Quantitative in-vivo and clinical imaging (Boppart)

定量体内和临床成像 (Boppart)

• 批准号: 10705172
• 负责人: Stephen A Boppart
• 金额: $ 19.09万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2027-06-20
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705172
• 关键词: Algorithms; Apoptosis; Application procedure; Artificial Intelligence; Autophagocytosis; Binding; Biological; Biological Markers; Biophotonics; Biopsy Specimen; Cancer Detection; Catheters; Cell Death Process; Cells; Chemicals; Clinical; Clinical Medicine; Clinical Trials; Contrast Media; Decision Making; Detection; Development; Diagnosis; Diagnostic; Disease; Dyes; Endoscopes; Engineering; FDA approved; Fiber; Financial cost; Histopathology; Human; Human Subject Research; Image; Imaging Device; Imaging technology; Label; Laboratories; Laboratory Finding; Light; Lipids; Machine Learning; Maps; Measures; Medical; Medicine; Metabolic; Metabolism; Methods; Microscopic; Microscopy; Mitochondria; Modality; Molecular; Monitor; Names; Necrosis; Needles; Optical Biopsy; Optics; Organelles; Organism; Pathologic; Pathology; Patients; Performance; Phase; Photoreceptors; Procedures; Process; Research Personnel; Retina; Risk; Safety; Science; Sensitivity and Specificity; Signal Transduction; Site; Slide; Spectrum Analysis; Stains; Structure; System; Systemic disease; Technology; Thick; Time; Tissue Expansion; Tissue Stains; Tissue imaging; Tissues; Variant; Visualization; adaptive optics; base; biomedical imaging; bioprocess; clinical imaging; clinically relevant; deep learning; design; digital pathology; imaging capabilities; imaging modality; imaging probe; imaging system; improved; in vivo; in vivo imaging; instrument; multimodality; nanoparticle; new technology; novel; optical imaging; point of care; research study; single molecule; spatiotemporal; technology development; translational potential; uptake

SUMMARY It is essential that technological advances in imaging developed in the laboratory find direct translational paths to rapidly demonstrate their clinical utility in patients, and establish the potential for improving detection, diagnosis, and monitoring of disease. While label-based optical imaging modalities have demonstrated potential in intraoperative cancer detection, mapping the microvasculature, and site-specifically targeting of altered metabolism and pathology, to name a few, these approaches often come at a significant time and financial cost due to the associated safety risks and lengthy review processes required for FDA approval of any new contrast agent or probe. Importantly, any new targeted contrast agent or probe inevitably will have some degree of non- specific binding or off-target labeling, as well as a variable degree of uptake or labeling of the targeted cell or site. In the end, the measured or imaged signal levels are always questioned. Is the signal low because the targeted pathology is minimal, or because the targeted efficiency of labeling is low? The importance of label-free imaging is therefore high, and the need for label-free imaging across size scales is great. By identifying robust label-free signals or biomarkers that indicate changes in structure, molecular composition, metabolism, and function, quantitative clinical and in vivo imaging not only becomes a feasible alternative to label-based methods, but also provides a direct and rapid translational path to clinical human studies, since regulatory approval is not additionally needed for a contrast agent or probe. This enables rapid in vivo first-to-human and limited-scale human subjects research studies (and subsequently larger clinical trials) to be performed with the new optical imaging technologies, and make early determination of the clinical utility of the technologies and the new optical biomarkers that they generate. This TRD focuses on the technological development through four specific aims that progress from 1) the sub-cellular and cellular scale, identifying optical biomarkers and signatures that would indicate more systemic disease processes, to 2) tissue sections in an advanced digital pathology platform with artificial intelligence, to 3) computational optical imaging algorithms that extend the depth and performance of optical imaging in thick tissues, and finally to 4) engineered beam delivery systems to widely expand tissue access and application for these label-free optical imaging modalities. Collectively, this project will demonstrate novel technological advances that will find a myriad of applications to advance the biological and medicine sciences, and improve diagnostic and monitoring capabilities in clinical medicine.

总结 至关重要的是，在实验室中开发的成像技术进步找到了直接的平移路径 为了快速证明其在患者中的临床效用，并建立改进检测的潜力， 诊断和监测疾病。虽然基于标签的光学成像模式已经证明了其潜力， 在术中癌症检测、微血管绘图和改变的位点特异性靶向中， 代谢和病理学，仅举几例，这些方法通常需要大量的时间和经济成本 由于相关的安全风险和FDA批准任何新造影剂所需的冗长审查过程， 代理或探针。重要的是，任何新的靶向造影剂或探针不可避免地将具有一定程度的非靶向性。 特异性结合或脱靶标记，以及靶细胞的可变程度的摄取或标记，或 绝佳的价钱最后，测量或成像的信号电平总是受到质疑。信号低是因为 靶向病理是最小的，还是因为标记的靶向效率低？标签免费的重要性 因此，成像要求很高，并且非常需要跨越尺寸尺度的无标记成像。通过识别鲁棒 无标记信号或生物标志物，其指示结构、分子组成、代谢和 功能，定量临床和体内成像不仅成为基于标记的方法的可行替代方案， 而且还为临床人体研究提供了直接和快速的转化途径，因为监管批准并不 造影剂或探针另外需要。这使得能够快速地在体内首次用于人类和有限规模的 人类受试者研究（以及随后的更大规模的临床试验）将使用新的光学 成像技术，并尽早确定该技术的临床实用性和新的光学 它们产生的生物标志物。该TRD通过四个具体目标关注技术发展 从1）亚细胞和细胞尺度，识别光学生物标志物和签名， 指示更多系统性疾病过程，2）先进数字病理学平台中的组织切片， 人工智能，3）计算光学成像算法，扩展了深度和性能， 厚组织中的光学成像，最后是4）工程光束传输系统，以广泛扩展组织 这些无标记光学成像模式的访问和应用。总的来说，这个项目将证明 新的技术进步，将发现无数的应用，以促进生物和医学 科学，并提高临床医学的诊断和监测能力。