Dynamic real-time reconstruction and rendering of breast tomosynthesis images

描述(申请人提供)：根据初步的临床结果，人们普遍认为数字乳腺断层合成(DBT)在未来有取代乳房X光摄影的潜力。目前至少有八家公司正在开发DBT成像系统，其中三家几乎没有开发初级审查工作站的经验。实时层析成像(RTT)具有开发医疗工作站的经验。RTT目前正在开发一个医生评审工作站，用于数字乳房断层成像图像的初步诊断。我们认为，基于DBT数据集的巨大规模、对乳房成像的严格图像质量要求以及在乳房筛查和诊断中对高通量的需求，专用工作站是必要的。为了满足高吞吐量的需求，我们特别建议开发和实现一种重建算法，该算法将允许在专用高端基于PC的图形处理器(GPU)上通过乳房体积动态实时重建和渲染(DRR)任意平面。我们相信，GPU技术的进步使按需重建层析合成图像成为可能，也是一种优势。支持DRR的理由有很多。首先，目前存在的GPU硬件允许对断层图像进行几乎瞬时的反投影和滤波(BPF)重建；这种硬件基本上是现成的，很容易获得。其次，目前正在生产的乳房断层合成数据集是各向异性的，具有大约0.07-0.1mm2的平面内分辨率和1 mm的平面外分辨率。这种各向异性是由结果图像集的大小和产生这些数据所需的时间决定的。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的长期目标是开发一个基于DRR原则的初级审查工作站。在这个第二阶段的提案中，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20帧每秒(Fps)的重建速率。在第二阶段，我们提出了以下具体目标：(1)使用通用的GPU编程技术在GPU上改进我们的反投影算子。(2)改进我们的图像滤波方法，使用通用的GPU编程技术专门增强钙化和肿块图像。(3)开发了厚片绘制方法，并在GPU上实现。(4)探索在GPU上处理大数据集的方法。宾夕法尼亚大学将对图像重建的图像质量进行评估，并将提供模拟体模图像，以优化图像反投影和过滤方法。与公众健康相关：乳房X光检查(包括数字乳房X光检查)受到许多基本限制，因为2D图像是由3D乳房解剖结构制成的。由于正常组织的叠加，乳房X光检查可能会产生假阳性结果，而乳房X光检查中可能会漏掉癌症，因为正常组织隐藏或掩盖了癌症。数字乳腺断层合成(DBT)是一种层析成像方法，具有解决上述两个问题的潜力。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摄影系统的部署所表明的那样，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。我们建议开发一个适用于DBT的主任医师评审工作站。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.