Novel integrative approaches for disease phenotyping, utilizing radiomics in Sarcoidosis

利用放射组学在结节病中进行疾病表型分析的新综合方法

• 批准号: 10374117
• 负责人: Nichole Carlson
• 金额: $ 63.36万
• 依托单位: NATIONAL JEWISH HEALTH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10374117
• 关键词: Affect; Age; Award; Bayesian Modeling; Biological Markers; Biometry; Characteristics; Chronic Obstructive Pulmonary Disease; Classification; Clinic; Clinical; Clinical Data; Complex; Data; Data Set; Diagnosis; Disease; Disease Progression; Evaluation; Follow-Up Studies; Future; Gender; Gene Expression; Gene Expression Profile; Genetic; Genetic Transcription; Genomics; Goals; Granulomatous; Granulomatous disease; Health; High Resolution Computed Tomography; Image; Image Analysis; Immune response; Impairment; Individual; Inflammation; Knowledge; Life; Longitudinal Studies; Lung; Lung diseases; Measures; Medical Genetics; Medical Imaging; Methods; National Heart, Lung, and Blood Institute; Organ; Patients; Pattern; Phenotype; Population; Predictive Value; Prevalence; Productivity; Prognosis; Pulmonary Emphysema; Pulmonary Function Test/Forced Expiratory Volume 1; Pulmonary Sarcoidosis; Quality of life; Radiology Specialty; Recommendation; Reproducibility; Research; Research Design; Research Personnel; Resolution; Retrospective cohort; Roentgen Rays; Sampling; Sarcoidosis; Scanning; Staging System; Standardization; Statistical Models; Stimulus; System; Testing; Texture; Thoracic Radiography; Time; United States; Validation; Variant; Visual; X-Ray Computed Tomography; adaptive immune response; base; clinical decision-making; cohort; cost; cost effective; data integration; density; disease phenotype; experience; field study; follower of religion Jewish; genetic association; genetic variant; genome-wide; genomic data; idiopathic pulmonary fibrosis; imaging genetics; improved; longitudinal design; lung imaging; lung injury; multidisciplinary; novel; predictive modeling; pulmonary function; quantitative imaging; radiological imaging; radiomics; transcriptomics; trial design; working group

PROJECT SUMMARY/ABSTRACT The goals of this proposal are to develop reproducible radiographic phenotypes of pulmonary sarcoidosis and integrate radiographic data with clinical data, genetic variants and transcriptional signatures, redefining sarcoidosis biomarkers. Our long-term goal is to use these integrative phenotypes and corresponding analytic approaches to develop 1) new objective intermediate endpoints of disease progression and 2) predictive models of disease progression to aid clinicians in clinical decision-making and researchers in trial design. Sarcoidosis is a systemic granulomatous disease, primarily involving the lungs, which affects ~ 110 thousand individuals in the United States, a prevalence which is likely underestimated. Usually diagnosed between 20-50 years of life, it results in a significant decrease in quality of life and productivity. While some individuals experience spontaneous resolution, others go on to develop severe disease. Current studies of pulmonary sarcoidosis rely on characterization of lung abnormalities based on chest x-ray, visually using the Scadding staging system. It is well recognized that there is misclassification of pulmonary disease based solely on Scadding stage. In addition, this system is not useful for treatment decisions and variably predicts disease course or prognosis. Computed tomography (CT) imaging of the lung to quantify parenchymal and other pulmonary abnormalities has offered improved disease quantification in other lung diseases (idiopathic pulmonary fibrosis and COPD-emphysema). We hypothesize that detailed radiomic analysis of lung CT images in sarcoidosis combined with visual scoring metrics will identify new, more refined, phenotypes of lung disease and that combined with clinical and transcriptomic information, will identify novel integrative disease phenotypes that can be shown, in future longitudinal studies, to predict pulmonary disease resolution or progression. In this project, we will 1) Develop a radiomic and comprehensive radiographic characterization of lung abnormalities in a large cohort of sarcoidosis patients, 2) Integrate clinical, genetic, transcriptomic and radiomic characterizations of sarcoidosis to identify predictors of radiomic features of sarcoidosis and develop new integrative phenotypes of sarcoidosis, 3) Validate the clinical and genetic associated with radiographic features and a new integrative phenotypes in a real-world clinical population, and 4) Characterize the longitudinal stability of radiographic characterizations of lung abnormalities among a retrospective cohort of 75 patients. Successful completion of this research will answer critical knowledge gaps as to how radiographic pulmonary abnormalities in sarcoidosis relate to clinical and genetic phenotypes and how to combine radiographic assessment, clinical and genetic/genomic data to identify distinct phenotypes of sarcoidosis. Ultimately, this proposal will establish new standardized phenotypes for following disease longitudinally and identifying groups on which to intervene. .

项目摘要/摘要 这项建议的目标是开发可重现的肺结节病的放射学表型和 将放射数据与临床数据、基因变异和转录签名相结合，重新定义 结节病生物标志物。我们的长期目标是使用这些综合的表型和相应的分析 开发1)新的疾病进展客观中间终点和2)预测模型的方法 以帮助临床医生做出临床决策和帮助研究人员进行试验设计。结节病是 一种系统性肉芽肿性疾病，主要累及肺部，影响全球约11万人。 美国，这一流行率可能被低估了。通常在20-50岁之间确诊，它 导致生活质量和生产力显著下降。虽然有些人会自发地体验 解决，其他人继续发展成严重的疾病。目前对肺结节病的研究依赖于 根据胸部X光，使用SCADIND分期系统直观地描述肺部异常的特征。它是 人们普遍认为，仅以分级为基础对肺部疾病进行错误分类是很有道理的。此外, 这个系统对治疗决策没有用处，只能可变地预测病程或预后。已计算 对肺部进行断层扫描(CT)成像以量化实质和其他肺部异常提供了 改善了其他肺部疾病(特发性肺纤维化和COPD-肺气肿)的疾病量化。 我们假设结节病患者肺部CT图像的详细放射组学分析结合目视 评分指标将识别新的、更精细的肺部疾病表型，并结合 临床和转录组信息，将确定新的综合疾病表型，可以 在未来的纵向研究中显示，可以预测肺部疾病的缓解或进展。在这 项目，我们将1)开发一种放射学和全面的肺部异常的放射学特征 一大群结节病患者，2)综合临床、遗传、转录和放射学特征 以确定结节病放射组学特征的预测因素并开发新的综合表型 结节病，3)验证临床和遗传学与放射学特征和一个新的综合 真实世界临床人群中的表型，以及4)放射学纵向稳定性的特征 75例患者的回顾队列中肺部异常的特征。成功完成 这项研究将回答关键的知识空白，即如何在结节病的放射学肺异常 与临床和遗传表型有关，以及如何结合放射学评估、临床和 基因/基因组数据，以确定结节病的不同表型。最终，这项提议将建立新的 标准化的表型，用于纵向跟踪疾病并确定要干预的群体。 。