Optimizing MDCT display for detection and diagnosis of pulmonary embolism

描述（由申请人提供）：多层螺旋CT （MDCT）正迅速成为检测和诊断肺栓塞（PE）的主要成像方式。它的主要限制是无法可靠地描绘亚节段动脉，并且每次研究都必须审查大量的图像数据。本应用程序建议实现适当分割的动脉树的立体显示，可以实时操作，旨在提高这些研究的准确性和效率。以往的肺血管分割方法大多是结合Hessian矩阵的特征向量来得到局部圆柱度的标量度量，在此过程中丢失了局部曲率方向的信息。通过利用来自3D数据集的结构张量场中的所有信息，特别是通过使用张量投票方法来识别包含血管和分支表面的体素，我们期望显著改善分割过程和小动脉的描述。将开发一种灵活的机制，用于实时显示分割数据的各种立体视图，由放射科医生选择。将开发专门用于观看PE的渲染方法。多种光线投射算法将被整合到系统中，因为某些方法更适合检测，而其他方法更适合在检测到特征后对其进行评估。由用于分割血管树的局部参数或表征血管分布统计特性的参数组成的图像将在读者的自由裁量权下显示。回顾性LROC研究（8个阅读器，4种显示模式，100例）将对新开发的方法进行评估。本研究将解决性能和效率以及某些心理物理问题，如对显示器的主观接受程度、操作速度、3D与2D的凝视模式，以及各种显示模式诱导疲劳的相对倾向。为了弥补案例验证金标准的不完善，混合分布分析也将被应用，并与LROC结果进行比较。这项研究应该确定一组包含pe的图像，这些图像可以很容易地在立体显示器上看到，但在传统显示器上不能很容易地检测到，反之亦然——这应该有助于阐明立体放射成像应用的好处，并为未来改进显示器提供有用的信息。

DESCRIPTION (provided by applicant): Multi-detector CT (MDCT) is rapidly becoming the primary imaging modality for detection and diagnosis of pulmonary embolism (PE). Its main limitations are its inability to reliably depict sub-segmental arteries and the large volume of image data that must be reviewed for each study. This application proposes to implement a stereographic display of appropriately segmented arterial trees, which can be manipulated in real time, with the intent of improving both the accuracy and efficiency of these studies. Most previous methods for segmenting pulmonary vessels are less than optimal in that, while they generally combine the eigenvectors of the Hessian matrix to derive a local scalar measure of cylindricity, in the process they lose information about the directions of the local curvatures. By exploiting all information in structure tensor fields derived from 3D datasets, and in particular by employing tensor voting methods to identify voxels comprising surfaces of vessels and bifurcations, we expect to significantly improve the segmentation process and the depiction of small arteries. A flexible mechanism will be developed for displaying various stereographic views of the segmented data in real time, at the option of the radiologist. Rendering methods, tailored specifically to viewing PE, will be developed. Multiple raycasting algorithms will be incorporated into the system because certain methods are better for detection while others are better for assessing a feature once it has been detected. Images comprised of local parameters used in segmenting vascular trees, or parameters that characterize statistical properties of vessel distributions, will be displayable at the readers' discretion. A retrospective LROC study (8 readers, 4 display modes, 100 cases) will be performed to evaluate the newly developed methods. This study will address performance and efficiency as well as certain psychophysical issues such as subjective acceptance of the display, speed of operation, pattern of gaze in 3D versus 2D, and the relative propensity of the various display modes to induce fatigue. To compensate for an imperfect gold standard for case verification, mixture distribution analysis will also be applied and compared to LROC results. This study should identify a set of images containing PEs that can be readily seen on stereo displays, but cannot be detected as easily on traditional displays, or vice versa - which should help clarify benefits of stereo for radiographic applications and provide useful information for making future refinements to the display.