Suppr超能文献

TNM-O:恶性肿瘤分期的本体支持

TNM-O: ontology support for staging of malignant tumours.

作者信息

Boeker Martin, França Fábio, Bronsert Peter, Schulz Stefan

机构信息

Institute for Medical Biometry and Statistics, Medical Center - University of Freiburg, Faculty of Medicine, Stefan-Meier-Str. 26, Freiburg i. Br., 79104, Germany.

Department of Informatics, University of Minho, Campus de Gualtar, Braga, 4710-057, Portugal.

出版信息

J Biomed Semantics. 2016 Nov 14;7(1):64. doi: 10.1186/s13326-016-0106-9.

Abstract

BACKGROUND

Objectives of this work are to (1) present an ontological framework for the TNM classification system, (2) exemplify this framework by an ontology for colon and rectum tumours, and (3) evaluate this ontology by assigning TNM classes to real world pathology data.

METHODS

The TNM ontology uses the Foundational Model of Anatomy for anatomical entities and BioTopLite 2 as a domain top-level ontology. General rules for the TNM classification system and the specific TNM classification for colorectal tumours were axiomatised in description logic. Case-based information was collected from tumour documentation practice in the Comprehensive Cancer Centre of a large university hospital. Based on the ontology, a module was developed that classifies pathology data.

RESULTS

TNM was represented as an information artefact, which consists of single representational units. Corresponding to every representational unit, tumours and tumour aggregates were defined. Tumour aggregates consist of the primary tumour and, if existing, of infiltrated regional lymph nodes and distant metastases. TNM codes depend on the location and certain qualities of the primary tumour (T), the infiltrated regional lymph nodes (N) and the existence of distant metastases (M). Tumour data from clinical and pathological documentation were successfully classified with the ontology.

CONCLUSION

A first version of the TNM Ontology represents the TNM system for the description of the anatomical extent of malignant tumours. The present work demonstrates its representational power and completeness as well as its applicability for classification of instance data.

摘要

背景

本研究的目的是:(1)提出TNM分类系统的本体框架;(2)通过结直肠癌本体对该框架进行示例说明;(3)通过将TNM类别分配给现实世界的病理数据来评估该本体。

方法

TNM本体使用解剖实体的基础解剖模型和BioTopLite 2作为领域顶级本体。TNM分类系统的一般规则和结直肠癌的特定TNM分类在描述逻辑中进行了公理描述。基于一家大型大学医院综合癌症中心的肿瘤文档实践收集了基于病例的信息。基于该本体,开发了一个对病理数据进行分类的模块。

结果

TNM被表示为一种信息制品,它由单个表示单元组成。对应于每个表示单元,定义了肿瘤和肿瘤聚集体。肿瘤聚集体由原发性肿瘤组成,如果存在的话,还包括浸润的区域淋巴结和远处转移。TNM编码取决于原发性肿瘤(T)的位置和某些特征、浸润的区域淋巴结(N)以及远处转移(M)的存在情况。来自临床和病理文档的肿瘤数据已通过该本体成功分类。

结论

TNM本体的第一个版本代表了用于描述恶性肿瘤解剖范围的TNM系统。本研究展示了其表示能力和完整性以及对实例数据分类的适用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/134c/5109740/7998d5ba341c/13326_2016_106_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验