Dynamic real-time reconstruction and rendering of breast tomosynthesis images

描述（由申请人提供）：基于初步的临床结果，人们普遍认为数字乳腺断层合成（DBT）在未来有可能取代乳房x线摄影。目前至少有八家公司正在开发DBT成像系统，其中三家公司很少或没有开发主要审查工作站的经验。实时断层扫描（RTT）具有开发医疗工作站的经验。RTT目前正在开发一个医生审查工作站，用于数字乳房断层合成图像的初步诊断。鉴于DBT数据集的庞大规模、乳腺成像对图像质量的严格要求，以及乳腺筛查和诊断对高通量的需求，我们认为有必要建立一个专用工作站。为了满足高吞吐量的需求，我们特别提出开发和实现一种重建算法，该算法将允许在专用的高端pc图形处理器单元（GPU）上通过乳房体积动态实时重建和渲染任意平面（DRR）。我们相信GPU技术的进步使得按需重建断层合成图像成为可能和优先。支持dr的理由有很多。首先，目前存在的GPU硬件允许几乎即时的反投影和滤波（BPF）重建断层图像；这种硬件基本上是现成的，随时可用。其次，目前生产的乳腺断层合成数据集具有各向异性，面内分辨率约为0.07-0.1 mm2，面外分辨率为1 mm。这种各向异性是由最终图像集的大小和产生这些数据所需的时间所必需的。然而，在DBT中，可以在任何位置重建图像；DRR允许任意重建，而不会对存储或速度产生不利影响。RTT的长期目标是建立一个基于DRR原则的初级审查工作站。在这个II期项目中，我们试图改进我们现有的DBT重建算法和过滤器，以增强乳腺癌的不同临床适应症，这对正确诊断至关重要。我们的最终目标是实现至少每秒20帧（fps）的重建率。在第二阶段，我们提出以下具体目标：(1)使用通用GPU编程技术在GPU上改进我们的反向投影算子。(2)改进我们的成像滤波方法，使用通用GPU编程技术专门增强钙化和肿块的图像。(3)开发厚片渲染方法并在GPU上实现。(4)探索在GPU上处理大型数据集的方法。宾夕法尼亚大学将提供图像重建的图像质量评估，并将提供模拟幻影图像，以优化图像反投影和过滤方法。公共卫生相关性：乳房x线照相术（包括数字乳房x线照相术）受到一些基本限制，因为二维图像是由三维乳房解剖构成的。由于正常组织的叠加，乳房x光检查可能产生假阳性结果，而由于正常组织隐藏或掩盖了癌症，乳房x光检查可能会遗漏癌症。数字乳腺断层合成（DBT）是一种断层成像方法，有可能解决乳房x线摄影的上述两个问题。多家制造商正在开发断层合成成像系统。然而，正如正在进行的临床数字乳房x光检查系统所表明的那样，采集技术的开发只是使DBT成为临床现实所需努力的一小部分。我们建议建立一个DBT的主治医师评审工作站。这是任何临床DBT系统的重要组成部分。

DESCRIPTION (provided by applicant): It is widely believed that digital breast tomosynthesis (DBT) has the potential to replace mammography in the future, based on preliminary clinical results. At least eight companies are currently developing DBT imaging systems, three of whom have little or no experience developing primary review workstations. Real-Time Tomography (RTT) has the experience to develop medical workstations. RTT is currently in the process of developing a physician review workstation for the primary diagnosis of digital breast tomosynthesis images. We believe that a dedicated workstation is necessary based upon the large size of DBT datasets, the stringent image quality requirements for breast imaging, and the need for high-throughput in both breast screening and diagnosis. To address the need for high-throughput, we specifically propose to develop and implement a reconstruction algorithm that will allow dynamic real-time reconstruction and rendering (DRR) of arbitrary planes through the breast volume on a dedicated high-end PC-based graphics processor unit (GPU). We believe that the advances in GPU technology make it both possible and preferential to reconstruct tomosynthesis images on demand. There are many reasons to favor DRR. First, the GPU hardware that exists today allows nearly instantaneous back-projection and filtered (BPF) reconstruction of tomographic images; this hardware is essentially off-the- shelf and readily available. Second, breast tomosynthesis datasets currently being produced are anisotropic, having in-plane resolution of approximately 0.07-0.1 mm2 and out-of-plane resolution of 1 mm. This anisotropy is necessitated by the size of the resultant image set, and the time required to produce those data. However, in DBT it is possible to reconstruct images at any location; DRR would allow arbitrary reconstruction without adversely impacting either storage or speed. The long-term goal of RTT is to develop a primary review workstation based on the DRR principle. In this Phase II proposal, we seek to refine our existing DBT reconstruction algorithm and filters to enhance the different clinical indications of breast cancer that is crucial for proper diagnosis. Our ultimate goal is to achieve a reconstruction rate of at least 20 frames per second (fps). In Phase II, we propose the following specific aims: (1) Refine our backprojection operators on a GPU using general-purpose GPU programming techniques. (2) Refine our imaging filtering methods to specifically enhance images of calcifications and masses using general-purpose GPU programming techniques. (3) Develop thick-slice rendering methods and implement them on a GPU. (4) Explore methods for handling large data sets on the GPU. The University of Pennsylvania will provide assessments of image quality of the image reconstructions and will provide simulated phantom images to allow optimization of the image backprojection and filtering methods. PUBLIC HEALTH RELEVANCE: Mammography (including digital mammography) is subject to a number of fundamental limitations because 2D images are made of the 3D breast anatomy. Mammograms can produce false positive findings due to the superposition of normal tissues, and cancers can be missed in mammograms because normal tissue hide or mask the cancer. Digital breast tomosynthesis (DBT) is a tomographic imaging method with the potential to solve both of the above problems of mammography. Tomosynthesis imaging systems are being developed by multiple manufacturers. However, as has been made clear from the ongoing deployment of clinical digital mammography systems, the development of the acquisition technology is only a small part of the effort that will be required to make DBT a clinical reality. We propose to develop a primary physician review workstation for DBT. This is an essential part of any clinical DBT system.