Combined ARFI and Shear Wave Imaging of Prostate Cancer: Optimizing Beam Sequences and Parameter Reconstruction Approaches.

IF 2.5 4区 医学 Q1 ACOUSTICS Ultrasonic Imaging Pub Date : 2023-07-01 Epub Date: 2023-05-02 DOI:10.1177/01617346231171895
Derek Y Chan, Daniel Cody Morris, Thomas J Polascik, Mark L Palmeri, Kathryn R Nightingale
{"title":"Combined ARFI and Shear Wave Imaging of Prostate Cancer: Optimizing Beam Sequences and Parameter Reconstruction Approaches.","authors":"Derek Y Chan, Daniel Cody Morris, Thomas J Polascik, Mark L Palmeri, Kathryn R Nightingale","doi":"10.1177/01617346231171895","DOIUrl":null,"url":null,"abstract":"<p><p>This study demonstrates the implementation of a shear wave reconstruction algorithm that enables concurrent acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) of prostate cancer and zonal anatomy. The combined ARFI/SWEI sequence uses closely spaced push beams across the lateral field of view and simultaneously tracks both on-axis (within the region of excitation) and off-axis (laterally offset from the excitation) after each push beam. Using a large number of push beams across the lateral field of view enables the collection of higher signal-to-noise ratio (SNR) shear wave data to reconstruct the SWEI volume than is typically acquired. The shear wave arrival times were determined with cross-correlation of shear wave velocity signals in two dimensions after 3-D directional filtering to remove reflection artifacts. To combine data from serially interrogated lateral push locations, arrival times from different pushes were aligned by estimating the shear wave propagation time between push locations. Shear wave data acquired in an elasticity lesion phantom and reconstructed using this algorithm demonstrate benefits to contrast-to-noise ratio (CNR) with increased push beam density and 3-D directional filtering. Increasing the push beam spacing from 0.3 to 11.6 mm (typical for commercial SWEI systems) resulted in a 53% decrease in CNR. In human <i>in vivo</i> data, this imaging approach enabled high CNR (1.61-1.86) imaging of histologically-confirmed prostate cancer. The <i>in vivo</i> images had improved spatial resolution and CNR and fewer reflection artifacts as a result of the high push beam density, the high shear wave SNR, the use of multidimensional directional filtering, and the combination of shear wave data from different push beams.</p>","PeriodicalId":49401,"journal":{"name":"Ultrasonic Imaging","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660585/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ultrasonic Imaging","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/01617346231171895","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/5/2 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ACOUSTICS","Score":null,"Total":0}
引用次数: 0

Abstract

This study demonstrates the implementation of a shear wave reconstruction algorithm that enables concurrent acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) of prostate cancer and zonal anatomy. The combined ARFI/SWEI sequence uses closely spaced push beams across the lateral field of view and simultaneously tracks both on-axis (within the region of excitation) and off-axis (laterally offset from the excitation) after each push beam. Using a large number of push beams across the lateral field of view enables the collection of higher signal-to-noise ratio (SNR) shear wave data to reconstruct the SWEI volume than is typically acquired. The shear wave arrival times were determined with cross-correlation of shear wave velocity signals in two dimensions after 3-D directional filtering to remove reflection artifacts. To combine data from serially interrogated lateral push locations, arrival times from different pushes were aligned by estimating the shear wave propagation time between push locations. Shear wave data acquired in an elasticity lesion phantom and reconstructed using this algorithm demonstrate benefits to contrast-to-noise ratio (CNR) with increased push beam density and 3-D directional filtering. Increasing the push beam spacing from 0.3 to 11.6 mm (typical for commercial SWEI systems) resulted in a 53% decrease in CNR. In human in vivo data, this imaging approach enabled high CNR (1.61-1.86) imaging of histologically-confirmed prostate cancer. The in vivo images had improved spatial resolution and CNR and fewer reflection artifacts as a result of the high push beam density, the high shear wave SNR, the use of multidimensional directional filtering, and the combination of shear wave data from different push beams.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
前列腺癌ARFI和横波联合成像:优化波束序列和参数重建方法。
本研究演示了一种横波重建算法的实现,该算法可以实现前列腺癌和分区解剖的并发声辐射力脉冲(ARFI)成像和横波弹性成像(SWEI)。ARFI/SWEI组合序列在横向视场中使用紧密间隔的推动光束,并在每个推动光束之后同时跟踪轴上(在激励区域内)和离轴(与激励横向偏移)。通过在横向视场中使用大量的推波束,可以收集到比通常获得的更高的信噪比(SNR)剪切波数据,以重建SWEI体积。经过三维定向滤波去除反射伪影后,利用横波速度信号在二维上的相互关系确定横波到达时间。为了结合连续询问的横向推力位置的数据,通过估计推力位置之间的横波传播时间来对齐来自不同推力的到达时间。在弹性病变体中获取剪切波数据,并使用该算法进行重建,结果表明,随着推波束密度的增加和三维定向滤波的增加,剪切波数据的噪比(CNR)有所提高。将推束间距从0.3 mm增加到11.6 mm(通常用于商用SWEI系统)可使CNR降低53%。在人体内数据中,这种成像方法能够对组织学证实的前列腺癌进行高CNR(1.61-1.86)成像。高推力波束密度、高剪切波信噪比、多维方向滤波以及不同推力波束的剪切波数据组合,提高了体内图像的空间分辨率和CNR,减少了反射伪影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Ultrasonic Imaging
Ultrasonic Imaging 医学-工程:生物医学
CiteScore
5.10
自引率
8.70%
发文量
15
审稿时长
>12 weeks
期刊介绍: Ultrasonic Imaging provides rapid publication for original and exceptional papers concerned with the development and application of ultrasonic-imaging technology. Ultrasonic Imaging publishes articles in the following areas: theoretical and experimental aspects of advanced methods and instrumentation for imaging
期刊最新文献
Development of a Polymer Ultrasound Contrast Agent Incorporating Nested Carbon Nanodots. Automated Deep Learning-Based Finger Joint Segmentation in 3-D Ultrasound Images With Limited Dataset. CBAM-RIUnet: Breast Tumor Segmentation With Enhanced Breast Ultrasound and Test-Time Augmentation Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer SPGAN Optimized by Piranha Foraging Optimization for Thyroid Nodule Classification in Ultrasound Images
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1