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. .

项目摘要/摘要 该提案的目标是发展肺结节病和 将射线照相数据与临床数据，遗传变异和转录特征整合，重新定义 结节病生物标志物。我们的长期目标是使用这些集成表型和相应的分析 开发的方法1）疾病进展的新客观中间终点和2）预测模型 疾病进展，以帮助临床医生参与临床决策和试验设计研究人员。结节病是 一种全身性肉芽肿性疾病，主要涉及肺部，影响约1.1万人 美国，这种流行可能被低估了。通常在20至50年之间被诊断出来 导致生活质量和生产率的显着降低。虽然有些人经历了自发的 解决方案，其他人继续发展严重疾病。当前的肺结节病的研究依赖 基于胸部X射线的肺部异常的表征，使用Scadding分期系统视觉。这是 众所周知，仅基于刺伤阶段，肺部疾病的分类错误。此外， 该系统对于治疗决策没有用，可以多样化预测疾病病程或预后。计算 肺的层析成像（CT）成像以量化实质和其他肺部异常 改善其他肺部疾病的疾病定量（特发性肺纤维化和COPD-胚胎症）。 我们假设结节病中肺CT图像的详细放射分析与视觉结合 评分指标将确定肺部疾病的新，更精致的表型，并结合 临床和转录组信息将确定可以是可以是的新型整合性疾病表型 在未来的纵向研究中显示，以预测肺部疾病的分辨或进展。在这个 项目，我们将1）开发出肺异常的放射线和全面的放射线表征 大量的结节病患者，2）整合临床，遗传，转录组和放射线表征 结节病以识别结节病的放射线特征的预测指标，并发展出新的整合表型 结节病，3）验证与射线照相特征和新综合性相关的临床和遗传 现实世界中的临床人群中的表型，以及4）射线照相的纵向稳定性 回顾性队列的75例患者的肺部异常表征。成功完成 这项研究将回答有关射线照相肺异常的关键知识差距 与临床和遗传表型有关，以及如何结合射线照相评估，临床和 遗传/基因组数据以鉴定结节病的不同表型。最终，该提议将建立新的 标准化表型，用于纵向遵循疾病，并确定要进行干预的组。 。