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: 10501992
• 负责人: Yu Chen
• 金额: $ 67.19万
• 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/10501992
• 关键词: 3-Dimensional; Acute Kidney Failure; Algorithms; Anatomy; Area; Biological; Biopsy; Caliber; Cessation of life; Clinic; Clinical; Clinical Research; Data; Device or Instrument Development; Devices; Diabetes Mellitus; Discrimination; Donor person; End stage renal failure; Failure; Generations; Goals; Gold; Guidelines; Hand; Healthcare; Histologic; Histology; Histopathology; Human; Hypertension; Image; Imaging Device; Imaging technology; Immunologics; In Situ; Intelligence; 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; base; 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 biopsy; 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.

总结 目前世界范围内用于移植的肾脏短缺，主要原因是没有可靠的方法 以确定可供移植的肾脏的存活能力。有未满足的临床需求，以减少> 8，000 每年因未能找到可供移植的肾脏而死亡的人数，减少了近4- 这将有助于减少等待捐赠者名单上的时间，并减少移植失败的数量。目前的筛选程序 死亡供体肾脏使用两种方法：1）基于来自活组织检查的解剖特征的病理学评分 （小管、肾小球等）以及2）从供体的病史中得出的肾脏供体概况指数（KDPI （高血压、糖尿病、体重等）。然而，临床研究表明，这些现有的方法 有限的辨别力。光学相干断层扫描（OCT）是一种成像技术， 原位和真实的时间的生物组织的高分辨率、非侵入性、横截面图像。我们有 表明OCT可以提供非侵入性的，实时的，肾脏的组织病理学信息， 这是不可能用任何其他已知的方法得到的。我们已经证明，OCT成像的人类 移植前和移植后的肾组织病理学可用于预测移植后肾功能 功能此外，这些初步试验已经证明，人类供体肾脏的OCT成像 在手术室中使用手持设备是安全的，并且整个肾脏可以在相对较短的时间内进行评估。 短时间从最近完成的一项对169个人类移植肾脏的临床研究中，我们发现， 扩大标准供体（ECD）肾（或边缘肾），增加管腔直径能够 在植入前预测移植物功能延迟恢复（DGF）。在本计画中，我们将发展一种新颖的光学相干断层扫描装置 通过智能扫描和深度学习，在移植前评估供体肾脏的存活率。通过扫描 通过在整个肾脏表面进行活检，我们的设备旨在消除由活检/KDPI范例产生的不确定性。的 OCT成像研究将与移植后肾功能相关，以建立成像算法 以及移植前肾脏OCT成像指南。我们的核心假设是， 通过OCT测量的综合形态学参数可用于确定移植后 肾功能本课题的具体目标是：1）研制机器人辅助的自动三维扫描OCT 成像设备，以在移植之前对人类肾脏进行成像。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，以评估预测术后 移植功能使用OCT。