Rapid quantitative renal fibrosis evaluation with dual-mode microscopy

使用双模式显微镜快速定量评估肾纤维化

• 批准号: 10345257
• 负责人: Farzad Fereidouni
• 金额: $ 60.44万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10345257
• 关键词: Acute; Adoption; Affect; Agreement; Algorithms; Archives; Artificial Intelligence; Atrophic; Basement membrane; Biomedical Engineering; Biopsy; Buffaloes; Caring; Cessation of life; Chemicals; Chronic Kidney Failure; Cicatrix; Clinical; Collagen; Color; Computer software; Computers; Consumption; Data; Data Science; Detection; Development; Diagnosis; Diagnostic; Disease; Disease Management; End stage renal failure; Ensure; Etiology; Evaluation; Felis catus; Fibrillar Collagen; Fibrosis; Formalin; Goals; Gold; Hematoxylin and Eosin Staining Method; Histologic; Histology; Image; Image Analysis; Injury; Institution; Interobserver Variability; Kidney; Kidney Diseases; Kidney Failure; Laboratories; Machine Learning; Manuals; Measures; Methods; Microscope; Microscopy; Morphology; Nature; Optics; Organ; Outcome; Paraffin Embedding; Pathologist; Pathology; Pathway interactions; Patient-Focused Outcomes; Patients; Performance; Preparation; Procedures; Process; Recurrence; Renal Replacement Therapy; Renal function; Reproducibility; Research; Retrospective Studies; Running; Scientist; Severity of illness; Signal Transduction; Sirius Red F3B; Site; Slide; Specimen; Speed; Staging; Stains; System; Techniques; Technology; Testing; Time; Tissue Embedding; Tissues; Translations; Trichrome stain; Trichrome stain method; Tubular formation; Universities; Validation; base; body system; clinical care; clinical practice; clinically significant; cost; deep learning; design; diagnosis standard; diagnostic value; digital; disease prognosis; fluorescence imaging; follow-up; histological stains; instrument; instrumentation; kidney allograft; kidney biopsy; kidney fibrosis; macromolecule; novel; personalized diagnostics; predict clinical outcome; prognostic model; prognostic value; stem; tool; transmission process; virtual

Abstract Kidneys, like other organs, have an inherent capacity to recover from acute injury; however, severe or recurrent injury can result in chronic kidney disease (CKD), the sequelae of which result in 82,000 deaths annually in the US alone. Regardless of the etiology of the initial injury, the common final pathway leading to- end stage renal disease is closely connected to fibrosis (excess or aberrant collagen distribution), one of the most important determinants of renal disease severity and prognosis. Histology is the gold standard for evaluation, typically using histochemical stains such as trichrome and PAS that highlight the presence of collagens and basement membrane, respectively. Nevertheless, these stains are not completely specific, can be technically challenging to perform well and reproducibly, and thus contribute to interobserver variability and a concomitant decrease in diagnostic precision. Moreover, they also require the preparation of extra slides and additional staining procedures, and thus increase cost and can prolong the diagnostic process. We propose to optimize, deploy, and test a new kind of microscope, DUET (DUal mode Emission and Transmission microscopy), developed at UC Davis, that will be a low-cost and very rapid solution for detection and digital characterization of the presence and distribution of collagen and other macromolecules, directly from standard formalin-fixed, paraffin-embedded hematoxylin and eosin-stained slides. Specifically, we will finalize the design of the hardware and software components of the instrument itself, validate imaging performance against standard histology and immunohistochemical stains for collagen and other components, and with the assistance of scientists at our partnering institutions (John Hopkins University and University of Buffalo) develop robust tools for analysis and quantitation of fibrosis. DUET instrument hardware will be shared with JHU to ensure that the methods are technically reproducible across multiple sites. The application leverages the expertise across three institutions in optics, biomedical engineering, renal pathology and novel artificial intelligence approaches. The goal of the project is development and validation of DUET, which promises to be a robust, inexpensive, and practical approach for the rapid and accurate evaluation of fibrosis, extensible to other renal pathologies, and indeed across other organs systems, with significant positive impact on disease research, clinical practice, and patient outcomes.

抽象的 肾脏与其他器官一样，具有从急性损伤中恢复的固有能力。然而，严重或 反复损伤可导致慢性肾病 (CKD)，其后遗症导致 82,000 人死亡 仅在美国每年一次。无论最初损伤的病因是什么，共同的最终途径导致- 终末期肾病与纤维化（胶原蛋白分布过多或异常）密切相关，纤维化是肾病的一种 肾病严重程度和预后的最重要决定因素。组织学是金标准 评估，通常使用组织化学染色剂（例如三色和 PAS）来突出显示 分别是胶原蛋白和基底膜。然而，这些污渍并不完全具有特异性，可以 在技​​术上具有挑战性，要表现良好且可重复，从而导致观察者间的变异性和 诊断精度随之下降。此外，他们还需要准备额外的幻灯片和 额外的染色程序，从而增加成本并可能延长诊断过程。 我们建议优化、部署和测试一种新型显微镜 DUET（双模式发射和 透射显微镜），由加州大学戴维斯分校开发，这将是一种低成本且非常快速的检测解决方案 直接对胶原蛋白和其他大分子的存在和分布进行数字表征 来自标准福尔马林固定、石蜡包埋的苏木精和伊红染色的载玻片。具体来说，我们将 最终确定仪器本身的硬件和软件组件的设计，验证成像 胶原蛋白和其他成分的标准组织学和免疫组织化学染色的性能， 并在我们的合作机构（约翰霍普金斯大学和大学）科学家的协助下 Buffalo）开发了用于纤维化分析和定量的强大工具。 DUET 仪器硬件将共享 与 JHU 合作，确保这些方法在技术上可在多个站点上重现。 该应用程序利用了光学、生物医学工程、肾病等三个机构的专业知识 病理学和新颖的人工智能方法。该项目的目标是开发和验证 DUET，它有望成为一种稳健、廉价且实用的方法，可实现快速、准确的检测 纤维化的评估，可扩展到其他肾脏病理，甚至跨其他器官系统， 对疾病研究、临床实践和患者结果产生显着的积极影响。