title: A new image-based stroke registry containing quantitative magnetic resonance imaging data.
abstract: 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.
  
  
  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, T(2)-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.
authors: Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea. kdongeog@duih.org
authors: Dong-Eog
authors: DE
authors: Kim
authors: Kyoung-Jong
authors: KJ
authors: Park
authors: Dawid
authors: D
authors: Schellingerhout
authors: Sang-Wuk
authors: SW
authors: Jeong
authors: Myung-Goo
authors: MG
authors: Ji
authors: Won Jun
authors: WJ
authors: Choi
authors: Yoon-Oh
authors: YO
authors: Tak
authors: Geon-Hwan
authors: GH
authors: Kwan
authors: Eun Ah
authors: EA
authors: Koh
authors: Sang-Mi
authors: SM
authors: Noh
authors: Hyung Yeol
authors: HY
authors: Jang
authors: Tae-Yun
authors: TY
authors: Kim
authors: Ji-Won
authors: JW
authors: Jeong
authors: Jae Sung
authors: JS
authors: Lee
authors: Heung-Kook
authors: HK
authors: Choi
mesh_terms: D000368:Aged; D002544:Cerebral Infarction / Q000473:pathology; D016208:Databases, Factual; D017352:Echo-Planar Imaging; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D012042:Registries; D015203:Reproducibility of Results; D012984:Software; D020521:Stroke / Q000473:pathology*