Novel Quantitative Emphysema Subtypes in MESA and SPIROMICS

MESA 和 SPIROMICS 中新的定量肺气肿亚型

• 批准号: 8759952
• 负责人: R Graham BARR
• 金额: $ 45.59万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8759952
• 关键词: Accounting; Alveolus; Atherosclerosis; Autopsy; Cardiac; Cause of Death; Cessation of life; Chronic Obstructive Airway Disease; Clinical; Clinical Research; Code; Cohort Studies; Computer software; Correlation Studies; Development; Diagnosis; Disease; Disease Progression; Environment; General Population; Genetic; Genome; Genotype; Goals; Gold; Hospitalization; Image; Image Analysis; Label; Lead; Learning; Lung; Measures; Methods; Microscope; Modeling; Monitor; Normalcy; Obstruction; Onset of illness; Outcome; Participant; Pathology; Patients; Persons; Pharmaceutical Preparations; Phenotype; Physiological; Population; Prevention strategy; Process; Protocols documentation; Pulmonary Emphysema; Reading; Recruitment Activity; Research; Risk Factors; Sampling; Scanning; Series; Single Nucleotide Polymorphism; Smoker; Structure; Structure of parenchyma of lung; Symptoms; Techniques; Testing; Texture; Time; Tissues; United States; Validation; Variant; Walking; X-Ray Computed Tomography; attenuation; base; clinical practice; clinically relevant; clinically significant; cohort; computerized tools; cost; design; exome; follow-up; functional status; genome-wide; image processing; in vivo; lung imaging; mortality; never smoker; non-smoking; novel; outcome forecast; patient population; prevent; prognostic; prospective; public health relevance; radiologist; rare variant; respiratory; sample fixation; tool; volunteer

DESCRIPTION (provided by applicant): Chronic obstructive pulmonary disease (COPD) and emphysema together are the third leading cause of death in the United States. COPD and emphysema are recognized to be heterogeneous diseases, but its underlying mechanisms are not fully understood and there is a lack of precise, biologically based and clinically applicable definitions of emphysema and COPD. In particular, certain subtypes of emphysema have been found to correlate with different risk factors and are therefore likely to represent different diseases. Computed tomography (CT) imaging provides rich in vivo information on the lung parenchyma, airways and vasculature but use of this information is limited. Current approaches for CT-based emphysema quantification and subtyping rely on either crude methods that discard most of the spatial information in CT scans (e.g. thresholding) or on approaches based on supervised learning that simply replicate radiologists' interpretation or use physiological measures as labels. This project will develop the missing computational tools and perform the clinical correlation studies required to exploit CT lung imaging as a new 'microscope' for lung structure examination and will define quantitative emphysema subtypes (QES) for clinical and research use. To reach this goal, we will: (1) develop novel and robust image processing tools for the extraction of emphysema radiological features on thousands of CT scans, (2) perform unsupervised clustering of emphysema radiological features on the large MESA cohort of patients to discover QES and, (3) quantify the levels of normality for QES among homogeneous populations of non-smoking "normal" participants without respiratory symptoms and disease. We will then, starting at the latest in Year 3, demonstrate the clinical relevance of the QES by correlating with symptoms, functional status, respiratory outcomes (hospitalization and death) and examine associations with genotype (genome-wide single nucleotide polymorphisms and exomic rare variants). The power of the analysis is provided by the exploitation of three (MESA, SPIROMICS, EMCAP) very large cohorts of Lung studies - containing CT lung images, respiratory and genetic measures - from normal volunteers and COPD patients. Longitudinal progression of QES in the general population over 10 years (MESA study) and over 5 years among smokers (EMCAP study) will confirm the sensitivity of patients' follow up with CT scans. At the end, QES will be validated to be used to phenotype emphysema into subtypes that have major prognostic significance, contribute to symptoms and have a genetic underpinning. The proposed QES, being derived from automated processing tools, are therefore efficient, low-cost, reproducible, comprehensive, and highly translatable into clinical practice.

描述（由申请人提供）：慢性阻塞性肺病（COPD）和肺气肿一起是美国第三大死因。 COPD和肺气肿被认为是异质性疾病，但其潜在机制尚未完全了解，并且缺乏精确的、基于生物学和临床适用的肺气肿和COPD定义。特别是，已发现肺气肿的某些亚型与不同的危险因素相关，因此可能代表不同的疾病。计算机断层扫描 (CT) 成像提供了有关肺实质、气道和脉管系统的丰富体内信息，但这些信息的使用有限。目前基于 CT 的肺气肿量化和亚型分型方法要么依赖于丢弃 CT 扫描中大部分空间信息（例如阈值化）的粗略方法，要么依赖于基于监督学习的方法，这些方法简单地复制放射科医生的解释或使用生理测量作为标签。该项目将开发缺失的计算工具，并进行临床相关研究，以利用 CT 肺部成像作为肺部结构检查的新“显微镜”，并将定义供临床和研究使用的定量肺气肿亚型 (QES)。为了实现这一目标，我们将：(1) 开发新颖且强大的图像处理工具，用于在数千次 CT 扫描中提取肺气肿放射学特征，(2) 对大型 MESA 患者队列进行肺气肿放射学特征的无监督聚类，以发现 QES，(3) 量化无呼吸道症状的非吸烟“正常”参与者同质群体中 QES 的正常水平，以及 疾病。然后，我们将最晚从第 3 年开始，通过与症状、功能状态、呼吸结果（住院和死亡）相关来证明 QES 的临床相关性，并检查与基因型（全基因组单核苷酸多态性和外显子组罕见变异）的关联。分析的力量是通过利用来自正常志愿者和慢性阻塞性肺病患者的三项非常大的肺部研究队列（MESA、SPIROMICS、EMCAP）提供的，其中包括 CT 肺部图像、呼吸和遗传测量。一般人群 10 年以上（MESA 研究）和吸烟者 5 年以上 QES 纵向进展（EMCAP 研究）将证实患者 CT 扫描随访的敏感性。最后，QES 将被验证可用于将肺气肿表型分为具有重大预后意义、有助于症状并具有遗传基础的亚型。因此，所提出的 QES 源自自动化处理工具，具有高效、低成本、可重复、全面且高度可转化为临床实践的特点。