Development and evaluation of a combined X-ray transmission and diffraction imaging system for pathology

摘要 病理学在临床诊断中起着至关重要的作用，它面临着许多影响其疗效的挑战。为 例如，切除的标本通常需要准备和分析多达30-40个载玻片。 显微镜，直到疾病被确认；切片的选择使用主观方法，如 作为触诊，这在很大程度上取决于执行评估的个人的技能，并介绍 临床过程中的不一致；对于检查的每个幻灯片，分析和注释需要手动 观察组织的每一个微观区域。因此，大多数病理评估通常需要1-3次。 几周的时间来分析样本并得出关于潜在癌症的结论。另一个挑战是， 无论处理了多少个滑块，保险报销金额都是有上限的， 额外的费用由医院承担。因此，医院必须平衡两者之间的权衡 最大限度地减少切片数量(为了经济上的可行性)，并且不影响诊断护理。这些挑战 不仅影响临床病理，而且影响涉及病理标本和组织选择的研究 生物库。迫切需要消除主观性，减少病理学家的工作量，增加 组织学分析中的吞吐量。我们建议通过开发一种名为X射线的新技术来满足这一需求 衍射成像(XRDi)，它可以扫描任何数量的手术切除的切片病理标本和 在几分钟内自动在每个切片中指示疾病的可能性和位置。与 之前，我们构建了一个研究原型XRDi系统，并通过扫描演示了它的实用性 以及对300个乳腺癌切片进行高精度和高分辨率的评估。在这个直接到第二阶段的SBIR中 应用，我们现在将构建一个新的临床版本的XRDi扫描仪，它是负担得起的，可靠的，和 准确，可直接集成到临床病理工作流程中。我们将建造扫描仪，测试和 评估其性能，并通过现场测试与临床病理学相结合来展示其有效性 美国的实验室。该项目将提供首个同类的、商业上可行的XRDi扫描仪， 病理标本的非破坏性成像，能够告知病理学家存在和 肿瘤在不同组织切片中的位置。拟议的临床扫描仪将能够：1)分析 样品的整个切片体积，而不是切片子集表面的几个微米，这是 目前标准的护理过程使用显微镜，2)基于X射线衍射仪的疾病定量识别 直接从组织获得的信息，以及3)基于定量的、可重现的切片选择 测量，从而消除了与用户相关的主观性。重要的是，它将显著加快速度 病理工作流，在数小时内而不是数天内提供决策，并提高工作效率和 通过减少每个病例分析的幻灯片数量，提高病理实验室的盈利能力。

ABSTRACT Pathology, which plays a vital role in clinical diagnosis, faces numerous challenges that impact its efficacy. For example, resected specimens often require preparing and analysis of as many as 30-40 slide blocks under a microscope until the disease is confirmed; selection of slices for slide preparation uses subjective methods such as palpation, which depend greatly on the skill of the individual performing the assessment and introduces inconsistency in the clinical process; and for each slide block examined, analysis and annotation requires manual observation of every microscopic region of the tissue. As a result, most pathology evaluations often take 1-3 weeks to analyze samples and reach a conclusion regarding potential cancers. An added challenge is that insurance reimbursements are capped per case regardless of the number of slide blocks processed, with any additional costs being absorbed by the hospital. Consequently, hospitals must balance the trade-off between minimizing the number of slices (for economic viability) and not compromising diagnostic care. These challenges affect not only clinical pathology but also research involving pathology specimens and tissue selection for biobanking. There is a critical need to eliminate subjectivity, reduce pathologists’ workload, and increase throughput in histological analysis. We propose to meet this need by developing a new technology called X-ray diffraction imaging (XRDI), which can scan any number of surgically resected, sliced pathology specimens and automatically indicate the likelihood and location of disease in each slice within minutes. In collaboration with Duke University, we previously built a research prototype XRDI system and demonstrated its utility by scanning and evaluating 300 breast cancer slices with high accuracy and resolution. In this direct-to-phase-II SBIR application, we will now construct a new clinical version of the XRDI scanner that is affordable, reliable, and accurate, and can be directly integrated into the clinical pathology workflow. We will build the scanner, test and evaluate its performance, and demonstrate its utility through field-testing in collaboration with clinical pathology laboratories in the US. This project will provide a first-of-its-kind, commercially feasible XRDI scanner for rapid, non-destructive imaging of pathology specimens with the ability to inform pathologists about the presence and location of cancer within the different tissue slices. The proposed clinical scanner will enable: 1) analysis of the whole slice volume of the specimen rather than a few microns at the surface of a subset of the slices, which is the current standard of care process using microscopy, 2) quantitative identification of disease based on XRD information obtained directly from the tissue, and 3) slice selection based on quantitative, reproducible measurements, thereby eliminating user-related subjectivity. Importantly, it would significantly speed up pathology workflow, providing decisions within hours instead of days, and improve the productivity and profitability of pathology labs by reducing the number of slide blocks analyzed per case.