Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Warwick Medical School, University of Warwick, Coventry, United Kingdom.
Histopathology Department, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, United Kingdom; Histopathology Department, University Hospitals of Leicester NHS Trust, Leicester, United Kingdom.
Mod Pathol. 2023 Nov;36(11):100297. doi: 10.1016/j.modpat.2023.100297. Epub 2023 Aug 4.
As digital pathology replaces conventional glass slide microscopy as a means of reporting cellular pathology samples, the annotation of digital pathology whole slide images is rapidly becoming part of a pathologist's regular practice. Currently, there is no recognizable organization of these annotations, and as a result, pathologists adopt an arbitrary approach to defining regions of interest, leading to irregularity and inconsistency and limiting the downstream efficient use of this valuable effort. In this study, we propose a Standardized Annotation Reporting Style for digital whole slide images. We formed a list of 167 commonly annotated entities (under 12 specialty subcategories) based on review of Royal College of Pathologists and College of American Pathologists documents, feedback from reporting pathologists in our NHS department, and experience in developing annotation dictionaries for PathLAKE research projects. Each entity was assigned a suitable annotation shape, SNOMED CT (SNOMED International) code, and unique color. Additionally, as an example of how the approach could be expanded to specific tumor types, all lung tumors in the fifth World Health Organization of thoracic tumors 2021 were included. The proposed standardization of annotations increases their utility, making them identifiable at low power and searchable across and between cases. This would aid pathologists reporting and reviewing cases and enable annotations to be used for research. This structured approach could serve as the basis for an industry standard and be easily adopted to ensure maximum functionality and efficiency in the use of annotations made during routine clinical examination of digital slides.
随着数字病理学取代传统的玻璃载玻片显微镜成为报告细胞病理学样本的手段,数字病理学全切片图像的注释正迅速成为病理学家常规实践的一部分。目前,这些注释没有可识别的组织,因此,病理学家采用任意的方法来定义感兴趣的区域,导致不规则和不一致,并限制了对这种有价值的工作的下游高效利用。在这项研究中,我们提出了一种数字全切片图像的标准化注释报告风格。我们根据皇家病理学院和美国病理学院文件的审查、我们 NHS 部门报告病理学家的反馈以及在开发 PathLAKE 研究项目注释字典方面的经验,列出了 167 种常见的注释实体(分为 12 个专业子类别)。为每个实体分配了合适的注释形状、SNOMED CT(国际卫生组织标准)代码和唯一的颜色。此外,作为如何将这种方法扩展到特定肿瘤类型的一个例子,纳入了 2021 年第五版世界卫生组织胸部肿瘤分类中的所有肺部肿瘤。这种注释的标准化增加了它们的实用性,使得它们在低倍放大时可以识别,并可以在病例之间和病例内部进行搜索。这将有助于病理学家报告和审查病例,并使注释能够用于研究。这种结构化的方法可以作为行业标准的基础,并且易于采用,以确保在常规数字切片临床检查过程中注释的最大功能和效率。