Segmentation of Ultrasonic Data","authors":"Shaun McKnight;Vedran Tunukovic;S. Gareth Pierce;Ehsan Mohseni;Richard Pyle;Charles N. MacLeod;Tom O’Hare","doi":"10.1109/TUFFC.2024.3408314","DOIUrl":"10.1109/TUFFC.2024.3408314","url":null,"abstract":"In nondestructive evaluation (NDE), accurately characterizing defects within components relies on accurate sizing and localization to evaluate the severity or criticality of defects. This study presents for the first time a deep learning (DL) methodology using 3-D U-Net to localize and size defects in carbon fiber reinforced polymer (CFRP) composites through volumetric segmentation of ultrasonic testing (UT) data. Using a previously developed approach, synthetic training data, closely representative of experimental data, was used for the automatic generation of ground truth segmentation masks. The model’s performance was compared to the conventional amplitude 6 dB drop analysis method used in the industry against ultrasonic defect responses from 40 defects fabricated in CFRP components. The results showed good agreement with the 6 dB drop method for in-plane localization and excellent through-thickness localization, with mean absolute errors (MAEs) of 0.57 and 0.08 mm, respectively. Initial sizing results consistently oversized defects with a 55% higher mean average error than the 6 dB drop method. However, when a correction factor was applied to account for variation between the experimental and synthetic domains, the final sizing accuracy resulted in a 35% reduction in MAE compared to the 6 dB drop technique. By working with volumetric ultrasonic data (as opposed to 2-D images), this approach reduces preprocessing (such as signal gating) and allows for the generation of 3-D defect masks which can be used for the generation of computer-aided design files; greatly reducing the qualification reporting burden of NDE operators.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 9","pages":"1106-1119"},"PeriodicalIF":3.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141236810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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