There is widespread interest and concern about the evidence and hypothesis that the auditory system is involved in ultrasound neuromodulation. We have addressed this problem by performing acoustic shear wave simulations in mouse skull and behavioral experiments in deaf mice. The simulation results showed that shear waves propagating along the skull did not reach sufficient acoustic pressure in the auditory cortex to modulate neurons. Behavioral experiments were subsequently performed to awaken anesthetized mice with ultrasound targeting the motor cortex or ventral tegmental area (VTA). The experimental results showed that ultrasound stimulation (US) of the target areas significantly increased arousal scores even in deaf mice, whereas the loss of ultrasound gel abolished the effect. Immunofluorescence staining also showed that ultrasound can modulate neurons in the target area, whereas neurons in the auditory cortex required the involvement of the normal auditory system for activation. In summary, the shear waves propagating along the skull cannot reach the auditory cortex and induce neuronal activation. Ultrasound neuromodulation-induced arousal behavior needs direct action on functionally relevant stimulation targets in the absence of auditory system participation.
{"title":"Spatiotemporal Distributions of Acoustic Propagation in Skull During Ultrasound Neuromodulation","authors":"Wen Meng;Zhengrong Lin;Yanchang Lu;Xiaojing Long;Long Meng;Chang Su;Zhiqiong Wang;Lili Niu","doi":"10.1109/TUFFC.2024.3383027","DOIUrl":"10.1109/TUFFC.2024.3383027","url":null,"abstract":"There is widespread interest and concern about the evidence and hypothesis that the auditory system is involved in ultrasound neuromodulation. We have addressed this problem by performing acoustic shear wave simulations in mouse skull and behavioral experiments in deaf mice. The simulation results showed that shear waves propagating along the skull did not reach sufficient acoustic pressure in the auditory cortex to modulate neurons. Behavioral experiments were subsequently performed to awaken anesthetized mice with ultrasound targeting the motor cortex or ventral tegmental area (VTA). The experimental results showed that ultrasound stimulation (US) of the target areas significantly increased arousal scores even in deaf mice, whereas the loss of ultrasound gel abolished the effect. Immunofluorescence staining also showed that ultrasound can modulate neurons in the target area, whereas neurons in the auditory cortex required the involvement of the normal auditory system for activation. In summary, the shear waves propagating along the skull cannot reach the auditory cortex and induce neuronal activation. Ultrasound neuromodulation-induced arousal behavior needs direct action on functionally relevant stimulation targets in the absence of auditory system participation.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 5","pages":"584-595"},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140335509","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 : 2024-03-28DOI: 10.1109/TUFFC.2024.3378051
{"title":"IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control Publication Information","authors":"","doi":"10.1109/TUFFC.2024.3378051","DOIUrl":"https://doi.org/10.1109/TUFFC.2024.3378051","url":null,"abstract":"","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 4","pages":"C2-C2"},"PeriodicalIF":3.6,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10485186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140321671","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 : 2024-03-26DOI: 10.1109/TUFFC.2024.3381451
Suzi Liang;Bradley E. Treeby;Eleanor Martin
Existing data on the acoustic properties of low-temperature biological materials is limited and widely dispersed across fields. This makes it difficult to employ this information in the development of ultrasound applications in the medical field, such as cryosurgery and rewarming of cryopreserved tissues. In this review, the low-temperature acoustic properties of biological materials, and the measurement methods used to acquire them were collected from a range of scientific fields. The measurements were reviewed from the acoustic setup to thermal methodologies for samples preparation, temperature monitoring, and system insulation. The collected data contain the longitudinal and shear velocity, and attenuation coefficient of biological soft tissues and biologically relevant substances—water, aqueous solutions, and lipids—in the temperature range down to −50 °C and in the frequency range from 108 kHz to 25 MHz. The multiple reflection method (MRM) was found to be the preferred method for low-temperature samples, with a buffer rod inserted between the transducer and sample to avoid direct contact. Longitudinal velocity changes are observed through the phase transition zone, which is sharp in pure water, and occurs more slowly and at lower temperatures with added solutes. Lipids show longer transition zones with smaller sound velocity changes; with the longitudinal velocity changes observed during phase transition in tissues lying between these two extremes. More general conclusions on the shear velocity and attenuation coefficient at low-temperatures are restricted by the limited data. This review enhance knowledge guiding for further development of ultrasound applications in low-temperature biomedical fields, and may help to increase the precision and standardization of low-temperature acoustic property measurements.
{"title":"Review of the Low-Temperature Acoustic Properties of Water, Aqueous Solutions, Lipids, and Soft Biological Tissues","authors":"Suzi Liang;Bradley E. Treeby;Eleanor Martin","doi":"10.1109/TUFFC.2024.3381451","DOIUrl":"10.1109/TUFFC.2024.3381451","url":null,"abstract":"Existing data on the acoustic properties of low-temperature biological materials is limited and widely dispersed across fields. This makes it difficult to employ this information in the development of ultrasound applications in the medical field, such as cryosurgery and rewarming of cryopreserved tissues. In this review, the low-temperature acoustic properties of biological materials, and the measurement methods used to acquire them were collected from a range of scientific fields. The measurements were reviewed from the acoustic setup to thermal methodologies for samples preparation, temperature monitoring, and system insulation. The collected data contain the longitudinal and shear velocity, and attenuation coefficient of biological soft tissues and biologically relevant substances—water, aqueous solutions, and lipids—in the temperature range down to −50 °C and in the frequency range from 108 kHz to 25 MHz. The multiple reflection method (MRM) was found to be the preferred method for low-temperature samples, with a buffer rod inserted between the transducer and sample to avoid direct contact. Longitudinal velocity changes are observed through the phase transition zone, which is sharp in pure water, and occurs more slowly and at lower temperatures with added solutes. Lipids show longer transition zones with smaller sound velocity changes; with the longitudinal velocity changes observed during phase transition in tissues lying between these two extremes. More general conclusions on the shear velocity and attenuation coefficient at low-temperatures are restricted by the limited data. This review enhance knowledge guiding for further development of ultrasound applications in low-temperature biomedical fields, and may help to increase the precision and standardization of low-temperature acoustic property measurements.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 5","pages":"607-620"},"PeriodicalIF":3.6,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293380","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 : 2024-03-26DOI: 10.1109/TUFFC.2024.3381923
Cornelis van Damme;Gandhika K. Wardhana;Andrada Iulia Velea;Vasiliki Giagka;Tiago L. Costa
In the emerging research field of bioelectronic medicine, it has been indicated that neuromodulation of the vagus nerve (VN) has the potential to treat various conditions such as epilepsy, depression, and autoimmune diseases. In order to reduce side effects, as well as to increase the effectiveness of the delivered therapy, sub-fascicle stimulation specificity is required. In the electrical domain, increasing spatial selectivity can only be achieved using invasive and potentially damaging approaches like compressive forces or nerve penetration. To avoid these invasive methods while obtaining a high spatial selectivity, a 2-mm diameter extraneural cuff-shaped proof-of-concept design with integrated lead zirconate titanate (PZT) based ultrasound (US) transducers is proposed in this article. For the development of the proposed concept, wafer-level microfabrication techniques are employed. Moreover, acoustic measurements are performed on the device, in order to characterize the ultrasonic beam profiles of the integrated PZT-based US transducers. A focal spot size of around $200times 200,,mu text{m}$ is measured for the proposed cuff. Moreover, the curvature of the device leads to constructive interference of the US waves originating from multiple PZT-based US transducers, which in turn leads to an increase of 45% in focal pressure compared to the focal pressure of a single PZT-based US transducer. Integrating PZT-based US transducers in an extraneural cuff-shaped design has the potential to achieve high-precision US neuromodulation of the VN without requiring intraneural implantation.
在新兴的生物电子医学研究领域，对迷走神经（VN）的神经调控具有治疗癫痫、抑郁症和自身免疫性疾病等多种疾病的潜力。为了减少副作用并提高治疗效果，需要对椎下神经束进行特异性刺激。在电学领域，提高空间选择性只能通过压迫力或神经穿透等具有潜在破坏性的侵入性方法来实现。为了在获得高空间选择性的同时避免这些侵入性方法，本文提出了一种直径为 2 毫米的硬膜外袖带形概念验证设计，其中集成了基于锆钛酸铅（PZT）的超声（US）换能器。为开发所提出的概念，采用了晶圆级微加工技术。此外，还对设备进行了声学测量，以确定基于 PZT 的集成 US 传感器的超声波束轮廓。测量结果表明，拟议袖套的焦斑尺寸约为 200 μm x 200 μm。此外，该装置的弧度会导致来自多个 PZT US 传感器的 US 波发生建设性干扰，这反过来又会导致焦点压力比单个 PZT US 传感器的焦点压力增加 45%。将基于 PZT 的 US 传感器集成到硬膜外袖带设计中，有可能实现对迷走神经的高精度 US 神经调控，而无需进行硬膜内植入。
{"title":"Feasibility Study for a High-Frequency Flexible Ultrasonic Cuff for High-Precision Vagus Nerve Ultrasound Neuromodulation","authors":"Cornelis van Damme;Gandhika K. Wardhana;Andrada Iulia Velea;Vasiliki Giagka;Tiago L. Costa","doi":"10.1109/TUFFC.2024.3381923","DOIUrl":"10.1109/TUFFC.2024.3381923","url":null,"abstract":"In the emerging research field of bioelectronic medicine, it has been indicated that neuromodulation of the vagus nerve (VN) has the potential to treat various conditions such as epilepsy, depression, and autoimmune diseases. In order to reduce side effects, as well as to increase the effectiveness of the delivered therapy, sub-fascicle stimulation specificity is required. In the electrical domain, increasing spatial selectivity can only be achieved using invasive and potentially damaging approaches like compressive forces or nerve penetration. To avoid these invasive methods while obtaining a high spatial selectivity, a 2-mm diameter extraneural cuff-shaped proof-of-concept design with integrated lead zirconate titanate (PZT) based ultrasound (US) transducers is proposed in this article. For the development of the proposed concept, wafer-level microfabrication techniques are employed. Moreover, acoustic measurements are performed on the device, in order to characterize the ultrasonic beam profiles of the integrated PZT-based US transducers. A focal spot size of around \u0000<inline-formula> <tex-math>$200times 200,,mu text{m}$ </tex-math></inline-formula>\u0000 is measured for the proposed cuff. Moreover, the curvature of the device leads to constructive interference of the US waves originating from multiple PZT-based US transducers, which in turn leads to an increase of 45% in focal pressure compared to the focal pressure of a single PZT-based US transducer. Integrating PZT-based US transducers in an extraneural cuff-shaped design has the potential to achieve high-precision US neuromodulation of the VN without requiring intraneural implantation.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 7","pages":"745-756"},"PeriodicalIF":3.0,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293379","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 : 2024-03-26DOI: 10.1109/TUFFC.2024.3382231
Chengyang Huang;Ali Zare Hosseinzadeh;Francesco Lanza di Scalea
Ultrasonic synthetic aperture focus techniques (SAFTs) using less than the total number of available array elements to transmit (“sparse” transmissions) have been recently used in both medical imaging and industrial nondestructive testing (NDT) imaging to increase test speed and simplify multiplexer hardware. The challenge of sparse arrays is to obtain a reasonable image quality given the reduced transmitter–receiver combinations available to the beamforming process. This article proposes a “ultrasparse” SAFT method that employs a minimum number of transmitter elements (from one to four elements only) to obtain an entire full-matrix capture (FMC) set of waveforms. Specifically, a “virtual” FMC is obtained from normalized cross-power spectra between each array element pair in an implementation of “passive” ultrasonic sensing. In order to maintain high image quality without sacrificing imaging speed (e.g., applying a minimal initial time delay and keeping a short time recording window), several key steps have to be taken in this “passive” imaging mode, specifically: 1) the use of carefully designed segment-averaged normalized cross-power spectrum (NCPS) for robust passive reconstruction of the ultrasonic impulse response function (IRF) between two receivers; 2) the use of both the causal and acausal portions of the passively reconstructed IRFs; and 3) the compounding of multiple wave modes in the beamforming process. These steps also ensure the elimination of the near-field blind zone hence potentially enabling near-field imaging. The article first reviews the theory of passive IRF reconstruction between two receivers, comparing time-averaged cross correlation versus segment-averaged NCPS, and then demonstrates the application to ultrasparse SAFT FMC imaging of drilled holes in an aluminum block using a linear transducer array where only one to four elements are used in transmission.
{"title":"Ultrasparse Ultrasonic Synthetic Aperture Focus Imaging by Passive Sensing","authors":"Chengyang Huang;Ali Zare Hosseinzadeh;Francesco Lanza di Scalea","doi":"10.1109/TUFFC.2024.3382231","DOIUrl":"10.1109/TUFFC.2024.3382231","url":null,"abstract":"Ultrasonic synthetic aperture focus techniques (SAFTs) using less than the total number of available array elements to transmit (“sparse” transmissions) have been recently used in both medical imaging and industrial nondestructive testing (NDT) imaging to increase test speed and simplify multiplexer hardware. The challenge of sparse arrays is to obtain a reasonable image quality given the reduced transmitter–receiver combinations available to the beamforming process. This article proposes a “ultrasparse” SAFT method that employs a minimum number of transmitter elements (from one to four elements only) to obtain an entire full-matrix capture (FMC) set of waveforms. Specifically, a “virtual” FMC is obtained from normalized cross-power spectra between each array element pair in an implementation of “passive” ultrasonic sensing. In order to maintain high image quality without sacrificing imaging speed (e.g., applying a minimal initial time delay and keeping a short time recording window), several key steps have to be taken in this “passive” imaging mode, specifically: 1) the use of carefully designed segment-averaged normalized cross-power spectrum (NCPS) for robust passive reconstruction of the ultrasonic impulse response function (IRF) between two receivers; 2) the use of both the causal and acausal portions of the passively reconstructed IRFs; and 3) the compounding of multiple wave modes in the beamforming process. These steps also ensure the elimination of the near-field blind zone hence potentially enabling near-field imaging. The article first reviews the theory of passive IRF reconstruction between two receivers, comparing time-averaged cross correlation versus segment-averaged NCPS, and then demonstrates the application to ultrasparse SAFT FMC imaging of drilled holes in an aluminum block using a linear transducer array where only one to four elements are used in transmission.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 5","pages":"518-535"},"PeriodicalIF":3.6,"publicationDate":"2024-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140293435","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 : 2024-03-25DOI: 10.1109/TUFFC.2024.3381529
Xufei Chen;Xueting Li;Simona Turco;Ruud J. G. van Sloun;Massimo Mischi
Ultrasound elastography (USE) is a promising tool for tissue characterization as several diseases result in alterations of tissue structure and composition, which manifest as changes in tissue mechanical properties. By imaging the tissue response to an applied mechanical excitation, USE mimics the manual palpation performed by clinicians to sense the tissue elasticity for diagnostic purposes. Next to elasticity, viscosity has recently been investigated as an additional, relevant, diagnostic biomarker. Moreover, since biological tissues are inherently viscoelastic, accounting for viscosity in the tissue characterization process enhances the accuracy of the elasticity estimation. Recently, methods exploiting different acquisition and processing techniques have been proposed to perform ultrasound viscoelastography. After introducing the physics describing viscoelasticity, a comprehensive overview of the currently available USE acquisition techniques is provided, followed by a structured review of the existing viscoelasticity estimators classified according to the employed processing technique. These estimators are further reviewed from a clinical usage perspective, and current outstanding challenges are discussed.
超声弹性成像（USE）是一种用于组织特征描述的前景广阔的工具，因为多种疾病会导致组织结构和组成发生变化，表现为组织机械性能的变化。通过对组织对外加机械激励的反应进行成像，超声弹性成像模拟了临床医生为诊断目的而进行的手动触诊，以感知组织的弹性。除弹性外，粘度最近也被研究为另一种相关的诊断生物标志物。此外，由于生物组织本身具有粘弹性，在组织特征描述过程中考虑粘度可提高弹性估算的准确性。最近，人们提出了利用不同的采集和处理技术来进行超声粘弹性成像的方法。在介绍了描述粘弹性的物理学原理后，对目前可用的 USE 采集技术进行了全面概述，随后根据所采用的处理技术对现有的粘弹性估算器进行了结构性审查。从临床应用的角度对这些估算器进行了进一步评述，并讨论了当前面临的挑战。
{"title":"Ultrasound Viscoelastography by Acoustic Radiation Force: A State-of-the-Art Review","authors":"Xufei Chen;Xueting Li;Simona Turco;Ruud J. G. van Sloun;Massimo Mischi","doi":"10.1109/TUFFC.2024.3381529","DOIUrl":"10.1109/TUFFC.2024.3381529","url":null,"abstract":"Ultrasound elastography (USE) is a promising tool for tissue characterization as several diseases result in alterations of tissue structure and composition, which manifest as changes in tissue mechanical properties. By imaging the tissue response to an applied mechanical excitation, USE mimics the manual palpation performed by clinicians to sense the tissue elasticity for diagnostic purposes. Next to elasticity, viscosity has recently been investigated as an additional, relevant, diagnostic biomarker. Moreover, since biological tissues are inherently viscoelastic, accounting for viscosity in the tissue characterization process enhances the accuracy of the elasticity estimation. Recently, methods exploiting different acquisition and processing techniques have been proposed to perform ultrasound viscoelastography. After introducing the physics describing viscoelasticity, a comprehensive overview of the currently available USE acquisition techniques is provided, followed by a structured review of the existing viscoelasticity estimators classified according to the employed processing technique. These estimators are further reviewed from a clinical usage perspective, and current outstanding challenges are discussed.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 5","pages":"536-557"},"PeriodicalIF":3.6,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140287342","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 : 2024-03-25DOI: 10.1109/TUFFC.2024.3379293
Olivier Lombard;Emilie Franceschini
Quantitative ultrasound (QUS) techniques based on the backscatter coefficient (BSC) aim to characterize the scattering properties of biological tissues. A scattering model is fit to the measured BSC, and the fitted QUS parameters can provide local tissue microstructure, namely, scatterer size and acoustic concentration. However, these techniques may fail to provide a correct description of tissue microstructure when the medium is polydisperse and/or dense. The objective of this study is to investigate the effects of scatterer size polydispersity in sparse or dense media on the QUS estimates. Four scattering models (i.e., the monodisperse and polydisperse sparse models, and the monodisperse and polydisperse concentrated models based on the structure factor) are compared to assess their accuracy and reliability in quantifying the QUS estimates. Simulations are conducted with different scatterer size distributions for sparse, moderately dense, and dense media (volume fractions of 1%, 20%, and 73%, respectively). The QUS parameters are estimated by using model-based inverse methods at different center frequencies between 8 and 50 MHz. Experimental data are also analyzed using colon adenocarcinoma HT29 cell pellet biophantoms to further validate the results obtained from simulations at the volume fraction of 73%. Our findings reveal that the choice of scattering model has a significant impact on the accuracy of QUS estimates. For sufficiently high frequencies and dense media, the polydisperse concentrated model outperforms the other models and enables more accurate quantification. Furthermore, our results contribute to advancing our understanding of the complexities associated with scatterer size polydispersity and dense media in spectral-based QUS techniques.
{"title":"Effects of Size Polydispersity and Dense Media on Quantitative Ultrasound Estimates","authors":"Olivier Lombard;Emilie Franceschini","doi":"10.1109/TUFFC.2024.3379293","DOIUrl":"10.1109/TUFFC.2024.3379293","url":null,"abstract":"Quantitative ultrasound (QUS) techniques based on the backscatter coefficient (BSC) aim to characterize the scattering properties of biological tissues. A scattering model is fit to the measured BSC, and the fitted QUS parameters can provide local tissue microstructure, namely, scatterer size and acoustic concentration. However, these techniques may fail to provide a correct description of tissue microstructure when the medium is polydisperse and/or dense. The objective of this study is to investigate the effects of scatterer size polydispersity in sparse or dense media on the QUS estimates. Four scattering models (i.e., the monodisperse and polydisperse sparse models, and the monodisperse and polydisperse concentrated models based on the structure factor) are compared to assess their accuracy and reliability in quantifying the QUS estimates. Simulations are conducted with different scatterer size distributions for sparse, moderately dense, and dense media (volume fractions of 1%, 20%, and 73%, respectively). The QUS parameters are estimated by using model-based inverse methods at different center frequencies between 8 and 50 MHz. Experimental data are also analyzed using colon adenocarcinoma HT29 cell pellet biophantoms to further validate the results obtained from simulations at the volume fraction of 73%. Our findings reveal that the choice of scattering model has a significant impact on the accuracy of QUS estimates. For sufficiently high frequencies and dense media, the polydisperse concentrated model outperforms the other models and enables more accurate quantification. Furthermore, our results contribute to advancing our understanding of the complexities associated with scatterer size polydispersity and dense media in spectral-based QUS techniques.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 5","pages":"572-583"},"PeriodicalIF":3.6,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140287341","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 : 2024-03-24DOI: 10.1109/TUFFC.2024.3404997
Sergei Vostrikov;Matteo Anderegg;Luca Benini;Andrea Cossettini
Wearable ultrasound (US) is a novel sensing approach that shows promise in multiple application domains, and specifically in hand gesture recognition (HGR). In fact, US enables to collect information from deep musculoskeletal structures at high spatiotemporal resolution and high signal-to-noise ratio, making it a perfect candidate to complement surface electromyography for improved accuracy performance and on-the-edge classification. However, existing wearable solutions for US-based gesture recognition are not sufficiently low power for continuous, long-term operation. On top of that, practical hardware limitations of wearable US devices (limited power budget, reduced wireless throughput, and restricted computational power) set the need for the compressed size of models for feature extraction and classification. To overcome these limitations, this article presents a novel end-to-end approach for feature extraction from raw musculoskeletal US data suited for edge computing, coupled with an armband for HGR based on a truly wearable (12 cm2, 9 g), ultralow-power (ULP) (16 mW) US probe. The proposed approach uses a 1-D convolutional autoencoder (CAE) to compress raw US data by $20times $ while preserving the main amplitude features of the envelope signal. The latent features of the autoencoder are used to train an XGBoost classifier for HGR on datasets collected with a custom US armband, considering armband removal/repositioning in between sessions. Our approach achieves a classification accuracy of 96%. Furthermore, the proposed unsupervised feature extraction approach offers generalization capabilities for intersubject use, as demonstrated by testing the pretrained encoder on a different subject and conducting posttraining analysis, revealing that the operations performed by the encoder are subject-independent. The autoencoder is also quantized to 8-bit integers and deployed on a ULP wearable US probe along with the XGBoost classifier, allowing for a gesture recognition rate $geq 25$ Hz and leading to 21% lower power consumption [at 30 frames/s (FPS)] compared to the conventional approach (raw data transmission and remote processing).
{"title":"Unsupervised Feature Extraction From Raw Data for Gesture Recognition With Wearable Ultralow-Power Ultrasound","authors":"Sergei Vostrikov;Matteo Anderegg;Luca Benini;Andrea Cossettini","doi":"10.1109/TUFFC.2024.3404997","DOIUrl":"10.1109/TUFFC.2024.3404997","url":null,"abstract":"Wearable ultrasound (US) is a novel sensing approach that shows promise in multiple application domains, and specifically in hand gesture recognition (HGR). In fact, US enables to collect information from deep musculoskeletal structures at high spatiotemporal resolution and high signal-to-noise ratio, making it a perfect candidate to complement surface electromyography for improved accuracy performance and on-the-edge classification. However, existing wearable solutions for US-based gesture recognition are not sufficiently low power for continuous, long-term operation. On top of that, practical hardware limitations of wearable US devices (limited power budget, reduced wireless throughput, and restricted computational power) set the need for the compressed size of models for feature extraction and classification. To overcome these limitations, this article presents a novel end-to-end approach for feature extraction from raw musculoskeletal US data suited for edge computing, coupled with an armband for HGR based on a truly wearable (12 cm2, 9 g), ultralow-power (ULP) (16 mW) US probe. The proposed approach uses a 1-D convolutional autoencoder (CAE) to compress raw US data by \u0000<inline-formula> <tex-math>$20times $ </tex-math></inline-formula>\u0000 while preserving the main amplitude features of the envelope signal. The latent features of the autoencoder are used to train an XGBoost classifier for HGR on datasets collected with a custom US armband, considering armband removal/repositioning in between sessions. Our approach achieves a classification accuracy of 96%. Furthermore, the proposed unsupervised feature extraction approach offers generalization capabilities for intersubject use, as demonstrated by testing the pretrained encoder on a different subject and conducting posttraining analysis, revealing that the operations performed by the encoder are subject-independent. The autoencoder is also quantized to 8-bit integers and deployed on a ULP wearable US probe along with the XGBoost classifier, allowing for a gesture recognition rate \u0000<inline-formula> <tex-math>$geq 25$ </tex-math></inline-formula>\u0000 Hz and leading to 21% lower power consumption [at 30 frames/s (FPS)] compared to the conventional approach (raw data transmission and remote processing).","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 7","pages":"831-841"},"PeriodicalIF":3.0,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141092680","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 : 2024-03-24DOI: 10.1109/TUFFC.2024.3405374
Hao Guo;Steven Freear;Guang-Quan Zhou
Conventional medical ultrasound systems utilizing focus-beam imaging generally acquire multichannel echoes at frequencies in tens of megahertz after each transmission, resulting in significant data volumes for digital beamforming. Furthermore, integrating state-of-the-art beamformers with transmission compounding substantially increases the beamforming complexity. Except for upgrading the hardware system for better computing performance, an alternative strategy for accelerating ultrasound data processing is the wavenumber beamforming algorithm, which has not been effectively extended to synthetic focus-beam transmission imaging. In this study, we propose a novel wavenumber beamforming algorithm to efficiently reduce the computational complexity of traditional focus-beam ultrasound imaging. We further integrate the wavenumber beamformer with a sub-Nyquist sampling framework, enabling ultrasonic systems to acquire echoes within the active bandwidth at significantly reduced rates. Simulation and experimental results indicate that the proposed beamformer offers image quality comparable to the state-of-the-art spatiotemporal beamformer while reducing the sampling rate and runtime by nearly ninefold and fourfold, respectively. The proposed approach would potentially help the development of low-power consumption and portable ultrasound systems.
{"title":"Wavenumber Beamforming With Sub-Nyquist Sampling for Focus-Beam Ultrasound Imaging","authors":"Hao Guo;Steven Freear;Guang-Quan Zhou","doi":"10.1109/TUFFC.2024.3405374","DOIUrl":"10.1109/TUFFC.2024.3405374","url":null,"abstract":"Conventional medical ultrasound systems utilizing focus-beam imaging generally acquire multichannel echoes at frequencies in tens of megahertz after each transmission, resulting in significant data volumes for digital beamforming. Furthermore, integrating state-of-the-art beamformers with transmission compounding substantially increases the beamforming complexity. Except for upgrading the hardware system for better computing performance, an alternative strategy for accelerating ultrasound data processing is the wavenumber beamforming algorithm, which has not been effectively extended to synthetic focus-beam transmission imaging. In this study, we propose a novel wavenumber beamforming algorithm to efficiently reduce the computational complexity of traditional focus-beam ultrasound imaging. We further integrate the wavenumber beamformer with a sub-Nyquist sampling framework, enabling ultrasonic systems to acquire echoes within the active bandwidth at significantly reduced rates. Simulation and experimental results indicate that the proposed beamformer offers image quality comparable to the state-of-the-art spatiotemporal beamformer while reducing the sampling rate and runtime by nearly ninefold and fourfold, respectively. The proposed approach would potentially help the development of low-power consumption and portable ultrasound systems.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"972-984"},"PeriodicalIF":3.0,"publicationDate":"2024-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141092805","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 : 2024-03-23DOI: 10.1109/TUFFC.2024.3404826
Quang Tran;William D. O’Brien;Aiguo Han
The use of the structure function (SF) to model interscatterer contribution to ultrasonic scattering is a major step to improve the capability and accuracy of quantitative ultrasound (QUS) and tissue characterization. However, existing QUS-based SF models rely on the hard-sphere (HS) model, which is limited in its applicability for complex scatterer distributions in real tissue. This article introduces the sticky HS (SHS) model for QUS and tissue characterization, which considers a very short-range attractive potential that accounts for the adhesive nature of biological cells and yields a new parameter called stickiness. Herein, the analytical SF expression is presented for monodisperse scatterer size and validated using simulations of scatterer distributions with varying degrees of grouping and volume fractions (0.16, 0.32, and 0.40) over the frequency range from 15 to 110 MHz. The SHS model is applied to three mammary tumor types with differing spatial distributions of tumor cells. The histology-derived SF is computed by considering the nuclei as the main sources of scattering. The results show that the SHS model provides more accurate scatterer radius and volume fraction estimates than the HS model when fit to histology-derived SF versus frequency curves. Furthermore, the new stickiness parameter provided by SHS is sensitive to the grouping structure in tumor cell distribution. This stickiness parameter, combined with the radius and volume fraction estimated from the SHS model, enables better differentiation between different tumor types than using the radius and volume fraction obtained from the HS model. This study demonstrates the potential of the SHS model to improve the QUS tissue characterization.
{"title":"Sticky Hard-Sphere Model for Characterizing Tumor Microstructure via Quantitative Ultrasound","authors":"Quang Tran;William D. O’Brien;Aiguo Han","doi":"10.1109/TUFFC.2024.3404826","DOIUrl":"10.1109/TUFFC.2024.3404826","url":null,"abstract":"The use of the structure function (SF) to model interscatterer contribution to ultrasonic scattering is a major step to improve the capability and accuracy of quantitative ultrasound (QUS) and tissue characterization. However, existing QUS-based SF models rely on the hard-sphere (HS) model, which is limited in its applicability for complex scatterer distributions in real tissue. This article introduces the sticky HS (SHS) model for QUS and tissue characterization, which considers a very short-range attractive potential that accounts for the adhesive nature of biological cells and yields a new parameter called stickiness. Herein, the analytical SF expression is presented for monodisperse scatterer size and validated using simulations of scatterer distributions with varying degrees of grouping and volume fractions (0.16, 0.32, and 0.40) over the frequency range from 15 to 110 MHz. The SHS model is applied to three mammary tumor types with differing spatial distributions of tumor cells. The histology-derived SF is computed by considering the nuclei as the main sources of scattering. The results show that the SHS model provides more accurate scatterer radius and volume fraction estimates than the HS model when fit to histology-derived SF versus frequency curves. Furthermore, the new stickiness parameter provided by SHS is sensitive to the grouping structure in tumor cell distribution. This stickiness parameter, combined with the radius and volume fraction estimated from the SHS model, enables better differentiation between different tumor types than using the radius and volume fraction obtained from the HS model. This study demonstrates the potential of the SHS model to improve the QUS tissue characterization.","PeriodicalId":13322,"journal":{"name":"IEEE transactions on ultrasonics, ferroelectrics, and frequency control","volume":"71 8","pages":"985-994"},"PeriodicalIF":3.0,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141086673","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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