TY - DATA T1 - Supplementary Material for: A New Image-Based Stroke Registry Containing Quantitative Magnetic Resonance Imaging Data PY - 2011/11/18 AU - Kim D.-E. AU - Park K.-J. AU - Schellingerhout D. AU - Jeong S.-W. AU - Ji M.-G. AU - Choi W.J. AU - Tak Y.-O. AU - Kwan G.-H. AU - Koh E.A. AU - Noh S.-M. UR - https://karger.figshare.com/articles/dataset/Supplementary_Material_for_A_New_Image-Based_Stroke_Registry_Containing_Quantitative_Magnetic_Resonance_Imaging_Data/5122858 DO - 10.6084/m9.figshare.5122858.v1 L4 - https://ndownloader.figshare.com/files/8708128 L4 - https://ndownloader.figshare.com/files/8708131 L4 - https://ndownloader.figshare.com/files/8708134 L4 - https://ndownloader.figshare.com/files/8708137 KW - Alphanumeric data KW - Image-based stroke registry KW - Quantitative magnetic resonance imaging data N2 - Background: Conventional stroke registries contain alphanumeric text-based data on the clinical status of stroke patients, but this format captures imaging data in a very limited form. There is a need for a new type of stroke registry to capture both text- and image-based data. Methods and Results: We designed a next-generation stroke registry containing quantitative magnetic resonance imaging (MRI) data, ‘DUIH_SRegI’, developed a supporting software package, ‘Image_QNA’, and performed experiments to assess the feasibility and utility of the system. Image_QNA enabled the mapping of stroke-related lesions on MR onto a standard brain template and the storage of this extracted imaging data in a visual database. Interuser and intrauser variability of the lesion mapping procedure was low. We compared the results from the semi automatic lesion registration using Image_QNA with automatic lesion registration using SPM5 (Statistical Parametric Mapping version 5), a well-regarded standard neuroscience software package, in terms of lesion location, size and shape, and found Image_QNA to be superior. We assessed the clinical usefulness of an image-based registry by studying 47 consecutive patients with first-ever lacunar infarcts in the corona radiata. We used the enriched dataset comprised of both image-based and alphanumeric databases to show that diffusion MR lesions overlapped in a more posterolateral brain location for patients with high NIH Stroke Scale scores (≧4) than for patients with low scores (≤3). In April 2009, we launched the first prospective image-based acute (≤1 week) stroke registry at our institution. The registered data include high signal intensity ischemic lesions on diffusion, T2-weighted, or fluid attenuation inversion recovery MRIs, and low signal intensity hemorrhagic lesions on gradient-echo MRIs. An interim analysis at 6 months showed that the time requirement for the lesion registration (183 consecutive patients, 3,226 MR slices with visible stroke-related lesions) was acceptable at about 1 h of labor per patient by a trained assistant with physician oversight. Conclusions: We have developed a novel image-based stroke registry, with database functions that allow the formulation and testing of intuitive, image-based hypotheses in a manner not easily achievable with conventional alphanumeric stroke registries. ER -