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.

项目摘要 COPD是发病率和死亡率的主要原因。尽管吸烟减少，但COPD的死亡率 继续增加，现在是美国第三大死亡原因。 COPD是一种异质疾病， 一部分以气道的重塑和侧面破坏性的特征为特征。肺气肿是一个 与遗传和表观遗传成分的关键COPD相关表型。但是，肺气肿的进展是 知识渊博，目前可用于测量肺气肿进展的工具受到限制。纵向 研究已经证实，COPD患者和 由于混杂因素，肺气肿的进展分析在患者中有很大差异 参与CT扫描的肺损伤进展分析。直接结果是需要 由于统计功率的降低，用于在临床试验中应用的样本量太大。 影响肺气肿进展分析的主要混杂因素是 校准（设备间的变异性），扫描受试者的生物学变化（大小和增加 数量），获取的变异性（剂量，重建方法）和归因于受主体内的可变性 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 组织的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。统计框架中CT扫描的标准化将使 强大的统计检验的定义以评估肺部异常的程度和活性，该测试将是 从统计学上讲噪声和未配对的校准。此外，它将提供p值的地图。最后，我们 将定义标准化CT扫描的基于不同的进程终点的光密度法 经过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。 我们最近发表的方法获得的初步数据显示出令人鼓舞的结果。我们证明我们 可以有效地获取噪声的强大估计器，该噪声也可以保留实质的结构信息。 另外，我们的噪音稳定方法改变了非雄激素噪声均匀的噪声 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 纵向研究中常见的依据间障碍。 同时，该奖项目的提出的研究将充分利用全面的优势 数据集可通过COPDGENE研究获得。该提案中的目标是可能的 通过与Raul San Jose Estepar博士博士的积极合作。作为导师；和出色的咨询 委员会包括著名领导人在医学图像分析，翻译研究领域的委员会， COPD中的定量成像，COPD的遗传流行病学。