STTR Phase I: An automated digital pathology lab for rapid on-site processing and imaging of tissue biopsies

STTR 第一阶段：自动化数字病理学实验室，用于组织活检的快速现场处理和成像

• 批准号: 1820258
• 负责人: Mei Wang
• 金额: $ 22.5万
• 依托单位: Instapath Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1820258&HistoricalAwards=false
• 关键词: STTR; Phase; automated; digital; pathology

This STTR Phase 1 project seeks to develop an automated system that would significantly increase the speed and accuracy of biopsy assessments at the point of care. The proposed technology eliminates extensive manual tissue processing steps and generates digital images of fresh biopsies that look just like standard pathology slides. The imaging can be performed in seconds, thus improving the efficiency of biopsy assessments at the point of care. Rapid, whole fresh biopsy imaging also improves evaluation accuracy while maximally preserving tissue for further testing and facilitating remote pathology consultation. With over five million patients in the United States undergoing biopsy procedures each year, and one in five of those patients returning for repeat procedures due to inaccuracies in biopsy assessments, an increase in accuracy and procedure speed could have a profound impact. This could lead to decreases in patient procedure time and decreases in repeat procedure rates, preventing unnecessary, painful, and invasive repeat biopsy procedures. With an estimated 1.6 billion USD spend on repeat procedures per year, this would also represent a significant decrease in financial burden on patients. In addition, due to the decrease in time per procedure, this could increase procedure throughput for hospitals, thus increasing hospital revenue potential. Finally, by producing remotely viewable images, this system could be utilized in a remote pathology setting at underserved communities within the US.This STTR Phase I project seeks to develop an automated sample processing and tissue pathology imaging system that delivers biopsy-to-image in a completely automated manner on fully-intact fresh tissues within five minutes of tissue removal. Through integration with the previously developed Video-Rate Structured Illumination Microscopy (VR-SIM) system as the integrated optical sectioning modality, and using novel fluorescence dye combinations that recapitulate gold-standard histology, the throughput, efficiency, and accuracy of biopsy evaluation can be improved while maximally preserving tissue for downstream processing and readily facilitating telepathology consultation. Preliminary work in multiple fresh tissue preparations, including core-needle biopsies and whole surgical resections, indicates that the technology and method can deliver high image quality and diagnostic accuracy in short, clinically-relevant timeframes. A prototype of an automated, disposable cartridge system for biopsy staining and imaging for effortless integration with VR-SIM imaging will be developed. Image quality will be optimized at the highest optical sectioning power to be equivalent to physically-sectioned tissues, using polarization-gated VR-SIM and novel immersion media. ADPL workflow testing, validation of diagnostic image quality, and verification of compatibility with downstream analysis in human biopsy samples will be completed.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.

STTR 第一阶段项目旨在开发一种自动化系统，该系统将显着提高护理点活检评估的速度和准确性。所提出的技术消除了大量的手动组织处理步骤，并生成新鲜活检的数字图像，看起来就像标准病理学幻灯片一样。成像可以在几秒钟内完成，从而提高了护理点活检评估的效率。快速、完整的新鲜活检成像还可以提高评估准确性，同时最大限度地保留组织以进行进一步测试并促进远程病理咨询。美国每年有超过 500 万患者接受活检手术，其中五分之一的患者由于活检评估不准确而返回重复手术，因此准确性和手术速度的提高可能会产生深远的影响。这可能会减少患者手术时间和重复手术率，从而防止不必要的、痛苦的和侵入性的重复活检手术。每年重复手术的费用估计为 16 亿美元，这也意味着患者的经济负担显着减轻。此外，由于每次手术时间的减少，这可能会增加医院的手术吞吐量，从而增加医院的收入潜力。最后，通过生成可远程查看的图像，该系统可用于美国服务欠缺社区的远程病理学环境。该 STTR 第一阶段项目旨在开发一种自动化样本处理和组织病理学成像系统，可在在组织去除后五分钟内，以完全自动化的方式对完整的新鲜组织进行处理。 通过与先前开发的视频速率结构照明显微镜 (VR-SIM) 系统集成作为集成光学切片模式，并使用重现金标准组织学的新型荧光染料组合，可以提高活检评估的吞吐量、效率和准确性。得到改善，同时最大限度地保留组织用于下游处理，并轻松促进远程病理咨询。多种新鲜组织制备（包括芯针活检和整个手术切除）的初步工作表明，该技术和方法可以在较短的临床相关时间范围内提供高图像质量和诊断准确性。将开发用于活检染色和成像的自动化一次性盒式系统原型，以便与 VR-SIM 成像轻松集成。使用偏振门控 VR-SIM 和新型浸没介质，在最高光学切片功率下优化图像质量，使其与物理切片组织相当。 ADPL 工作流程测试、诊断图像质量验证以及与人体活检样本下游分析的兼容性验证即将完成。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。