Supplementary Material for: A New Image-Based Stroke Registry Containing Quantitative Magnetic Resonance Imaging Data

<i>Background:</i> 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. <i>Methods and Results:</i> 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. <i>Conclusions:</i> 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.

背景：传统卒中登记库仅存储卒中患者临床状态的字母数字文本数据，对影像学数据的收录形式极为有限，亟需开发新型卒中登记库以同时覆盖文本与影像学两类数据的采集与存储。
方法与结果：本研究设计了一款可收录定量磁共振成像（Magnetic Resonance Imaging, MRI）数据的新一代卒中登记库"DUIH_SRegI"，开发了配套软件包"Image_QNA"，并通过实验评估了该系统的可行性与实用价值。Image_QNA可将磁共振成像上的卒中相关病灶配准至标准脑模板，并将提取的影像学数据存储于可视化数据库中。病灶配准操作的使用者间与使用者内变异度均较低。本研究以病灶位置、大小与形态为评估指标，对比了使用Image_QNA进行的半自动病灶配准结果，与使用广受认可的标准神经科学软件包"SPM5（Statistical Parametric Mapping 5，统计参数映射5）"完成的全自动病灶配准结果，发现Image_QNA的表现更优。本研究纳入47例连续收治的首次发生放射冠腔隙性脑梗死患者，以此评估影像学登记库的临床应用价值。通过结合影像学与字母数字数据库构建的富集数据集，本研究发现：相较于美国国立卫生研究院卒中量表（National Institutes of Health Stroke Scale, NIHSS）评分≤3分的患者，评分≥4分的患者其弥散磁共振成像病灶所在的脑区位置更偏后外侧。2009年4月，本机构启动了首个前瞻性影像学导向的急性（发病≤1周）卒中登记库。登记数据涵盖弥散加权成像、T₂加权成像及液体衰减反转恢复成像上的高信号缺血性病灶，以及梯度回波磁共振成像上的低信号出血性病灶。登记启动后6个月的中期分析显示：经培训的辅助人员在医师监督下完成病灶配准的耗时约为每例患者1小时，针对183例连续患者（共3226幅可见卒中相关病灶的磁共振切片）而言，该耗时处于可接受范围内。
结论：本研究开发了一款新型影像学导向卒中登记库，其数据库功能可支持直观的影像学相关假设的构建与验证，这是传统字母数字式卒中登记库难以实现的。