Quantification and automated characterization of mucus plug pathology in asthmatics

哮喘患者粘液栓病理学的量化和自动表征

• 批准号: 10676722
• 负责人: Brendan Huang
• 金额: $ 8.23万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10676722
• 关键词: 3-Dimensional; Acute; Address; Affect; Air Movements; Airway Resistance; Algorithms; Architecture; Area; Artificial Intelligence; Asthma; Automation; Binding; Biological Markers; Blood Vessels; Characteristics; Chest; Chronic; Clinical Trials; Coughing; Data; Data Set; Diagnostic; Diagnostic Procedure; Disease Outcome; Elements; Event; Forced expiratory volume function; Goals; Image; Impairment; Institution; Knowledge; Label; Length; Link; Location; Manuals; Masks; Measures; Modeling; Monitor; Mucolytics; Mucous body substance; Network-based; Pathology; Patients; Performance; Pharmaceutical Preparations; Phenotype; Play; Positioning Attribute; Questionnaires; Research; Resistance; Role; Scanning; Scheme; Severity of illness; Shapes; Slice; Specific qualifier value; Spirometry; Sputum; Symptoms; System; Techniques; Testing; Therapeutic; Time; Training; Trees; Variant; Vital capacity; Width; X-Ray Computed Tomography; airway obstruction; asthmatic; asthmatic patient; automated algorithm; automated segmentation; candidate identification; cohort; convolutional neural network; deep learning model; design; genetic association; image processing; imaging Segmentation; improved; lung imaging; neural network architecture; novel; novel diagnostics; patient subsets; prospective; radiological imaging; radiologist; reconstruction; respiratory; supervised learning; two-dimensional

Project Summary Mucus plugging has long been implicated in acute and fatal respiratory events in severe asthma, but we have recently shown that chronic mucus plugging is common in asthmatic patients and appears mechanistically linked with both impaired airflow and worsening disease severity. In particular, in analyses of baseline computed tomography (CT) lung scans in asthmatic patients, we found that airway mucus plugs are highly prevalent, persist for many years, frequently occur without cough and sputum symptoms, and are strongly associated with airflow obstruction. However, it is unknown what radiographic characteristics of mucus plugging cause severe airflow obstruction, in part because detailed characterization of mucus plugs on CT scan is extremely labor intensive and requires highly trained thoracic radiologists for assessment. In Aim 1 of this application, we propose to test the hypotheses, informed by our preliminary data, that three radiographic features of mucus plugs— mucus plug volume, number of proximal plugs, and fraction of airway tree occluded —all predict worsening airflow obstruction. We additionally propose that the airway tree can be converted into a network of resistive elements in which the effective resistance of the entire tree is computed with and without mucus plugs, and the relative contribution of mucus plugs to airway resistance can be determined. In Aim 2, we aim to substantially lower the barrier to quantification of mucus plugging on CT scans by developing an automated, convolutional neural network-based algorithm for mucus plug segmentation. We believe that our findings will allow the identification of a large subset of patients with chronic severe “mucushigh” asthma and raise possibilities for novel mucus-targeted treatments to improve airflow and other disease outcomes in this subset of patients.

项目概要 长期以来，粘液堵塞一直被认为与严重哮喘的急性和致命性呼吸系统事件有关，但我们已经发现 最近表明，慢性粘液堵塞在哮喘患者中很常见，并且在机械上出现 与气流受损和疾病严重程度恶化有关，特别是在基线分析中。 通过对哮喘患者进行计算机断层扫描 (CT) 肺部扫描，我们发现气道粘液塞高度 流行，持续多年，常无咳嗽、咳痰症状，发病强烈 然而，粘液的放射学特征尚不清楚。 堵塞会导致严重的气流阻塞，部分原因是 CT 上粘液塞的详细表征 扫描的劳动强度极大，需要训练有素的胸部放射科医生进行评估。 在这个应用程序中，我们建议根据我们的初步数据来测试假设，即三个射线照相 粘液栓的特征——粘液栓体积、近端栓的数量以及气道树闭塞的比例 —所有预测气流阻塞都会恶化。我们还建议将气道树转变为气道树。 电阻元件网络，其中整棵树的有效电阻是在有或没有的情况下计算的 在目标 2 中，可以确定粘液塞以及粘液塞对气道阻力的相对贡献。 我们的目标是通过开发一种方法来大幅降低 CT 扫描中粘液堵塞定量的障碍 我们相信，基于卷积神经网络的自动化粘液塞分割算法。 研究结果将有助于识别一大批患有慢性严重“粘液高”哮喘的患者， 提高了新型粘液靶向治疗的可能性，以改善气流和其他疾病结果 患者的子集。