Toward a practical ultrasound tomography algorithm for improved breast imaging

描述（由申请人提供）：超声断层扫描是一种新兴的乳腺成像方式。然而，目前的超声断层扫描的成像算法，受到计算机的有限的存储器和处理器速度的阻碍，是基于射线理论，并假设一个均匀的背景，这是不准确的复杂的异质区域，当病变的大小是大约相同的大小或小于所使用的超声波的波长失败。因此，必须在超声成像算法中使用波动理论，以正确处理乳腺组织的异质性和衍射效应，以便准确地对小病变进行成像。此外，通过充分利用图形处理单元（GPU）的计算架构，可以大大减轻密集的计算负担的波形层析成像。这项研究的长期目标是开发新的和实用的临床乳腺成像方法，能够定期检测病变之前，他们成为转移。该I期研究的目的和追求该目标的第一步是使波形断层扫描在临床环境中实用。我们的中心假设是，通过利用Delphinus Medical Technologies SoftVue采集几何结构和计算架构实现的波形断层扫描算法将能够在临床相关时间尺度上生成高精度和高分辨率的乳腺图像。提出这项研究的理由是，最近的技术发展的汇合，使新的方法大大提高了超声断层扫描的性能，这将导致乳腺癌检测和诊断的重大改进。预期的结果是所提出的技术的验证，支持我们的长期目标，一个实用的，低成本的乳腺癌检测和诊断设备。我们将通过以下具体目标来检验我们的假设并追求我们的目标。目的1：使波形超声断层成像算法适应SoftVue计算架构。目标2：使用数字乳腺模型评估目标1中算法的准确度和分辨率。目的3：研究目的1中算法的计算速度，以使用数值乳腺模型进行实际临床应用。 公共卫生相关性：拟议的研究探讨了新的波形超声断层扫描算法与我们的商业刀片服务器重建引擎的计算架构集成，嵌入式GPU（SoftVue系统），用于快速和最佳的多参数乳腺成像。所提出的技术的成功结果将导致乳腺癌成像的重大改进，并支持我们的长期目标，即实用，低成本的乳腺癌检测和诊断设备。

DESCRIPTION (provided by applicant): Ultrasound tomography is an emerging modality for breast imaging. However, current ultrasonic tomography's imaging algorithms, hindered by the limited memory and processor speed of computers, are based on ray theory and assume a homogeneous background, which is inaccurate for complex heterogeneous regions and fails when the size of lesions is about the same size or smaller than the wavelength of ultrasound used. Therefore, wave theory must be used in ultrasonic imaging algorithms to properly handle the heterogeneous nature of breast tissue and the diffraction effects in order to accurately image small lesions. Moreover, by taking full advantage of Graphic Processing Units (GPUs) computational architecture, the intensive computation burden of waveform tomography can be greatly alleviated. The long term goal of this research is to develop novel and practical clinical breast imaging methods capable of regularly detecting lesions before they become metastatic. The objective of this Phase I study and the first step in the pursuit of that goal is to make waveform tomography practical in a clinical setting. Our central hypothesis is that the waveform tomography algorithms, implemented by utilizing the Delphinus Medical Technologies SoftVue acquisition geometry and computation architecture, will be able to produce high-accuracy and high-resolution breast images on clinically relevant time scales. The rationale for the proposed study is that a confluence of recent technical developments has enabled new approaches for dramatically improving the performance of ultrasound tomography, which would lead to major improvements in breast cancer detection and diagnosis. The expected outcome is a validation of the proposed technique that supports our long term goal of a practical, low-cost device for breast cancer detection and diagnosis. We will test our hypothesis and pursue our goals through the following specific aims. Aim 1: Adapt waveform ultrasound tomography algorithm to the SoftVue computational architecture. Aim 2: Assess the accuracy and resolution of the algorithm in Aim 1 using numerical breast models. Aim 3: Investigate the computational speed of the algorithm in Aim 1 for practical clinical applications using numerical breast models. PUBLIC HEALTH RELEVANCE: The proposed research explores novel waveform ultrasound tomography algorithms integrated with the computational architecture of our commercial blade-server reconstruction engine with embedded GPUs (SoftVue system) for rapid and optimal multi-parameter breast imaging. Successful outcome of the proposed technique will lead to major improvements in breast cancer imaging and support our long term goal of a practical, low-cost device for breast cancer detection and diagnosis.