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 由于没有可靠的手段 确定可用于移植的肾脏的可行性。有未满足的临床需要减少> 8,000 每年因寻找可行的肾脏匹配的失败而发生的死亡，以减少接近4-- 捐赠者候补名单的一年时间，并减少移植失败的数量。当前筛选过程 已故的供体肾脏使用两种方法：1）基于活检的解剖学特征的病理得分 （管，glomerulli等）和2）肾脏供体档案指数（KDPI）来自捐赠者的病史 （高血压，糖尿病，体重等）。但是，临床研究表明这些当前方法具有 有限的判别能力。光学相干断层扫描（OCT）是一种可以获得的成像技术 生物组织的高分辨率，非侵入性的横截面图像。我们有 证明OCT可以提供肾脏的非侵入性，实时的组织病理学信息 无法使用任何其他已知程序获得。我们已经证明了人类的十点成像 肾脏组织病理学在移植之前和之后都可以用于预测移植后肾脏 功能。此外，这些初步试验证明了人类供体肾脏的OCT成像 手术室中有一个手持单元是安全的，可以在亲戚中评估整个肾脏 短时间。从最近完成的临床研究中，有169个人类移植儿童，我们发现 扩展的标准供体（ECD）肾脏（或边缘肾脏），肾小管直径增加能够 预测植入之前的延迟移植功能（DGF）。在此提案中，我们将开发一个新颖的OCT设备 通过智能扫描和深度学习，可以在移植前评估供体肾脏生存能力。通过扫描 整个肾脏表面，我们的设备打算消除活检/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，以建立成像算法 以及孩子在移植之前对OCT成像的指南。我们的中心假设是 通过OCT测量的全面形态参数可用于确定移植后 肾功能。该提案的具体目的是：1）开发机器人辅助自动3D扫描OCT 成像装置在移植之前成像人肾脏。 2）开发基于深度学习的图像 处理算法以定量评估OCT参数作为功能状态的指标 肾脏，使用组织学评分系统作为黄金标准。 3）得出评估的诊断标准 移植肾功能并进行前瞻性临床研究，以评估预测后预测的准确性 使用OCT的移植功能。