I-Corps: Ultrahigh resolution human tissue imaging platform

I-Corps：超高分辨率人体组织成像平台

• 批准号: 2324844
• 负责人: Yongxin Zhao
• 金额: $ 5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324844&HistoricalAwards=false
• 关键词: Corps; Ultrahigh; resolution; human; tissue

The broader impact/commercial potential of this I-Corps project is the development of a deep learning-empowered, ultrahigh-resolution human tissue imaging platform. The proposed technology is designed to enable biomedical researchers and pathologists to obtain nanoscale insights into human tissues and observe subtle disease-related changes in biopsies. The goal is to provide a tool to support biomedical research, pre-clinical drug development, and predict cancer patients’ prognosis and treatment outcomes. It is envisioned that this platform may be used for the development of tests to identify early on which cancer treatments will be effective for certain patients, and provide immediate guidance for clinicians to make optimal decisions before disease conditions worsen or metastasize. The potential societal impact of this technology is significant as it may improve diagnosis, treatment response prediction, and healthcare outcomes. This I-Corps project is based on the development of super-resolution optical imaging technology. The proposed technology overcomes the fundamental resolution limits of conventional optical microscopes by utilizing tissue expansion, a process whereby the tissue is chemically embedded into a water-swellable hydrogel and physically expanded. This allows for a more detailed view of the nanoscopic details of tissue using a traditional fluorescent microscope commonly accessible in clinical research labs. The proposed process is designed to expand biological specimens up to 11-fold and facilitates imaging with effectively ~25 nm resolution using conventional optical microscopes or with ~15 nm effective resolution when combined with Super Resolution Optical Fluctuation Imaging. The proposed platform can extract actionable information from pathology specimens by combining deep learning. Such information is otherwise unavailable using existing pathological imaging techniques, such as bright field and florescent imaging. In addition, the proposed platform may be compatible with commercial multiplexing imaging platforms and may offer a powerful assay to reveal the complex spatial omics maps and signaling pathways of healthy and diseased tissues, which is essential for pre-clinical development. The proposed technology may be used with a broad range of biological specimens and allows for a more detailed view of nanoscopic structures in tissues using fluorescent microscopy commonly accessible in biomedical research laboratories.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该I-Corps项目的更广泛的影响/商业潜力是开发深度学习的超高分辨率人体组织成像平台。该提出的技术旨在使生物医学研究人员和病理学家能够获得对人体组织的纳米级见解，并观察到与疾病相关的微妙变化。目的是提供一种工具来支持生物医学研究，临床前药物开发并预测癌症患者的预后和治疗结果。可以预见的是，该平台可用于开发测试，以识别哪些癌症治疗对某些患者有效，并为临床医生提供直接指导，以便在疾病状况恶化或转移疾病之前做出最佳决策。该技术的潜在社会影响很大，因为它可以改善诊断，治疗反应预测和医疗保健结果。这个I-Corps项目基于超分辨率光学成像技术的开发。该提出的技术通过利用组织扩展克服了传统光学显微镜的基本分辨率限制，从而将组织化学嵌入到水的水凝胶中并物理扩展。这允许使用临床研究实验室通常可以使用的传统荧光显微镜对组织的纳米镜细节进行更详细的了解。该提出的过程旨在扩展生物学标本最多11倍和设施成像，并使用常规光学显微镜有效分辨率约为25 nm，或者与超级分辨率光波动成像结合使用时约15 nm有效分辨率。所提出的平台可以通过结合深度学习来从病理标本中提取可行的信息。否则，使用现有的病理成像技术（例如明亮的场和荧光成像），这些信息是无法使用的。此外，所提出的平台可能与商业多路复用成像平台兼容，并可能提供有力的测定法，以揭示健康和解散的组织的复杂空间上的OMICS图和信号传导途径，这对于临床前开发至关重要。该提出的技术可以与广泛的生物标本一起使用，并可以使用荧光显微镜在生物医学研究实验室中访问的荧光显微镜在技巧中更详细地了解纳米镜结构。这项奖项反映了NSF的法定任务，并被认为是通过该基金会的知识绩效和广泛的影响来评估的法定任务，并被认为是珍贵的支持。