DUAL ENERGY SCREENING FOR NODULAR DISEASE

这些研究的目的是开发和评估一个实用的 利用双能量胸部摄影筛查结节性疾病的方法。 双能量技术用于去除骨或软组织 通过利用不同的能量， 骨和软组织中X射线衰减的依赖性。 该技术 使用在两种不同X射线能量下获得的图像来求解骨骼 和软组织成分。 双能量诊断的优势是 软组织结节的可见性通过消除 存在重叠的肋骨，结节的钙含量可能是 通过观察骨骼图像来确定。 获得双能量图像 与传统的X光片同时，几乎没有或没有增加 在患者剂量中，从而使得临床实用筛选成为可能 procedure. 所产生的双能量图像可以由以下人员手动查看： 一个放射科医生，并可能在未来可能会被自动化处理， 结节检测计划，以确定进一步审查这些患者 有潜在的结节 在这个竞争性的延续应用程序中的项目完善了双重- 能源筛选技术在本补助金的第1-3年开发。 本建议中的具体研究包括： 散射校正算法，降噪算法的改进， 用于获得非对称性荧光屏-胶片暗盒的评价 互补的常规图像，评价新的双板计算 用于产生互补常规图像的射线照相方法， 双能量图像质量的详细评价，临床 使用混合常规/双能量评估结节检测 配置和评价结节检测使用人工神经 网络来确定双能量成像是否提供了改进的特异性 用于计算机辅助检测。 在每一个研究领域， 重点将放在详细评价技术改进， 实施的实用性和临床相关的诊断 改进.

The purpose of these studies is to develop and evaluate a practical screening method for nodular disease using dual-energy chest radiography. The dual-energy technique is used to subtract either bone or soft-tissue structures from a radiographic image, by utilizing the different energy dependence of X-ray attenuation in bone and soft-tissue. The technique uses images acquired at two different X-ray energies to solve for the bone and soft-tissue components. The diagnostic advantages of dual-energy are that the visibility of soft-tissue nodules is improved by eliminating the presence of overlying ribs, and the calcium content of nodules may be determined by viewing the bone image. The dual-energy images are acquired simultaneously with a conventional radiograph, with little or no increase in patient dose, thereby making possible a clinically practical screening procedure. The resulting dual-energy images may be reviewed manually by a radiologist, and possibly in the future may be processed by automated nodule detection schemes to identify for further review those patients with potential nodules. The projects in this competing continuation application refine the dual- energy screening techniques developed in years 1-3 of the present grant. The specific studies in this proposal include: refinement of a new scatter-correction algorithm, refinement of noise-reduction algorithms, evaluation of new asymmetric screen-film cassettes for acquiring the complementary conventional image, evaluation of a new two-plate computed radiography approach for producing the complementary conventional image, detailed evaluation of image quality in dual-energy images, clinical evaluation of nodule detection using the hybrid conventional/dual-energy configuration, and evaluation of nodule detection using artificial neural networks to determine if dual-energy imaging provides improved specificity for computer-aided detection. In each of these areas of research, emphasis will be placed on detailed evaluation of technical improvement, practicality of implementation, and clinically-related diagnostic improvement.