I-Corps: Chemometric fluorescence microscopic imaging and virtual staining for rapid label-free histopathology

这个I-Corps项目的更广泛的影响/商业潜力是能够进行稳健、快速和无标签的生物样品评价。癌症是一个全球性的公共卫生问题，其诊断目前依赖于对生物材料样本的评估。迫切需要时间有效和客观的替代方法来解决现有过程的几个缺点，这些缺点是耗时，劳动密集型，并受到解释者的变化。 拟定项目是一种在未处理或最低限度处理的细胞和组织标本上使用光照的经确认方法。所提出的方法，特别是满足快速和准确的诊断在手术室和远程病理学实验室的需求。 该I-Corps项目旨在推进未染色细胞和组织标本的化学计量荧光显微成像和虚拟染色（CFM-VS）的翻译。使用内源性细胞荧光，CFM产生2D图像，揭示亚细胞形态和功能，视觉上区分特定的细胞特性，包括结构，细胞代谢和蛋白质生产。CFM的一个独特优势是对内源性荧光生物分子的绝对浓度进行定量，从而实现可靠和准确的诊断。CFM及其衍生的虚拟染色（CFM-VS）已成功应用于肺癌和前列腺癌的鉴别诊断。未染色的组织切片的虚拟染色图像不仅共享传统苏木精和伊红（HE）染色图像对应物的形态，而且指示由于癌症引起的生化改变。CFM-VS的吸引人的特征包括：能够接近实时地对未处理或最小处理的细胞和组织切片进行成像;产生&病理学家熟悉的虚拟HE染色图像;消除组织处理中引入的失真;该奖项反映了NSF的法定使命，被认为是值得的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，

The broader impact/commercial potential of this I-Corps project is to enable robust, rapid, and label-free biological sample evaluation. Cancer is a worldwide public health problem, and its diagnosis currently depends on evaluation of specimens of biological material. Time-efficient and objective alternative methods are urgently needed to address several shortcomings of the existing process, which is time-consuming, labor-intensive, and subject to interpreter variations. The proposed project is a validated method using light on unprocessed or minimally processed cell and tissue specimens. The proposed method particularly meets the demands of rapid and accurate diagnosis in surgical suites and telepathology laboratories. This I-Corps project is to advance the translation of chemometric fluorescence microscopic imaging and virtual staining (CFM-VS) on unstained cell and tissue specimens. Using endogenous cellular fluorescence, CFM produces 2D images revealing both subcellular morphology and function, visually differentiating specific cell properties including structure, cellular metabolism, and protein production. One unique advantage of CFM is the quantification of the absolute concentration of the endogenous fluorescent biomolecules, enabling reliable and accurate diagnosis. CFM and the derived virtual staining (CFM-VS) have been successfully applied to differentiate and diagnose lung and prostate cancers. The virtually stained images for unstained histological slides not only share the morphology of traditional hematoxylin and eosin (H&E) stained image counterparts, but also indicate the biochemical alterations due to cancer. Attractive features of CFM-VS include: ability to image unprocessed or minimally processed cell and tissue sections in close to real-time; yields virtual H&E stained images familiar to pathologists; eliminates distortions introduced in tissue processing; and robust diagnosis is achieved and may be improved through adaption of the algorithm from learning with the accumulation of data.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.