TY - JOUR
T1 - TNM-O an ontology for the tumor-node-metastasis classification of malignant tumors
T2 - International Conference on Biomedical Ontology, ICBO 2015
AU - Boeker, Martin
AU - Franga, Fabio
AU - Bronsert, Peter
AU - Schulz, Stefan
PY - 2015
Y1 - 2015
N2 - Objectives: To (1) present an ontological framework for the TNM classification system, (2) implement a TNM ontology for colon and rectum tumors based on this framework, and (3) evaluate this ontology with a classifier for 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 system and the specific TNM classification for colorectal tumors were formulated. Additional information was collected from tumor documentation practice in an academic Comprehensive Cancer Center. Based on the ontology, an automatic classifier for pathology data was developed. Results: TNM was represented as an information artefact which consists of single representational units. Corresponding to every representational unit, tumors and tumor aggregates were defined. Tumor aggregates consist of the primary tumor and (if existent) of infiltrated regional lymph nodes and distant metastases. TNM codes depend on the location and certain qualities of the primary tumor (T), the infiltrated regional lymph nodes (N) and the existence of distant metastases (M). Tumor 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 tumors. The presented work is already sufficient to show its representational correctness and completeness as well as its applicability for classification of instance data.
AB - Objectives: To (1) present an ontological framework for the TNM classification system, (2) implement a TNM ontology for colon and rectum tumors based on this framework, and (3) evaluate this ontology with a classifier for 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 system and the specific TNM classification for colorectal tumors were formulated. Additional information was collected from tumor documentation practice in an academic Comprehensive Cancer Center. Based on the ontology, an automatic classifier for pathology data was developed. Results: TNM was represented as an information artefact which consists of single representational units. Corresponding to every representational unit, tumors and tumor aggregates were defined. Tumor aggregates consist of the primary tumor and (if existent) of infiltrated regional lymph nodes and distant metastases. TNM codes depend on the location and certain qualities of the primary tumor (T), the infiltrated regional lymph nodes (N) and the existence of distant metastases (M). Tumor 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 tumors. The presented work is already sufficient to show its representational correctness and completeness as well as its applicability for classification of instance data.
UR - http://www.scopus.com/inward/record.url?scp=84960976718&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84960976718
SN - 1613-0073
VL - 1515
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 27 July 2015 through 30 July 2015
ER -
