Advanced image reconstruction for accurate and high-resolution breast ultrasound tomography

先进的图像重建，可实现精确、高分辨率的乳腺超声断层扫描

基本信息

批准号：
10442593
负责人：
Mark A Anastasio
金额：
$ 57.49万
依托单位：
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-13 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10442593
关键词：
3-Dimensional 3D ultrasound Acoustics Adoption Algorithms Award Benign Breast Characteristics Clinical Clinical Data Clinical effectiveness Computer Simulation Coupled Data Detection Development Diagnostic Disease Equation Evaluation Formulation Frequencies Height Image Ionizing radiation Location Mammary Ultrasonography Mammography Measures Methods Modality Morphologic artifacts Noise Normal tissue morphology Outcome Physics Physiologic pulse Probability Property Radiation Reader Reporting Resolution Roentgen Rays Screening procedure Shapes Slice Specificity Speed System Technology Thinness Time Tissues Transducers Visual Work X-Ray Computed Tomography accurate diagnosis attenuation base breast cancer diagnosis breast imaging breast lesion clinical application experience image reconstruction imaging modality improved innovation malignant breast neoplasm member public health relevance quantitative ultrasound radiologist reconstruction soft tissue sound tomography ultrasound

项目摘要

ABSTRACT The broad objective of this project is to develop and refine advanced tomographic image reconstruction methods for ultrasound computed tomography (UST), referred to as waveform inversion methods, which will permit high resolution and quantitative breast imaging. These methods will yield volumetric estimates of the speed of sound (SOS) and acoustic attenuation (AA) distributions within the breast. The SOS and AA represent bio-parameters that can reveal differences in the geometric and elastic properties of tissue. Such information can greatly facilitate the differentiation of breast cancer from normal tissue or benign disease. Accordingly, UST holds great potential for improving the detection and management of breast cancer since it exploits effective endogenous tissue contrasts, is radiation- and breast-compression-free, and is relatively inexpensive. The SoftVue whole breast UST system developed by members of our team has been awarded FDA 510(k) clearance for diagnostic applications. Most reported methods for breast UST are ray-based and do not take into account acoustic diffraction effects; this results in images of relatively poor spatial resolution and accuracy. This is highly undesirable for breast imaging applications, in which the ability to resolve fine features is important for distinguishing healthy from diseased tissues. Waveform inversion methods for UST image reconstruction are based on the full acoustic wave equation and can circumvent the limitations of ray-based methods, thereby permitting high- resolution quantitative UST breast imaging. However, the application of waveform inversion methods to breast UST employing ring-transducer arrays has to-date employed 2D reconstruction methods to estimate sectional UST images. Because 3D wave propagation physics and the focusing properties of the transducers are not accounted for in this 2D approach, the images can contain significant artifacts and degraded spatial resolution. In this project, we will develop and optimize 3D UST waveform inversion methods for reconstructing SOS and AA images of the breast of unprecedented quality. These methods will utilize acoustic data measured at one or more locations of the ring-transducer array and will compensate for 3D wave physics and the focusing properties of the transducers. In this approach, a thin (in height) volume will be reconstructed instead of a single 2D slice. Whole breast imaging can then be accomplished by merging the thin reconstructed volumes corresponding to different locations instead of stacking lower quality 2D slices as done in existing 2D methods. The developed methods will be evaluated and refined by use of phantom and clinical data. The specific aims of this project are: (1) Develop waveform inversion methods for high resolution SOS imaging; (2) Develop waveform inversion methods for high resolution AA imaging; (4) Refinement of reconstruction methods via breast phantom studies; (5) Assessment and refinement of reconstruction methods using clinical data.

抽象的该项目的总体目标是开发和完善先进的断层扫描图像重建超声计算机断层扫描 (UST) 方法，称为波形反演方法，该方法将允许高分辨率和定量乳腺成像。这些方法将产生体积估计乳房内的声速（SOS）和声衰减（AA）分布。 SOS 和 AA 代表可以揭示组织几何和弹性特性差异的生物参数。这样的信息可以极大地促进乳腺癌与正常组织或良性疾病的区分。因此，UST 在改善乳腺癌的检测和管理方面具有巨大的潜力，因为它利用有效的内源性组织对比，无辐射和乳房压缩，并且相对便宜。我团队成员开发的SoftVue全乳UST系统荣获 FDA 510(k) 诊断应用许可。大多数报道的乳腺 UST 方法都是基于射线的，没有考虑声学衍射影响；这导致图像的空间分辨率和精度相对较差。这是非常不希望的乳腺成像应用，其中分辨精细特征的能力对于区分健康状况非常重要来自患病组织。 UST 图像重建的波形反演方法基于完整的声波方程，可以规避基于射线的方法的局限性，从而允许高分辨率定量 UST 乳腺成像。然而，波形反演方法在乳房中的应用采用环形换能器阵列的 UST 迄今为止已采用 2D 重建方法来估计截面 UST 图像。因为 3D 波传播物理学和换能器的聚焦特性不在这种 2D 方法中，图像可能包含明显的伪影和降低的空间分辨率。在这个项目中，我们将开发和优化用于重建SOS的3D UST波形反演方法以及前所未有质量的乳房 AA 图像。这些方法将利用在以下位置测量的声学数据环形换能器阵列的一个或多个位置，并将补偿 3D 波物理和聚焦传感器的特性。在这种方法中，将重建一个薄（高度）体积而不是一个单个二维切片。然后可以通过合并薄的重建体积来完成整个乳房成像对应于不同的位置，而不是像现有 2D 方法那样堆叠较低质量的 2D 切片。所开发的方法将通过使用模型和临床数据进行评估和完善。具体目标该项目是：（1）开发高分辨率SOS成像的波形反演方法； (2) 开发用于高分辨率AA成像的波形反演方法； (4) 重构方法的细化乳房模型研究； (5)利用临床数据评估和完善重建方法。