Paper
11 March 2010 The development of a disease oriented eFolder for multiple sclerosis decision support
Kevin Ma, Colin Jacobs, James Fernandez, Lilyana Amezcua, Brent Liu
Author Affiliations +
Abstract
Multiple sclerosis (MS) is a demyelinating disease of the central nervous system. The chronic nature of MS necessitates multiple MRI studies to track disease progression. Currently, MRI assessment of multiple sclerosis requires manual lesion measurement and yields an estimate of lesion volume and change that is highly variable and user-dependent. In the setting of a longitudinal study, disease trends and changes become difficult to extrapolate from the lesions. In addition, it is difficult to establish a correlation between these imaged lesions and clinical factors such as treatment course. To address these clinical needs, an MS specific e-Folder for decision support in the evaluation and assessment of MS has been developed. An e-Folder is a disease-centric electronic medical record in contrast to a patient-centric electronic health record. Along with an MS lesion computer aided detection (CAD) package for lesion load, location, and volume, clinical parameters such as patient demographics, disease history, clinical course, and treatment history are incorporated to make the e-Folder comprehensive. With the integration of MRI studies together with related clinical data and informatics tools designed for monitoring multiple sclerosis, it provides a platform to improve the detection of treatment response in patients with MS. The design and deployment of MS e-Folder aims to standardize MS lesion data and disease progression to aid in decision making and MS-related research.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin Ma, Colin Jacobs, James Fernandez, Lilyana Amezcua, and Brent Liu "The development of a disease oriented eFolder for multiple sclerosis decision support", Proc. SPIE 7628, Medical Imaging 2010: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 76280G (11 March 2010); https://doi.org/10.1117/12.844690
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Cited by 1 scholarly publication.
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KEYWORDS
Computer aided design

Databases

Magnetic resonance imaging

Imaging systems

Computer aided diagnosis and therapy

Image segmentation

Human-machine interfaces

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