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

项目概述和行政补充的理由半球阵列超声乳腺成像系统目前正在开发的罗切斯特大学与美国国立卫生研究院资助R 01 EB 009692是一个独特的设施，包括数据采集设备和混合数据采集和高性能计算机网络。该系统利用超声换能器阵列、前端电子器件、数字技术的显著进步以及逆散射的理论突破来提供内在组织特性的无斑点、高分辨率、定量图像，即，声速和衰减斜率。该系统被设计为通过使用10，240个并行通道进行发送和接收来在两秒间隔期间采集数据，并且通过使用新的重建算法以与X射线乳房摄影术的横向分辨率一样好的各向同性点分辨率对整个乳房体积进行成像。该系统使用非电离超声波，可对乳房进行无风险检查以检测癌症，并克服了X射线乳房摄影术的局限性，例如致密乳房的对比度分辨率低、压缩引起的解剖结构变形导致的变形和不适以及植入乳房的成像差。成功的证明将最终改变乳腺癌筛查的方式，并显着提高检测，诊断和监测乳腺癌治疗的反应。自从最初的赠款获得以来，一个重要的理论发展--一个重大的突破--已经发生。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体积，即，并联在我们的算法被扩展的同时，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与联邦政府支持的大型国家超级计算机设施相当，这些设施最初旨在用于重建。基于GPU的HPC网络与我们的数据采集系统相耦合，将能够在10 - 15分钟内生成乳房图像，而不是使用我们原始的单卷方法在超级计算机上需要的几天。以分钟而不是以天为单位测量的重建时间将对我们的成像仪器的临床实用性产生巨大影响，因为可以在单次访问的过程中获取数据并查看乳房的重建体积。一个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提供一种改进和有效的方法来筛查乳腺癌，并诊断其他乳腺疾病。

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.