Parametric Response Mapping (PRM) for the detection of chronic lung injury in hematopoietic cell transplant recipients

用于检测造血细胞移植受者慢性肺损伤的参数响应图 (PRM)

基本信息

批准号：
10414583
负责人：
Craig J Galban
金额：
$ 87.02万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-15 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10414583
关键词：
Accounting Adult Age Airway Disease Allogenic Biological Markers Bone Marrow Transplantation Bronchiolitis Obliterans Cessation of life Child Childhood Chronic Chronic Lung Injury Chronic Obstructive Pulmonary Disease Clinical Complication Data Detection Development Diagnosis Diagnostic Disease Disease Progression Dyspnea Early Diagnosis Functional disorder High Resolution Computed Tomography Image Intervention Lung Lung diseases Machine Learning Measurement Measures Medicine Methodology Michigan Modeling Morbidity - disease rate Multicenter Trials Observational Study Outcome Patient Care Patients Phase Population Prospective Studies Pulmonary Pathology Pulmonary function tests Quality of life Reporting Research Personnel Risk Scanning Serology Serum Structure of parenchyma of lung Survival Rate Syndrome Techniques Technology Testing Time Training Transplant Recipients Transplantation United States National Institutes of Health Universities X-Ray Computed Tomography base cell injury chronic graft versus host disease clinical development data repository design diagnostic value disorder subtype functional decline hematopoietic cell transplantation high risk improved learning strategy lung allograft lung development lung injury machine learning model mortality novel patient stratification pediatric patients pneumonitis and fibrosis post-transplant precision medicine prevent primary endpoint prospective pulmonary function pulmonary function decline recurrent infection response small airways disease

项目摘要

ABSTRACT Chronic lung dysfunction (CLD) is a potentially severe complication of bone marrow transplantation (BMT), particularly prevalent in patients who develop chronic graft versus host disease (GVHD) post-BMT. The development of CLD is associated with a 20%-40% long term survival rate, with the majority of patients diagnosed with CLD only after they have developed significant (and potentially irreversible) lung pathology. There is a critical need to identify CLD earlier in its clinical course, at a stage when treatment may prove beneficial to patients. Parametric response mapping (PRM) is a novel computed tomography (CT) based methodology that when applied to standard CT scans is capable of identifying and quantifying a variety of lung disease subtypes in patients. This technology was initially developed at Michigan Medicine over 10 years ago for patients with chronic obstructive pulmonary disease (COPD). In both single center and multicenter trials, PRM has demonstrated efficacy for the identification of CLD in adult BMT patients. Our central hypothesis is that PRM can identify patients with chronic GVHD who are at high risk for the development of CLD. We propose an observational study to examine PRM in adult and pediatric subjects (≥ 3 years in age) with chronic GVHD post- BMT. To test our hypothesis, we have established 3 specific aims. In the first two, we will examine PRM values at two main time points: at the onset of chronic GVHD (Aim 1) and at the onset of CLD (Aim 2), with CLD defined by standard NIH criteria. In Aim 3, we will develop a machine learning model that will incorporate serologic and pulmonary function test (PFT) biomarkers with PRM values to develop a composite biomarker strategy. Upon completion of our current proposal, we will establish PRM as a predictor of CLD in adult BMT patients. In addition, the PRM, PFT, and serologic data obtained from pediatric BMT patients will provide a data bank for future research in this population. Historically, the ability to identify CLD in pediatric patients has been PFT-dependent, with PFTs technically challenging to conduct in young children. The use of PRM as a diagnostic indicator of CLD in pediatric BMT patients will be a major advance of this proposal. Finally, our proposal takes our PRM methodology forward in adults, allowing us to study the trajectory of lung disease in adult BMT recipients with chronic GVHD, and following the onset of CLD.

抽象的慢性肺功能障碍（CLD）是骨髓移植（BMT）的潜在严重并发症，在 BMT 后发生慢性移植物抗宿主病 (GVHD) 的患者中尤其常见。 CLD 的发展与 20%-40% 的长期生存率相关，大多数患者只有在出现显着的（并且可能不可逆转的）肺部病变后才被诊断为慢性肺病。在治疗可能有益的阶段，迫切需要在其临床病程的早期阶段识别 CLD 参数响应映射 (PRM) 是一种基于计算机断层扫描 (CT) 的新型方法，当应用于标准 CT 扫描时，能够识别和量化各种肺部疾病亚型这项技术最初是密歇根医学院十多年前为患有以下疾病的患者开发的。在单中心和多中心试验中，PRM 已证实慢性阻塞性肺疾病 (COPD)。已证实 PRM 可以在成人 BMT 患者中识别 CLD 的功效。确定患有慢性 GVHD 的患者是否具有发展为 CLD 的高风险。观察性研究，检查患有慢性 GVHD 的成人和儿童受试者（≥ 3 岁）的 PRM BMT。为了检验我们的假设，我们制定了 3 个具体目标，在前两个目标中，我们将检查 PRM 值。在两个主要时间点：慢性 GVHD 发作时（目标 1）和 CLD 发作时（目标 2），其中 CLD 定义为根据 NIH 标准，我们将开发一个机器学习模型，将血清学和肺功能测试 (PFT) 生物标志物与 PRM 值一起开发复合生物标志物策略。完成我们当前的提案后，我们将建立 PRM 作为成人 BMT 患者 CLD 的预测因子。从儿科 BMT 患者获得的 PRM、PFT 和血清学数据将为未来提供数据库从历史上看，识别儿科患者 CLD 的能力依赖于 PFT。 PFT 在幼儿中进行在技术上具有挑战性。使用 PRM 作为 CLD 的诊断指标。在儿科 BMT 患者中的应用将是该提案的重大进步。最后，我们的提案采用了我们的 PRM。在成人中推进的方法，使我们能够研究成人 BMT 接受者的肺部疾病轨迹慢性 GVHD 以及 CLD 发作后。