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: 9900863
• 负责人: Nichole Carlson
• 金额: $ 64.91万
• 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 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9900863
• 关键词: Affect; Age; Award; Bayesian Modeling; Biological Markers; Biometry; Characteristics; Chronic Obstructive Airway Disease; Classification; Clinic; Clinical; Clinical Data; Complex; Data; Data Set; Diagnosis; Diagnostic radiologic examination; Disease; Disease Progression; Evaluation; Follow-Up Studies; Future; Gender; Gene Expression; Gene Expression Profile; Genetic; Genetic Transcription; Genomics; Goals; Granulomatous; 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; Pulmonary Emphysema; Pulmonary Function Test/Forced Expiratory Volume 1; Pulmonary Sarcoidosis; Quality of life; Radiology Specialty; Recommendation; Reproducibility; Research; Research Design; Research Personnel; Resolution; Respiratory physiology; 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; multidisciplinary; novel; outcome forecast; predictive modeling; 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. .

项目总结/摘要 本提案的目标是开发可重复的肺结节病放射学表型， 将放射学数据与临床数据、遗传变异和转录特征相结合，重新定义 结节病生物标志物。我们的长期目标是利用这些综合表型和相应的分析方法， 开发1）疾病进展的新客观中间终点和2）预测模型的方法 疾病进展，以帮助临床医生在临床决策和研究人员在试验设计。结节病是 一种全身性肉芽肿性疾病，主要累及肺部，影响约11万人， 美国，这一流行率可能被低估了。通常诊断为20-50岁之间的生活，它 导致生活质量和生产力显著下降。虽然有些人会自发地 其他人继续发展严重的疾病。目前肺结节病的研究依赖于 基于胸部X线，使用Scadding分期系统直观地表征肺部异常。是 公认仅根据Scadding分期对肺部疾病进行错误分类。此外，本发明还提供了一种方法， 该系统对于治疗决策没有用，并且不能预测疾病进程或预后。计算 肺的断层扫描（CT）成像以量化实质和其他肺异常已经提供了 改善其他肺部疾病（特发性肺纤维化和COPD-肺气肿）的疾病量化。 我们假设结节病肺部CT图像的详细放射组学分析结合视觉 评分指标将识别新的、更精确的肺部疾病表型， 临床和转录组学信息，将确定新的整合疾病表型， 在未来的纵向研究中显示，可以预测肺部疾病的消退或进展。在这 项目，我们将1）开发一个放射组学和全面的放射学特征的肺部异常， 一个大型的结节病患者队列，2）整合临床、遗传、转录组学和放射组学特征 确定结节病放射组学特征的预测因子并开发新的综合表型 3）阐明结节病的临床和遗传与影像学特征的相关性， 表型在现实世界的临床人群，和4）表征的纵向稳定性的放射 75例患者的回顾性队列中肺部异常的特征。成功完成 这项研究将回答关于结节病的放射学肺部异常如何 以及如何将联合收割机放射学评估、临床和 遗传/基因组数据以鉴定结节病的不同表型。最终，该提案将建立新的 标准化的表型，用于纵向跟踪疾病并确定要干预的组。 .