Affiliations: [a] Institute for Medical Biometry and Medical Informatics & Comprehensive Cancer Center, Faculty of Medicine and Medical Center, University of Freiburg, Germany | [b] Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria | [c] Department of Computer Science, University of Freiburg, Germany
Corresponding author: Susanne Zabka, Institute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Faculty of Medicine, Stefan-Meier-Str. 26, 79104 Freiburg i. Br., Germany. Tel.: ++49 (0)761 203-7705; Fax: ++49 (0)761 203-6711; E-mail: [email protected].
Note:  Accepted by: Heinrich Herre
Abstract: The TNM classification (Tumor-Node-Metastasis) is the most important coding scheme used to stage tumors based on size and location. Its coding rules may change across different TNM versions, such that the same tumor is represented by different codes in different versions. We present an ontology-based modular architecture for the management of TNM, using the coding rules for pancreas tumors in the considerably different TNM versions 7 and 8 in order to demonstrate how mappings (in the sense of re-classification) between TNM versions can be supported. To enable re-classification of tumor instances between TNM versions, mapping ontologies were created. This work describes two version mapping approaches, one using SWRL rules and the other intermediate classes representing the mapping criteria between the TNM versions. We show that tumor instances with defined characteristics were correctly classified in different TNM versions. In addition, ontological inconsistencies in classification systems based on informal text labels and possible conversion problems due to different categorization criteria in different TNM versions are demonstrated.