Dörenberg J, Schmidt C J, Berlage T, Knüchel-Clarke R
RWTH Aachen University, Templergraben 55, 52062, Aachen, Deutschland.
Institut für Pathologie, Uniklinik RWTH Aachen, Pauwelsstraße 30, 52074, Aachen, Deutschland.
Pathologie (Heidelb). 2025 Mar;46(2):108-114. doi: 10.1007/s00292-024-01398-3. Epub 2024 Dec 5.
The structured recording of data from histopathological findings and their interoperability is critical for quality assurance in pathology.
To harmonize the content of the reports, the International Collaboration on Cancer Reporting (ICCR) has defined standardized datasets. These datasets are not yet available in German nationwide. This gap is addressed here using the transurethral bladder resection (TUR-B) dataset as a use case.
We describe the process of establishing the datasets by carrying out translation, mapping on SNOMED CT codes, and using SNOMED CTs hierarchy to fill dropdown menus. Furthermore, we identified rules for checking for self-consistency of reports by using the example of the TUR bladder.
With this article, we have created an example of a German version of the ICCR TUR‑B dataset including mapping to the SNOMED CT terminology. Further activities should include the definition of overarching cancer disease models to further exploit the potential of SNOMED CT.
组织病理学检查结果数据的结构化记录及其互操作性对于病理学质量保证至关重要。
为统一报告内容，国际癌症报告协作组织（ICCR）定义了标准化数据集。这些数据集在德国全国范围内尚未可用。本文以经尿道膀胱切除术（TUR-B）数据集为例解决这一差距。
我们描述了通过进行翻译、映射到SNOMED CT代码以及使用SNOMED CT层次结构填充下拉菜单来建立数据集的过程。此外，我们以TUR膀胱为例确定了检查报告自一致性的规则。
通过本文，我们创建了一个ICCR TUR-B数据集德语版的示例，包括映射到SNOMED CT术语。进一步的活动应包括定义总体癌症疾病模型，以进一步挖掘SNOMED CT的潜力。
