Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care

Abstract

Objective: Epilepsy encompasses an extensive array of clinical and research subdomains, many of which emphasize multi-modal physiological measurements such as electroencephalography and neuroimaging. The integration of structured, unstructured, and signal data into a coherent structure for patient care as well as clinical research requires an effective informatics infrastructure that is underpinned by a formal domain ontology.

Methods: We have developed an epilepsy and seizure ontology (EpSO) using a four-dimensional epilepsy classification system that integrates the latest International League Against Epilepsy terminology recommendations and National Institute of Neurological Disorders and Stroke (NINDS) common data elements. It imports concepts from existing ontologies, including the Neural ElectroMagnetic Ontologies, and uses formal concept analysis to create a taxonomy of epilepsy syndromes based on their seizure semiology and anatomical location.

Results: EpSO is used in a suite of informatics tools for (a) patient data entry, (b) epilepsy focused clinical free text processing, and (c) patient cohort identification as part of the multi-center NINDS-funded study on sudden unexpected death in epilepsy. EpSO is available for download at http://prism.case.edu/prism/index.php/EpilepsyOntology.

Discussion: An epilepsy ontology consortium is being created for community-driven extension, review, and adoption of EpSO. We are in the process of submitting EpSO to the BioPortal repository.

Conclusions: EpSO plays a critical role in informatics tools for epilepsy patient care and multi-center clinical research.

Keywords: Clinical Data Integration; Clinical Free Text Processing; Epilepsy and Seizure Ontology; Patient Data Capture.

Figure 1

Lateralizing signs are associated with body parts using OWL2 existential restriction on the ontology class.

Figure 2

The location of scalp electrodes is defined in terms of specific brain regions to correlate EEG signals to anatomical location.

Figure 3

Multi-channel signal data are annotated using EpSO classes to describe seizure and associated localized events.

Figure 4

A fragment of the concept lattice for epilepsy syndromes (objects) and seizure semiology and anatomy (attributes).

Figure 5

The Multi-Modality Epilepsy Data Capture and Integration System (MEDCIS) query builder with ontology terms in the left frame and visual query widgets in the right frame.

Figure 6

The results of a patient cohort identification query listing the de-identified patient records and links to original records in the left-most column.