I-Corps: Ultrahigh resolution human tissue imaging platform

这个I-Corps项目更广泛的影响/商业潜力是开发一个深度学习授权的超高分辨率人体组织成像平台。 该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，并观察活检中与疾病相关的细微变化。 其目标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。 据设想，该平台可用于开发测试，以早期确定哪些癌症治疗对某些患者有效，并为临床医生提供即时指导，以便在疾病状况恶化或转移之前做出最佳决策。 这项技术的潜在社会影响是重要的，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项目是基于超分辨率光学成像技术的发展。所提出的技术通过利用组织扩张克服了传统光学显微镜的基本分辨率限制，组织扩张是一种将组织化学嵌入水溶胀性水凝胶中并物理扩张的过程。这允许使用临床研究实验室中常用的传统荧光显微镜对组织的纳米级细节进行更详细的观察。所提出的过程被设计为将生物样本扩展到11倍，并且使用传统光学显微镜以有效的~25 nm分辨率或与超分辨率光学波动成像结合时以~15 nm有效分辨率进行成像。所提出的平台可以通过结合深度学习从病理标本中提取可操作的信息。这样的信息否则使用现有的病理成像技术（例如明场和荧光成像）是不可用的。此外，所提出的平台可以与商业多路复用成像平台兼容，并且可以提供强大的测定来揭示健康和患病组织的复杂空间组学图谱和信号通路，这对于临床前开发至关重要。该技术可用于广泛的生物标本，并允许使用生物医学研究实验室中常用的荧光显微镜对组织中的纳米级结构进行更详细的观察。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.