SBIR Phase I: Automated Gram Stain Interpretation Via Digital Holographic Microscopy

这项小企业创新研究（SBIR）第一阶段项目的更广泛影响/商业潜力是通过对感染诊断至关重要的手动测试程序的自动化和标准化来改善医院实验室结果。更快、更高质量和更便宜的测试结果将有助于确保患者及时接受适当的药物治疗，通过自动化繁琐的实验室任务减少员工的倦怠，并降低医疗成本。正如自动化血液分析仪在很大程度上取代了人工血细胞计数一样，该平台最终将取代人工对细菌和酵母细胞的计数。作为该项目的一部分开发的新成像技术将创造先进的制造业工作岗位，并将创新产品引入外国企业主导的市场，从而提高美国的经济竞争力。对社会的长期利益包括减少抗菌素（杀死微生物的药物）耐药性，因为可以减少不必要的抗菌素。这个小企业创新研究（SBIR）第一阶段项目涉及开发一种新型显微镜平台，用于自动解释医院实验室进行的测试。该项目填补了微生物实验室面临训练有素的劳动力短缺而没有负担得起的自动化替代品的重要空白。医院的微生物实验室负责检查病人样本（如尿液和血液）中微生物（如细菌和酵母菌）的存在、类型和数量。该项目包括一个特殊光源的工程设计，一个定制的相机，以及一套人工智能（AI）算法，用于分析相机捕获的微观图像。一旦平台建成，其性能将在真实的患者样本上进行评估，通过将其与经验丰富的人类实验室技术人员进行比较，来证明该技术的可行性。该项目将测量平台产生正确答案的频率以及所需的时间。该平台还将在图像质量方面进行测试，以证明它可以拍摄最小的细菌并准确捕捉颜色。该奖项反映了美国国家科学基金会的法定使命，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 Small Business Innovation Research (SBIR) Phase I project is the improvement in hospital laboratory results by automating and standardizing a manual test procedure that is critical for the diagnosis of infections. Faster, higher quality and less expensive test results will help to ensure that patients receive timely treatment with the appropriate medications, reduce employee burnout through the automation of tedious laboratory tasks, and lower healthcare costs. Just as automated blood analyzers largely replaced manual blood cell counting, the proposed platform will eventually replace manual counting of bacteria and yeast cells. The new imaging technology developed as a part of this project will generate advanced manufacturing jobs and increase the economic competitiveness of the United States by introducing an innovative product to a market dominated by foreign firms. Long-term benefits to society include decreased antimicrobial (medicines that kill microorganisms) resistance as infections are managed with fewer unnecessary antimicrobials.This Small Business Innovation Research (SBIR) Phase I project involves the development of a novel microscopy platform for automating the interpretation of tests performed in hospital laboratories. This project fills an important gap specific to microbiology labs that are facing a trained labor shortage without affordable automated alternatives. Microbiology labs in hospitals are responsible for examining patient samples (e.g., urine and blood) for the presence, type, and quantity of microscopic organisms (e.g., bacteria and yeast). This project includes the engineering of a special light source, a customized camera, and a suite of artificial intelligence (AI)-enabled algorithms to analyze the microscopic images captured by the camera. Once the platform is built, its performance will be evaluated on real patient samples to demonstrate the feasibility of the technology by comparing it to experienced human lab technicians. The project will measure how often the platform produces the correct answer as well as how long it takes. The platform will also be tested in terms of image quality to demonstrate that it can take pictures of the smallest bacteria and accurately capture color.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.