Automatic Wide-Field Optical Coherence Tomography for Assessment of Transplant Kidney Viability

用于评估移植肾活力的自动广域光学相干断层扫描

• 批准号: 10700999
• 负责人: Steven Potter
• 金额: $ 62.63万
• 依托单位: UNIVERSITY OF MASSACHUSETTS AMHERST
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10700999
• 关键词: 3-Dimensional; Acute Kidney Failure; Algorithms; Anatomy; Area; Biological; Biopsy; Cessation of life; Clinic; Clinical; Clinical Research; Collaborations; Data; Device or Instrument Development; Devices; Diabetes Mellitus; Diameter; Discrimination; Donor person; End stage renal failure; Failure; Generations; Goals; Guidelines; Healthcare; Histologic; Histology; Histopathology; Human; Hypertension; Image; Imaging Device; Imaging technology; Immunologics; In Situ; Intelligence; Ischemia; Kidney; Kidney Diseases; Kidney Transplantation; Location; Maps; Measures; Medical History; Medical center; Methods; Morphology; Nephrology; Oklahoma; Operating Rooms; Operative Surgical Procedures; Optical Coherence Tomography; Organ Donor; Organ Procurements; Organ Transplantation; Outcome; Pathologic; Pathology; Patients; Procedures; Process; Quality of life; Renal function; Resolution; Risk; Robotics; Sampling; Scanning; Site; Specificity; Surface; System; Technology; Testing; Time; Tissues; Training; Translating; Transplantation; Tubular formation; Uncertainty; Validation; Visual; Waiting Lists; Weight; algorithm development; care burden; cohort; deep learning; deep learning model; delayed graft function; diagnostic criteria; functional status; graft failure; graft function; high resolution imaging; high risk; human imaging; image processing; imaging study; implantation; improved; indexing; kidney imaging; novel; post-transplant; predictive modeling; prognostic; prospective; robot assistance; screening; tool; virtual

Summary There is a worldwide shortage of kidneys for transplantation due mainly to the fact that there is no reliable means to determine the viability of kidneys available for transplant. There are unmet clinical needs to reduce the >8,000 deaths that occur each year from failures of finding viable kidney matches for transplant, to reduce the nearly 4- year time on donor waitlists, and to reduce the number of failed transplants. The current process for screening deceased donor kidneys uses two methods: 1) pathological scores based on anatomical features from a biopsy (tubules, glomeruli, etc.) and 2) the Kidney Donor Profile Index (KDPI) derived from the donor’s medical history (hypertension, diabetes, weight, etc.). However, clinical research indicates that those current methods have limited discriminative power. Optical coherence tomography (OCT) is an imaging technology that can obtain high-resolution, non-invasive, cross-sectional images of biological tissues in situ and in real time. We have demonstrated that OCT can provide non-invasive, real-time, histopathological information of the kidney that is impossible to obtain using any other known procedure. We have demonstrated that OCT imaging of human kidney histopathology both prior to and following their transplant can be used to predict post-transplant renal function. Furthermore, these preliminary trials have demonstrated that OCT imaging of human donor kidneys with a hand-held unit in the operating room is safe and that the entire kidney can be evaluated within a relatively short period of time. From a recently finished clinical study with 169 human transplant kidneys, we found that in the expanded criteria donor (ECD) kidneys (or marginal kidneys), increased tubular lumen diameter was able to predict delayed graft function (DGF) prior to implantation. In this proposal, we will develop a novel OCT device with intelligent scanning and deep learning to evaluate donor kidney viability before transplant. By scanning the whole kidney surface, our device intends to eliminate the uncertainty created by the biopsy/KDPI paradigm. The OCT imaging studies will be correlated with post-transplant renal function in order to establish imaging algorithms and guidelines for OCT imaging of kidneys prior to their transplant. Our central hypothesis is that more comprehensive morphological parameters as measured by OCT can be used to determine post-transplantation renal function. The specific aims of this proposal are: 1) Develop robot-assisted automatic 3D scanning OCT imaging device to image human kidneys prior to their transplantation. 2) Develop deep-learning-based image processing algorithms to quantitatively assess the OCT parameters as indicators of the functional status of kidneys, using histology scoring system as the gold standard. 3) Derive the diagnostic criteria for assessing transplant kidney function and perform prospective clinical studies to assess the accuracy of predicting post- transplant function using OCT.

概括 全球范围内用于移植的肾脏短缺，主要原因是没有可靠的手段 以确定可用于移植的肾脏的活力。尚有未满足的临床需求，需要减少 >8,000 每年因未能找到可行的肾脏匹配移植而导致的死亡，以减少近 4- 捐赠者等待名单上的一年时间，并减少移植失败的数量。目前的筛选流程 已故捐献肾脏使用两种方法：1) 基于活检解剖特征的病理评分 （肾小管、肾小球等）和 2) 源自捐赠者病史的肾脏捐赠者概况指数 (KDPI) （高血压、糖尿病、体重等）。然而，临床研究表明，目前的这些方法已经 有限的歧视权力。光学相干断层扫描（OCT）是一种成像技术，可以获取 生物组织原位实时高分辨率、非侵入性横截面图像。我们有 证明 OCT 可以提供非侵入性、实时的肾脏组织病理学信息， 使用任何其他已知程序不可能获得。我们已经证明，人类的 OCT 成像 移植前和移植后的肾脏组织病理学可用于预测移植后的肾脏 功能。此外，这些初步试验表明，人类供体肾脏的 OCT 成像 在手术室使用手持式设备是安全的，并且可以在相对较短的时间内对整个肾脏进行评估 很短的一段时间。从最近完成的一项针对 169 例人体移植肾脏的临床研究中，我们发现 扩大标准供体（ECD）肾脏（或边缘肾），增加管腔直径能够 在植入前预测延迟移植物功能（DGF）。在本提案中，我们将开发一种新型 OCT 设备 通过智能扫描和深度学习在移植前评估供体肾脏的活力。通过扫描 整个肾脏表面，我们的设备旨在消除活检/KDPI 范式产生的不确定性。这 OCT 成像研究将与移植后肾功能相关联，以建立成像算法 以及移植前肾脏 OCT 成像指南。我们的中心假设是更多 OCT 测量的综合形态参数可用于确定移植后情况 肾功能。该提案的具体目标是：1）开发机器人辅助自动3D扫描OCT 在移植前对人类肾脏进行成像的成像装置。 2）开发基于深度学习的图像 定量评估 OCT 参数作为功能状态指标的处理算法 肾脏，使用组织学评分系统作为金标准。 3) 推导评估诊断标准 移植肾功能并进行前瞻性临床研究以评估预测移植后肾功能的准确性 使用 OCT 进行移植功能。