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

项目概述和行政补充的基本原理罗切斯特大学目前正在NIH赠款R01 EB009692的支持下开发半球阵列超声乳房成像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、前端电子学、数字技术的重大进步以及反向散射方面的理论突破，提供组织固有特征的无斑点、高分辨率、定量图像，即声速和衰减斜率。该系统使用10,240个并行传输和接收通道，在两秒的间隔内采集数据，并使用一种新的重建算法，以各向同性的点分辨率成像整个乳腺体积，其分辨率与X射线乳房X光摄影的横向分辨率一样好。使用非电离超声波，该系统可以对乳房进行无风险的癌症检测，并克服了X光乳房X光照相的局限性，如致密乳房对比度低、因受压导致解剖变形而导致的扭曲和不适，以及带有植入物的乳房成像不佳。成功的示范最终将改变乳腺癌筛查的方式，并显著改善对乳腺癌治疗反应的检测、诊断和监测。自从最初的拨款被授予以来，一个重要的理论发展发生了重大突破。这一突破使我们独特的重建算法可以独立地重建不同的子体，即并行重建。在我们的算法被扩展的同时，图形处理单元(GPU)正在演变为强大的并行计算引擎。这些图形处理器允许小型高性能计算机系统(HPC)执行大规模并行计算，这些计算非常适合实施我们的并行化重建算法。将图形处理器整合到我们系统的计算节点中，使混合计算机网络具有可与最初用于重建的联邦支持的大型国家超级计算机设施相媲美的计算能力。一个基于GPU的HPC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，而不是使用我们最初的单体积方法在超级计算机上需要数天的时间。重建时间以分钟而不是数天来衡量，将对我们的成像仪器的临床应用产生巨大影响，因为在一次访问过程中就可以获得数据，并查看重建的乳房体积。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房疾病提供一种改进和有效的方法。

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.