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. 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.

Mapping the Supratentorial Cerebral Arterial Territories Using 1160 Large Artery Infarcts

“…The ACA territory (Figures 2 and 3C) included medial frontal gyrus and superior frontal gyrus (sections 19-24), and anterior and middle parts of the cingulate (sections 15-22) and corpus callosum (sections [16][17][18][19][20]. Moreover, the ACA territory extended posteriorly to precuneus (sections 20-24) and splenium (sections [19][20].…”

NINJ2 SNP may affect the onset age of first-ever ischemic stroke without increasing silent cerebrovascular lesions

“…This may be due to heterogeneity among different ethnic groups or false positive or false negative results, possibly being related to the small effect size of the SNP in terms of predicting the stroke risk in the general population. The present study conducted within Korean stroke patients, while having characterized the subjects in a detailed manner with prospective registration of not only alphanumeric data but also a comprehensive set of quantitative multi-sequence MR imaging data [14], may have selection bias; and, our findings need to be replicated in other population samples. In addition, our short-term cohort study did not investigate the duration of exposure to cardiovascular risk factors, quality of control of the risk factors, and environmental factors that could influence the onset age of first stroke.…”

“…All patients have had their MR lesions prospectively segmented and registered on the ch2better brain template http://www.mccauslandcenter.sc.edu/CRNL/, for which a custom-built software package Image_QNA [14] was used. The software stores the shape and size of each lesion mapped in the standard template coordinate system, available for future analysis.…”

“…The Image_QNA-based registration of MR lesions showed low inter- and intra-user variability. Groups of subjects could be visually grouped together by generating lesion accumulation maps, in which summed images are used to display the visual information of many subjects on a single image set [14,18]. …”

“…This study, conducted in a hospital-based stroke cohort, could be underpowered to detect small effects of the single SNP on the development of the clinical endpoint [10,13]. Thus, in an effort to corroborate the associations, we used quantitative data on stroke-related MR lesions [14] as endophenotypes—subclinical phenotypes that are heritable traits, revealing the actions of genes predisposing an individual to develop conditions known to increase the risk of future disease, often having a larger genetic component than clinical disease endpoints, and manifesting years before clinical diagnostic criteria for the disease are met [13]. Considering that unrecognized or covert brain infarcts and white matter lesions are linked to increased risk for stroke [15], we investigated if the NINJ2 A/A or G/A genotype increased silent cerebrovascular lesions such as leukoaraiosis, asymptomatic lacunes, or microbleeds prior to the manifestation of first strokes.…”