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Robust Detection of Early Small Airway Disease

早期小气道疾病的稳健检测

基本信息

批准号：
10360612
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
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10360612
关键词：
Address Affect Air Air Movements Airway Disease Award Base Pairing Body Size Bronchioles Cause of Death Characteristics Chronic Obstructive Pulmonary Disease Clinical Clinical Trials Cohort Studies Cross-Sectional Studies Data Data Set Detection Development Devices Diagnosis 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 radiological imaging reconstruction response small airways disease success

项目摘要

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.

项目总结

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Statistical characterization of the linear attenuation coefficient in polychromatic CT scans.

DOI：
10.1002/mp.14384
发表时间：
2020-11
期刊：
Medical physics
影响因子：
3.8
作者：
Vegas G;San José Estépar R
通讯作者：
San José Estépar R

The Value of Virtual Clinical Trials for the Assessment of the Effect of Acquisition Protocols in Emphysema Quantification.

虚拟临床试验对于评估采集协议在肺气肿量化中的效果的价值。

DOI：
10.1016/j.chest.2023.02.011
发表时间：
2023
期刊：
Chest
影响因子：
9.6
作者：
VegasSanchez-Ferrero,Gonzalo;SanJoséEstépar,Raúl
通讯作者：
SanJoséEstépar,Raúl

Harmonization of in-plane resolution in CT using multiple reconstructions from single acquisitions.

DOI：
10.1002/mp.15186
发表时间：
2021-11
期刊：
Medical physics
影响因子：
3.8
作者：
Vegas-Sánchez-Ferrero G;Ramos-Llordén G;Estépar RSJ
通讯作者：
Estépar RSJ

Quantitative CT Evaluation of Emphysema Progression over 10 Years in the COPDGene Study.

COPDGene 研究中 10 年来肺气肿进展的定量 CT 评估。

DOI：
10.1148/radiol.222786
发表时间：
2023
期刊：
Radiology
影响因子：
19.7
作者：
Baraghoshi,David;Strand,Matthew;Humphries,StephenM;SanJoséEstépar,Raúl;VegasSanchez-Ferrero,Gonzalo;Charbonnier,Jean-Paul;Latisenko,Rudolfs;Silverman,EdwinK;Crapo,JamesD;Lynch,DavidA
通讯作者：
Lynch,DavidA