Ultrasound Imaging of Breast by Use of a Hemispheric Array and Inverse Scattering

在美国国立卫生研究院R01 EB009692的支持下，罗彻斯特大学目前正在开发半球阵列超声乳房成像系统，该系统是一种独特的设备，由数据采集设备和混合数据采集和高性能计算机网络组成。该系统利用超声换能器阵列、前端电子技术、数字技术和逆散射理论方面的重大进展，提供无斑点、高分辨率、定量的组织固有特征图像，即声速和衰减斜率。该系统通过10240个并行通道进行传输和接收，以两秒间隔获取数据，并使用一种新的重建算法对整个乳房体积进行成像，其各向同性点分辨率与x射线乳房x线摄影的横向分辨率一样好。使用非电离超声，该系统允许对乳房进行无风险的检查以检测癌症，并克服了x射线乳房x线摄影的局限性，例如致密乳房对比度分辨率低，由压缩引起的解剖变形引起的扭曲和不适，以及植入乳房的成像效果差。成功的证明将最终改变乳腺癌筛查的方式，并显著改善乳腺癌的检测、诊断和对治疗反应的监测。一项重要的理论发展——一项重大突破——自最初的资助被授予以来发生了。这一突破使我们独特的重建算法能够独立地重建不同的子卷，即并行重建。在我们的算法得到扩展的同时，图形处理单元（gpu）正在演变成强大的并行计算引擎。这些gpu允许小型高性能计算机系统（hpc）执行大规模并行计算，非常适合实现我们的并行重建算法。在我们系统的计算节点中加入gpu，使混合计算机网络的计算能力可以与最初用于重建的大型联邦政府支持的国家超级计算机设施相媲美。基于gpu的高性能计算网络与我们的数据采集系统相结合，将能够在10 - 15分钟内生成乳房图像，而不是使用我们原来的单卷方法在超级计算机上需要几天的时间。重建时间以分钟为单位，而不是以天为单位，这将对我们成像仪器的临床应用产生巨大影响，因为在一次就诊过程中可以获得数据和重建乳房的体积。一种能够在几分钟内产生100微米分辨率图像的超声成像系统，将为筛查乳腺癌和诊断其他乳腺疾病提供一种改进的、有效的方法。

Project Overview and Rationale for an Administrative Supplement The hemispheric array ultrasound breast imaging system currently being developed at the University of Rochester with the support of NIH grant R01 EB009692 is a unique facility comprised of a data-acquisition apparatus and a hybrid data-acquisition and high-performance computer network. The system leverages significant advances in ultrasound transducer arrays, front-end electronics, digital technology, and theoretical breakthroughs in inverse scattering to provide speckle-free, high- resolution, quantitative images of intrinsic tissue characteristics, i.e., sound speed and attenuation slope. The system is designed to acquire data during a two -second interval by using 10,240 parallel channels for transmission and reception and to image the entire breast volume with isotropic point resolution as good as the lateral resolution of x-ray mammography by use of a novel reconstruction algorithm. Using non-ionizing ultrasound, this system permits risk-free examination of the breast for cancer detection and overcomes limitations of x-ray mammography such as low resolution of contrast in dense breast, distortion and discomfort resulting from compression-induced deformation of anatomy, and poor imaging of breasts with implants. Demonstration of success would ultimately change the way screening for breast cancer is performed and significantly improve detection, diagnosis, and monitoring of response to treatment of breast cancer. An important theoretical development ¿ a major breakthrough ¿ has occurred since the original grant was awarded. This breakthrough allows our unique reconstruction algorithm to reconstruct different subvolumes independently, i.e., in parallel. At the same time that our algorithm was being extended, graphical processing units (GPUs) were evolving into powerful parallel computational engines. These GPUs allow small high-performance computer systems (HPCs) to perform massively parallel computations that are ideally suited for implementation of our parallelized reconstruction algorithm. Incorporation of GPUs in the computing nodes of our system endows the hybrid computer network with a computational capability comparable to that of the large, federally-supported national supercomputer facilities that were originally intended to be used for reconstructions. A GPU-based HPC network coupled to our data-acquisition system will be able to produce breast images in 10 ¿15 minutes rather than the days that would be required on a supercomputer using our original single-volume method. Reconstruction times measured in minutes rather than days would have an enormous impact on the clinical utility of our imaging instrument because data could be acquired and the reconstructed volumes of the breast viewed in the course of a single visit. An ultrasound imaging system capable of producing images with 100-micron resolution in minutes would provide an improved and efficient way to screen for breast cancer and also to diagnose other breast disease.