Grading glioma tumors using OWL-DL and NCI Thesaurus

Brain tumors' treatment and prognosis depend to a large extent on their grades. Grading tumors follows a set of rules that refers to domain knowledge. Developing an automatic grading system requires explicit and formal representation of the domain. The NCI Thesaurus is the major ontological resource in the cancer domain. However, the description of brain tumors and grades in the NCI Thesaurus does not enable automatic grading. We have developed an ontology based on the NCI Thesaurus for automatic classification of glioma tumors based on a reference grading system. Two sets of tests have been done. The first one has been automatically generated and the second one consists of eleven pathology reports. The resulting ontology contains 243 classes, among which 234 correspond to NCI Thesaurus classes. Because all of the generated tests were correctly classified, we believe our system to be correct. Ten clinical reports are correctly graded and one is graded incompletely.