A multi-center physiological data repository for SUDEP: Data curation, data conversion and workflow

Abstract

For any rare diseases, patient cohorts from individual medical research centers may not have sufficient statistical power to develop and verify/validate disease biomarkers as results of either small sample size or lack of patient-level predictors of the disease often in the form of recorded biological signals integrated with clinical data. Continuous recording is thus becoming a necessary step in the research to identify these biomarkers. The creation of a biological signals repository on top of a clinical data repository from multiple centers is thus a catalyst for current and future research of rare diseases. In this paper, several issues are considered in order to combine recorded physiological measurements from multiple centers to create a collaborative Big Data repository. Practical challenges including standardization of clinical information as well as physiological data are addressed. A case study of the Big-Data challenges associated with creating a large physiological data repository for the study of SUDEP (Sudden Unexpected Death in Epilepsy) as a part of the CSR (Center for SUDEP Research) study is presented. This includes end-to-end workflow from obtaining the source waveform data to storing standardized data files in the multi-center repository. This workflow has been implemented at Case Western Reserve University in partnership with University Hospitals to standardize data from multiple SUDEP centers that include Nihon Kohden, Micromed, and Nicolet physiological signal formats converted to European Data Format (EDF). A combination of existing third party, proprietary, and in-house-developed software tools used in the workflow are discussed.