Robust Detection of Early Small Airway Disease

早期小气道疾病的稳健检测

• 批准号: 10115272
• 负责人: Gonzalo Vegas Sanchez-Ferrero
• 金额: $ 13.43万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10115272
• 关键词: Address; Affect; Air; Air Movements; Airway Disease; Award; Base Pairing; Body Size; Bronchioles; Cause of Death; Characteristics; Chronic Obstructive Airway Disease; Clinical; Clinical Trials; Cohort Studies; Cross-Sectional Studies; Data; Data Set; Detection; Development; Devices; Diagnosis; Diagnostic radiologic examination; Dimensions; Disease; Disease Progression; Dose; Early Diagnosis; Early identification; Error Sources; Gases; Goals; Histology; Image; Impairment; Inflammatory Response; Lead; Longitudinal Studies; Lung; Measurement; Measures; Methodology; Methods; Modeling; Morbidity - disease rate; Names; Noise; Onset of illness; Pathogenesis; Patients; Pattern; Physics; Process; Protocols documentation; Publishing; Pulmonary Emphysema; Radiation exposure; Research; Resolution; Role; Scanning; Sensitivity and Specificity; Site; Smoking; Somatotype; Standardization; Statistical Methods; Techniques; Terminal Bronchiole; Therapeutic Intervention; Tissues; Validation; Vendor; X-Ray Computed Tomography; airway obstruction; base; biomarker performance; chronic airflow obstruction; cigarette smoke; clinically relevant; density; dosage; drug discovery; early onset; follow-up; functional decline; high risk; histological studies; image processing; imaging biomarker; imaging modality; improved; in vivo; interest; lung volume; microCT; mortality; particle; pulmonary function; pulmonary function decline; reconstruction; response; small airways disease; success

Project Summary Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality. Despite declines in smoking, mortality from COPD continues to increase and is now the 3rd leading cause of death in the US. The chronic airflow limitation of COPD is caused by a mixture of small airway disease and parenchymal destruction (emphysema). Recent studies have suggested a central role of small airway destruction in the pathogenesis of COPD. This evidence has sparked the interest in in-vivo assessment of small airway disease overall at the early onset of the disease. Early identification of small airway disease could lead to better patient diagnosis, early therapeutic intervention and provide more sensitive markers to elucidate the pathogenesis of the disease and its biomolecular basis that could inform much-needed drug discovery. Computed Tomography (CT) is an imaging modality that has proven to be effective in the quantification of parenchymal destruction. However, the imaging resolution required to obtain direct measures from small airways is beyond the limits of CT scans. A recent technique called parametric response mapping (PRM) proposes to distinguish gas trapping due to small airway disease from emphysema by matching inspiratory and expiratory CT scans and applying density thresholds to distinguish functional small airway disease (FSAD) and emphysema. Despite its success, the PRM shows some limitations that are precluding the accuracy, robustness and interpretation of its results in early disease: The CT density values highly depend on acquisition parameters (dosage, reconstruction kernel, changes in body size) that introduce subject- and scanner-dependent confounders. Although clinical trials use well defined acquisition protocols and phantom-calibrated acquisitions, the biases and noise patterns still are subject-dependent. In particular, many studies using PRM employ inspiratory and expiratory images that are obtained at different dose levels. This project will take full advantage of our most recent developments in image-driven statistical characterization of tissues to reduce the harmful effects of the main factors affecting PRM. The harmonization of CT scans in a statistical framework will enable robust PRM metrics in cross-sectional and longitudinal studies. The statistical characterization will also lead to define adaptive thresholds to detect the emphysema and FSAD minimizing type I and II error trade-off. We will validate the robustness of harmonized PRM metrics in multiparametric acquisitions and study its clinical relevance by studying associations with lung function. Our preliminary data shows that we can obtain harmonized images that minimize the scanner and subject- dependent confounders. Our tissue characterization in CT images also has proved its suitability to provide a statistical framework to define robust adaptive thresholds. Together, the research proposed in the aims of this award will take full advantage of the comprehensive dataset available through the COPDGene study.

项目概要 慢性阻塞性肺疾病（COPD）是发病率和死亡率的主要原因。尽管 随着吸烟率下降，慢性阻塞性肺病 (COPD) 死亡率持续上升，目前已成为第三大死因 美国。 COPD 的慢性气流受限是由小气道疾病和 实质破坏（肺气肿）。最近的研究表明小气道的核心作用 COPD 发病机制中的破坏。这一证据激发了人们对体内评估的兴趣 小气道疾病总体上发生在疾病的早期。早期发现小气道疾病 导致更好的患者诊断、早期治疗干预并提供更灵敏的标记物来阐明 该疾病的发病机制及其生物分子基础可以为急需的药物发现提供信息。 计算机断层扫描 (CT) 是一种成像方式，已被证明可以有效量化 实质破坏。然而，从微小的物体中获得直接测量所需的成像分辨率 气道超出了 CT 扫描的范围。一种称为参数响应映射 (PRM) 的最新技术 提出通过匹配吸气和呼气来区分小气道疾病引起的气体滞留和肺气肿 呼气 CT 扫描并应用密度阈值来区分功能性小气道疾病 (FSAD) 和 气肿。 尽管 PRM 取得了成功，但它也显示出一些局限性，影响了准确性、稳健性和准确性。 早期疾病结果的解释：CT 密度值高度依赖于采集参数 （剂量、重建内核、身体尺寸的变化）引入了受试者和扫描仪依赖性 混杂因素。尽管临床试验使用明确的采集协议和模体校准采集， 偏差和噪音模式仍然取决于主题。特别是，许多使用 PRM 的研究采用 在不同剂量水平下获得的吸气和呼气图像。 该项目将充分利用我们在图像驱动统计方面的最新进展 组织的表征，以减少影响 PRM 的主要因素的有害影响。协调一致 统计框架中的 CT 扫描将在横截面和纵向上实现稳健的 PRM 指标 研究。统计特征还将导致定义自适应阈值来检测肺气肿 FSAD 最小化 I 类和 II 类错误权衡。我们将验证统一 PRM 指标的稳健性 多参数采集并通过研究与肺功能的关联来研究其临床相关性。我们的 初步数据表明，我们可以获得协调的图像，最大限度地减少扫描仪和主题- 依赖混杂因素。我们在 CT 图像中的组织表征也证明了其适合提供 统计框架来定义稳健的自适应阈值。总之，本研究目标中提出的研究 该奖项将充分利用 COPDGene 研究提供的综合数据集。