Characterization of Renal Allograft Fibrosis and Prediction of Outcome Using a Quantitative MRI Approach

使用定量 MRI 方法表征同种异体肾纤维化并预测结果

基本信息

批准号：
10447657
负责人：
Octavia Bane
金额：
$ 60.18万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-07-08 至 2026-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10447657
关键词：
Acute Affect Allografting Area Atrophic Biological Markers Biopsy Blood Vessels Caring Cells Chronic Chronic Kidney Failure Classification Clinical Collagen Data Detection Development Diagnosis Diagnostic Diffusion Diffusion Magnetic Resonance Imaging Disease Disease Progression Early Diagnosis Edema End stage renal failure Endothelium Epithelial Cells Etiology Failure Fibrosis Functional disorder Goals Histopathology Immune Immunosuppression Infection Infiltration Inflammation Injury Injury to Kidney Kidney Kidney Transplantation Lesion Living Donors Longitudinal Studies Machine Learning Magnetic Resonance Imaging Measurement Measures Methods Modeling Modernization Monitor Motion Nature Outcome Pathology Pathway interactions Patient Monitoring Patient-Focused Outcomes Patients Performance Perfusion Phenotype Physiological Prevalence Process Proteinuria Protocols documentation RNA Reference Standards Relaxation Reproducibility Risk Sampling Errors Severities Staging Statistical Methods Statistical Models Structure Techniques Testing Time Tissue Sample Tissues Transplant Recipients Treatment Efficacy Tubular formation United States Validation Water antifibrotic treatment base clinical encounter clinically significant cohort comparative diffusion weighted experience feature selection improved insight inter-individual variation interstitial kidney allograft kidney biopsy kidney dysfunction machine learning model macromolecule model building mortality novel novel therapeutics outcome prediction patient population post-transplant predict clinical outcome prognostic prognostication renal damage secondary outcome statistical and machine learning treatment choice treatment optimization treatment planning urinary virtual

项目摘要

Project Summary Renal transplantation is the treatment of choice for patients with end stage renal disease. However, improvements in long-term allograft survival have not matched the observed improvements in the management of rejection. Progressive allograft dysfunction is frequently encountered clinically. The final common pathway of cumulative and incremental renal damage from several etiologies identified by histopathology is interstitial fibrosis/tubular atrophy (IFTA), which is associated with progression of renal dysfunction and reduced allograft survival. Histopathologic assessment and staging of IFTA requires tissue sampling, which is limited due to its invasive nature, risk of complications, inter-individual variability and sampling error. In this proposal, we will test a non-contrast advanced multiparametric MRI (mpMRI) protocol comprised of advanced relaxometry (T1 mapping and T1) and advanced diffusion weighted imaging (IVIM-DWI) as noninvasive markers of renal allograft fibrosis. This is motivated by our preliminary data demonstrating that mpMRI yields highly repeatable parameter measurements that capture allograft fibrosis. Our preliminary experience correlating mpMRI with IFTA is valuable, as confounding physiologic and pathophysiologic variables such as vascular flow, edema and other Banff phenotypes commonly co-exist. The multiparametric approach allows us to simultaneously capture and characterize these concurrent physiologic and pathophysiologic processes. As a secondary objective, we will assess the value of urinary RNA level based biomarkers, which have been previously validated for the diagnosis of IFTA. In this proposal, we aim to: 1) acquire data in patients undergoing indication and surveillance biopsy, using a non-contrast mpMRI protocol comprised of advanced diffusion weighted and relaxometry methods in order to accurately detect and stage allograft IFTA, and 2) other histopathological Banff measures of inflammation. We will build and validate diagnostic models using advanced statistical methods including machine learning in independent model-building and validation sets of renal transplant patients for detection and staging of each Banff measure, and assess the added value of urinary biomarkers of fibrosis. 3) We will evaluate the performance of mpMRI and urinary biomarkers to predict renal outcomes in a longitudinal study for the entire patient cohort up to 24 months. Our long-term objective is to validate a robust quantitative advanced mpMRI approach and develop models that accurately and non-invasively measure renal allograft fibrosis and clinical outcome, which may potentially impact the care of renal transplant patients by enabling early detection, the non-invasive longitudinal monitoring of disease, therapeutic efficacy of new drugs and for prognostication.

项目概要肾移植是终末期肾病患者的首选治疗方法。长期同种异体移植物存活率的改善与观察到的管理改善不相匹配临床上经常遇到进行性同种异体移植功能障碍。组织病理学确定的几种病因引起的累积性和增量性肾损伤是间质性的纤维化/肾小管萎缩（IFTA），与肾功能障碍的进展和同种异体移植物减少有关 IFTA 的组织病理学评估和分期需要组织取样，但由于其存活率而受到限制。侵入性、并发症风险、个体差异和采样误差。在本提案中，我们将测试非对比高级多参数 MRI (mpMRI) 协议，其中包括先进的松弛测量（T1 映射和 T1）和先进的扩散加权成像 (IVIM-DWI) 肾同种异体移植物纤维化的非侵入性标记物是由我们的初步数据证明的。 mpMRI 产生高度可重复的参数测量，捕获同种异体移植物纤维化。将 mpMRI 与 IFTA 相关联的经验很有价值，因为混淆了生理学和病理生理学血管流量、水肿和其他班夫表型等变量通常同时存在。方法使我们能够同时捕获和表征这些并发的生理和作为次要目标，我们将评估基于尿液 RNA 水平的价值。生物标志物，之前已被验证可用于 IFTA 的诊断。在本提案中，我们的目标是：1）使用非对比 mpMRI 协议由先进的扩散加权和松弛测量方法组成，以便准确检测同种异体移植物 IFTA 并进行分期，以及 2) 其他炎症组织病理学 Banff 测量。将使用先进的统计方法（包括机器学习）构建和验证诊断模型肾移植患者的独立模型构建和验证集，用于每个患者的检测和分期 Banff 测量并评估尿纤维化生物标志物的附加值 3) 我们将评估 mpMRI 和尿液生物标志物的性能在整个纵向研究中预测肾脏结果患者队列长达 24 个月。我们的长期目标是验证稳健的定量先进 mpMRI 方法并开发模型准确且非侵入性地测量肾同种异体移植纤维化和临床结果，这可能是通过实现早期检测、非侵入性纵向监测来影响移植肾患者的护理监测疾病、新药的治疗效果和预测。