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.

概括 在实验室中开发的成像的技术进步至关重要 快速证明他们在患者中的临床实用性，并建立了改善检测的潜力 诊断和监测疾病。虽然基于标签的光学成像方式表明了潜力 在术中癌症检测中 仅举几样，这些方法通常以大量时间和经济成本出现 由于相关的安全风险和FDA批准任何新对比所需的冗长的审核过程 代理或探测器。重要的是，任何新的靶向对比剂或不可避免地都会有一定程度的非 - 特定的结合或脱靶标记，以及目标细胞的摄取程度或标记程度可变 地点。最后，始终质疑测得的或成像的信号水平。是信号低，因为 靶向病理是最小的，或者是因为标记的目标效率较低？无标签的重要性 因此，成像很高，并且需要跨大小尺度的无标签成像。通过识别强大的 无标签信号或生物标志物，表明结构变化，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签的方法的可行替代方案，还可以 但也为临床人类研究提供了直接和快速的转化途径，因为监管批准不是 另外需要造影剂或探针。这使得在体内快速至人类和有限尺度 人类受试者的研究研究（随后进行较大的临床试验）将使用新的光学进行 成像技术，并尽早确定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通过四个特定目标专注于技术发展 从1）从1）亚细胞和细胞尺度进行了识别的光学生物标志物和特征 指出更多的全身性疾病过程，至2）在高级数字病理平台中的组织切片， 人工智能，至3）扩展了深度和性能的计算光学成像算法 厚组织中的光学成像，最后到4）工程束输送系统，以广泛扩展组织 这些无标签的光学成像方式的访问和应用。总体而言，这个项目将证明 新的技术进步将找到无数的应用来推进生物学和医学 科学，并提高临床医学的诊断和监测能力。