Optimizing MDCT display for detection and diagnosis of pulmonary embolism

优化 MDCT 显示以检测和诊断肺栓塞

• 批准号: 7568278
• 负责人: WALTER F GOOD
• 金额: $ 37.13万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-01-01 至 2010-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7568278
• 关键词: Address; Algorithms; Arteries; Blood Vessels; Clinical; Consultations; Data; Data Set; Depth Perception; Detection; Development; Diagnosis; Disabled Persons; Doctor of Philosophy; Embolism; Environment; Evaluation; Fatigue; Future; Glass; Goals; Gold; Image; Imagery; Lung; Measures; Methods; Operative Surgical Procedures; Pattern; Performance; Peripheral; Procedures; Process; Property; Psychophysiology; Pulmonary Embolism; Pulmonary vessels; Radiology Specialty; Reader; Reading; Relative (related person); Reporting; Research Personnel; Resolution; Slice; Speed; Structure; Study Section; Surface; System; Technology; Thick; Time; To specify; Trees; Voting; Work; X-Ray Computed Tomography; detector; flexibility; gaze; imaging modality; improved; lung volume; programs; radiologist; stereoscopic

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.

描述（由申请人提供）：多排CT（MDCT）正在迅速成为检测和诊断肺栓塞（PE）的主要成像方式。其主要局限性是无法可靠地描绘亚段动脉以及每项研究都必须审查大量图像数据。该应用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。大多数先前的肺血管分割方法都不是最佳的，虽然它们通常结合 Hessian 矩阵的特征向量来导出圆柱度的局部标量度量，但在此过程中它们会丢失有关局部曲率方向的信息。通过利用源自 3D 数据集的结构张量场中的所有信息，特别是通过采用张量投票方法来识别包含血管表面和分叉的体素，我们期望显着改进分割过程和小动脉的描述。将开发一种灵活的机制，用于根据放射科医生的选择实时显示分段数据的各种立体视图。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纳入系统中，因为某些方法更适合检测，而另一些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由读者自行决定是否显示。将进行回顾性 LROC 研究（8 个阅读器、4 种显示模式、100 个案例）来评估新开发的方法。这项研究将解决性能和效率以及某些心理物理问题，例如显示器的主观接受度、操作速度、3D 与 2D 中的注视模式以及各种显示模式引起疲劳的相对倾向。为了弥补案例验证黄金标准的不完善，还将应用混合物分布分析并与 LROC 结果进行比较。这项研究应该确定一组包含 PE 的图像，这些图像可以在立体显示器上轻松看到，但在传统显示器上无法轻易检测到，反之亦然 - 这将有助于阐明立体对于射线照相应用的好处，并为未来对显示器进行改进提供有用的信息。