Feasibility of an ontology driven tumor-node-metastasis classifier application: A study on colorectal cancer

The objectives of this work are (1) to develop a classifier application for tumor staging based on a formal representation of the Tumor-Node-Metastasis classification system (TNM), and (2) to show the feasibility of this approach on real data. This paper presents a classifier application for colorectal tumors based on the TNM-O ontology. It was developed in the Java using the OWL-API. The TNM-O uses the Foundational Model of Anatomy for representing anatomical entities and BioTopLite2 as a domain-Top-level ontology. The classifier application processes input data via a user interface or tabular data. The classification starts with the creation of RDF Individuals for each pathological information item formally described in the ontology. These Individuals are then classified by the HermiT Description Logics reasoner by A-Box classification. A dataset with 382 entries was provided by the pathology department of a university hospital. It was automatically classified with regard to metastatic regional lymph nodes. Results or expert classification by pathologists and automatic classification were compared. The automatic process helped to detect and explain inconsistencies between expert and automatic classifications. This work, we demonstrate the use of semantic technologies in a TNM classifier application separating underlying medical knowledge represented in OWL from process logics. The presented prototypical TNM classifier application shows the potential to be integrated in larger software systems.