title: Design and development of an ethnically-diverse imaging informatics-based eFolder system for multiple sclerosis patients.
abstract: OBJECTIVE
  MRI has been used to identify multiple sclerosis (MS) lesions in brain and spinal cord visually. Integrating patient information into an electronic patient record system has become key for modern patient care in medicine in recent years. Clinically, it is also necessary to track patients' progress in longitudinal studies, in order to provide comprehensive understanding of disease progression and response to treatment. As the amount of required data increases, there exists a need for an efficient systematic solution to store and analyze MS patient data, disease profiles, and disease tracking for both clinical and research purposes.
  
  
  METHODS
  An imaging informatics based system, called MS eFolder, has been developed as an integrated patient record system for data storage and analysis of MS patients. The eFolder system, with a DICOM-based database, includes a module for lesion contouring by radiologists, a MS lesion quantification tool to quantify MS lesion volume in 3D, brain parenchyma fraction analysis, and provide quantitative analysis and tracking of volume changes in longitudinal studies. Patient data, including MR images, have been collected retrospectively at University of Southern California Medical Center (USC) and Los Angeles County Hospital (LAC). The MS eFolder utilizes web-based components, such as browser-based graphical user interface (GUI) and web-based database. The eFolder database stores patient clinical data (demographics, MS disease history, family history, etc.), MR imaging-related data found in DICOM headers, and lesion quantification results. Lesion quantification results are derived from radiologists' contours on brain MRI studies and quantified into 3-dimensional volumes and locations. Quantified results of white matter lesions are integrated into a structured report based on DICOM-SR protocol and templates. The user interface displays patient clinical information, original MR images, and viewing structured reports of quantified results. The GUI also includes a data mining tool to handle unique search queries for MS. System workflow and dataflow steps has been designed based on the IHE post-processing workflow profile, including workflow process tracking, MS lesion contouring and quantification of MR images at a post-processing workstation, and storage of quantitative results as DICOM-SR in DICOM-based storage system. The web-based GUI is designed to display zero-footprint DICOM web-accessible data objects (WADO) and the SR objects.
  
  
  CONCLUSIONS
  The MS eFolder system has been designed and developed as an integrated data storage and mining solution in both clinical and research environments, while providing unique features, such as quantitative lesion analysis and disease tracking over a longitudinal study. A comprehensive image and clinical data integrated database provided by MS eFolder provides a platform for treatment assessment, outcomes analysis and decision-support. The proposed system serves as a platform for future quantitative analysis derived automatically from CAD algorithms that can also be integrated within the system for individual disease tracking and future MS-related research. Ultimately the eFolder provides a decision-support infrastructure that can eventually be used as add-on value to the overall electronic medical record.
authors.affiliation: IPILab, Dept. of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089-1111, United States. Electronic address: kevincma@usc.edu.
authors.forename: Kevin C
authors.initials: KC
authors.lastname: Ma
authors.affiliation: Dept. of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089-1111, United States.
authors.forename: James R
authors.initials: JR
authors.lastname: Fernandez
authors.affiliation: Dept. of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089-1111, United States.
authors.forename: Lilyana
authors.initials: L
authors.lastname: Amezcua
authors.affiliation: Dept. of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089-1111, United States.
authors.forename: Alex
authors.initials: A
authors.lastname: Lerner
authors.affiliation: Dept. of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089-1111, United States.
authors.forename: Mark S
authors.initials: MS
authors.lastname: Shiroishi
authors.affiliation: IPILab, Dept. of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089-1111, United States.
authors.forename: Brent J
authors.initials: BJ
authors.lastname: Liu
mesh_terms: D005006:Ethnicity; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D009103:Multiple Sclerosis / Q000473:pathology*; D011873:Radiology Information Systems / Q000458:organization & administration*; D014584:User-Computer Interface