Statistical Standardization of CT for the Analysis of Parenchymal Injury Progression in Smokers

CT 统计标准化用于分析吸烟者实质损伤进展

• 批准号: 10223419
• 负责人: Gonzalo Vegas Sanchez-Ferrero
• 金额: $ 18.79万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10223419
• 关键词: Address; Advisory Committees; Affect; Area; Award; Behavior; Biological; Biological Markers; Biomedical Research; Calibration; Cause of Death; Characteristics; Chronic Obstructive Airway Disease; Clinical; Clinical Data; Clinical Trials; Collaborations; Cross-Sectional Studies; Data; Data Set; Densitometry; Descriptor; Detection; Development; Devices; Disease; Disease Progression; Disease model; Doctor of Philosophy; Dose; Dyspnea; Epigenetic Process; Estimation Techniques; Genetic; Genetic Determinism; Goals; Heterogeneity; Image; Image Analysis; Impairment; Individual; Inflammation; Inflammatory Response; Injury; Longitudinal Studies; Lung; Maps; Measures; Medical Genetics; Medical Imaging; Mentors; Methodology; Methods; Modeling; Morbidity - disease rate; Noise; Outcome; Patients; Performance; Phase; Phenotype; Process; Publishing; Pulmonary Emphysema; Pulmonary Mass; Quality of life; Radiation exposure; Regression Analysis; Research; Sample Size; Scanning; Sensitivity and Specificity; Severities; Signal Transduction; Smoker; Smoking; Standardization; Statistical Methods; Structure; Structure of parenchyma of lung; Syndrome; Techniques; Testing; Time; Tissues; Translational Research; Translations; Uncertainty; Variant; Vendor; X-Ray Computed Tomography; airway obstruction; airway remodeling; base; cigarette smoke; clinical care; clinical investigation; cohort; density; dosage; genetic association; genetic epidemiology; genetic variant; genome wide association study; genomic data; image processing; imaging biomarker; improved; interest; low dose computed tomography; lung injury; mortality; novel marker; particle; physical model; preservation; progression marker; pulmonary function; quantitative imaging; rare variant; reconstruction; recruit; tool

Project Summary 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. COPD is a heterogeneous disease, characterized in part by airway remodeling and emphysematous destruction of parenchyma. Emphysema is a key COPD-related phenotype with a genetic and epigenetic component. Emphysema progression is, however, poorly understood and current tools available to measure emphysema progression are limited. Longitudinal studies have confirmed that the presence and severity of emphysema vary greatly in patients with COPD and the progression analysis of emphysema varies substantially among patients due to confounding factors involved in the analysis of lung injury progression with CT scans. The immediate consequence is the need of too large sample size for application in clinical trials due to the reduction of statistical power. The main confounding factors affecting the analysis of emphysema progression are the impairments of calibrations (inter-device variability), the biological changes in the scanned subject (increase of size and volume), variability in the acquisition (dose, reconstruction methods), and intra-subject variability due to the non-homogeneous behavior of noise. This project will take full advantage of the most recent developments in image-driven statistical characterization of tissues to reduce the harmful effects of the main confounding factors affecting the analysis of emphysema progression. The standardization of CT scans in a statistical framework will enable the definition of powerful statistical test to assess the extent and activity of lung abnormalities, the test will be statistically robust to noise and unpaired calibrations. Additionally, it will provide a map of p-values. Finally, we will define different progression endpoints based densitometry of the standardized CT scans that will be validated performing association with clinical outcomes, inflammation biomarkers, and genetic variants. Our preliminary data obtained with our recently published methods show promising results. We show that we can effectively obtain robust estimators to noise that also preserve the structural information of parenchyma. Additionally, our noise-stabilization methods transform the non-homogenous noise a homogeneous noise that can be efficiently characterized. Our tissue characterization in CT images also has proved its suitability to correct he inter-device impairments common in longitudinal studies. Together, the research proposed in the aims of this award will take full advantage of the comprehensive dataset available through the COPDGene study. The execution of the aims in this proposal will be possible through active collaboration with Dr. Raul San Jose Estepar, Ph.D. as the mentor; and an outstanding Advisory Committee including renowned leaders in the fields of medical image analysis, translational research, quantitative imaging in COPD, the genetic epidemiology of COPD.

项目概要 COPD 是发病和死亡的主要原因。尽管吸烟率下降，但慢性阻塞性肺病死亡率 持续增加，现已成为美国第三大死亡原因。 COPD是一种异质性疾病， 部分特征在于气道重塑和肺实质的肺气肿破坏。肺气肿是一种 具有遗传和表观遗传成分的关键慢性阻塞性肺病相关表型。然而，肺气肿的进展是 人们对此知之甚少，目前可用于测量肺气肿进展的工具也很有限。纵向 研究证实，慢性阻塞性肺病 (COPD) 患者和慢性阻塞性肺病 (COPD) 患者的肺气肿的存在和严重程度差异很大。 由于混杂因素，肺气肿的进展分析在患者之间存在很大差异 参与通过 CT 扫描分析肺损伤进展。直接的后果是需要 由于统计功效的降低，样本量太大，无法应用于临床试验。 影响肺气肿进展分析的主要混杂因素是 校准（设备间变异性）、扫描对象的生物变化（尺寸和尺寸的增加） 体积）、采集的可变性（剂量、重建方法）以及由于 噪声的非均匀行为。 该项目将充分利用图像驱动统计的最新发展 组织表征，以减少影响分析的主要混杂因素的有害影响 肺气肿进展。 CT 扫描在统计框架中的标准化将使 定义强大的统计测试来评估肺部异常的程度和活动，该测试将是 对噪声和未配对校准具有统计稳健性。此外，它将提供 p 值图。最后，我们 将根据标准化 CT 扫描的密度测定来定义不同的进展终点 经验证的表现与临床结果、炎症生物标志物和遗传变异的关联。 我们通过最近发布的方法获得的初步数据显示出有希望的结果。我们表明我们 可以有效地获得稳健的噪声估计量，同时保留实质的结构信息。 此外，我们的噪声稳定方法将非均匀噪声转变为均匀噪声， 可以有效地表征。我们在 CT 图像中的组织表征也证明了其适用性 纠正纵向研究中常见的设备间损伤。 总之，该奖项目标中提出的研究将充分利用综合性 可通过 COPDGene 研究获得的数据集。本提案中的目标的执行是可能的 通过与 Raul San Jose Estepar 博士的积极合作作为导师；和出色的咨询 委员会包括医学图像分析、转化研究、 慢性阻塞性肺病的定量成像，慢性阻塞性肺病的遗传流行病学。