Clinical Implications of Bronchiectasis in Smokers

项目摘要/摘要 慢性阻塞性肺疾病(COPD)在美国影响着大约2600万人。它 据估计，这些人中有16%-56%患有支气管扩张症(呼吸道病理性扩张)。这个 COPD患者存在支气管扩张与较长的住院时间、较长的康复时间有关 病情恶化，死亡率增加。高分辨率计算机对支气管扩张症的可视化评价 体层摄影(CT)扫描是标准的诊断方法。 在本次调查中，目测评估将用于进一步开发、验证、改进和应用 自动成像工具客观评估吸烟者的支扩负担，使用基线和 COPD基因研究(一大群患有和不患有COPD的吸烟者)的后续胸部CT扫描。在……里面 目标1，我们将在基线和5年随访的子集上进行支气管扩张的可视评分和标记。 调高CT扫描。然后，我们将评估基线支气管扩张症和急性呼吸道疾病之间的关系。 疾病发作、与健康相关的生活质量和死亡。在目标2中，我们将执行基于点的(在单个 客观测量支气管扩张型与非扩张型患者的支气管扩张和气道形态 为AIM 1标记的支气管扩张性呼吸道切片，以识别区分支气管扩张症的CT特征。我们会 构建接收器工作特性(ROC)曲线以确定这些目标的预测能力 检测支气管扩张症的测量。最后，在目标3中，我们将全面开发、验证和改进 自动成像工具，其特征被发现具有歧视性，以检测AIMS 1和2中的支气管扩张。 然后，我们将在所有基线和后续CT扫描中使用该工具来确定支气管扩张的负担 (估计N=16,300)，并评估其与临床相关疾病结局的相关性，包括急性 呼吸道疾病发作、生活质量和死亡率。我们还将使用ROC分析以及 综合歧视指数(IDI)和净重分类指数(NRI)措施以评估#年的贡献 我们预测这些结果的成像工具。

Project Summary/Abstract Chronic obstructive pulmonary disease (COPD) affects approximately 26 million people in the United States. It is estimated that 16%-56% of these people have bronchiectasis (pathologic dilation of the airways). The presence of bronchiectasis in COPD has been linked to longer hospital stays, prolonged recovery from exacerbations, and increased mortality. The visual assessment of bronchiectasis on high-resolution computed tomography (CT) scans is the standard diagnostic method. In this investigation the visual assessment will be used to further develop, validate, refine, and apply an automated imaging tool to objectively assess the burden of bronchiectasis in smokers using baseline and follow-up chest CT scans from the COPDGene Study (a large cohort of smokers with and without COPD). In Aim 1, we will perform a visual scoring and marking of bronchiectasis on a subset of baseline and 5-yr follow- up CT scans. We will then assess the associations between baseline bronchiectasis and acute respiratory disease episodes, health-related quality of life, and death. In aim 2, we will perform point-based (at a single slice) objective measurements of bronchial dilation and airway morphology in bronchiectatic and non- bronchiectatic airway sections labeled for Aim 1 to identify CT features that distinguish bronchiectasis. We will build receiver operating characteristics (ROC) curves to determine the predictive ability of these objective measurements to detect bronchiectasis. Finally, in Aim 3 we will fully develop, validate, and refine an automated imaging tool with the features found to be discriminatory to detect bronchiectasis in Aims 1 and 2. We will then determine the burden of bronchiectasis using this tool on all baseline and follow-up CT scans (estimated N= 16,300) and assess its association with clinically relevant disease outcomes including acute respiratory disease episodes, quality of life, and mortality. We will also use ROC analysis as well as the integrated discrimination index (IDI) and net reclassification index (NRI) measures to assess the contribution of our imaging tool to predict those outcomes.