Annotated Clinical MRIs and Linked Metadata of Patients with Acute Stroke, Baltimore, Maryland, 2009-2019 (ICPSR 38464)

Version Date: Dec 7, 2022 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Andreia V. Faria, Johns Hopkins University

https://doi.org/10.3886/ICPSR38464.v4

Version V4 ()

  • V5 [2022-12-12]
  • V4 [2022-12-07] unpublished
  • V3 [2022-12-05] unpublished
  • V2 [2022-10-19] unpublished
  • V1 [2022-05-16] unpublished

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Additional information about this collection can be found in Version History.

2022-12-07 Making PI readme available for public download.

2022-12-05 Updating zip packages and README.

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This is a collection of 2,888 clinical MRIs of patients admitted at a National Stroke Center, over ten years, with clinical diagnosis of acute or early subacute stroke. The collection includes diverse MRI modalities and protocols. The infarct core was manually defined in the diffusion weighted images; the images are provided in native subject space and in standard space (MNI), in Neuroimaging Informatics Technology Initiative (NIfTI) format. The data format and organization follows Brain Imaging Data Structure (BIDS) guidelines. The collection includes diverse metadata, comprised of demographic information, basic clinical profile (NIH Stroke Scale/Score (NIHSS), hospitalization duration, blood pressure at admission, BMI, and associated health conditions), and expert description of the acute lesion. This resource provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.

The dataset is divided in folders with 60-70 subjects. Each folder contains the "raw data" (multimodal MRIs, in native space), "DWI-mask" (manually-defined lesion masks, brain masks, and 3D DWI, b0, and recalculated ADC), "DWI-MNI-IntensityNormalized" (DWI and lesion masks in MNI coordinates), and "phenotype" (individual ".tsv" files with metadata of each subject). The "templates" folder contains images averages and lesion frequency maps. The "documentation" contains comprehensive data documentation, the phenotypes of the whole dataset, and the data dictionary.

Faria, Andreia V. Annotated Clinical MRIs and Linked Metadata of Patients with Acute Stroke, Baltimore, Maryland, 2009-2019. Inter-university Consortium for Political and Social Research [distributor], 2022-12-07. https://doi.org/10.3886/ICPSR38464.v4

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Access to these data is restricted. Users interested in obtaining these data must complete a Restricted Data Use Agreement, specify the reason for the request, and obtain IRB approval or notice of exemption for their research.

Individuals from non-member institutions can access these data for a fee. To obtain access, please contact ICPSR for additional details at ICPSR-help@umich.edu.

Inter-university Consortium for Political and Social Research
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2009-01-01 -- 2019-12-31
2009-01-01 -- 2019-12-31
  1. Individuals from non-member institutions can access these data for a fee. To obtain access, please contact ICPSR for additional details at ICPSR-help@umich.edu.

  2. In addition to the ICPSR citation, users are asked to cite the upcoming publication in which these data are described. Please use the following citation:

    Liu CF, Leigh R, Johnson B, Urrutia V, Hsu J, Xu X, Xu Li, Mori S, Hillis A, Faria AV. A large dataset of annotated clinical MRIs and linked metadata of patients with acute stroke. Preprint https://doi.org/10.21203/rs.3.rs-1705779/v1.

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The purpose of the study was to provide high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.

Cross-sectional
Individual

clinical MRIs of patients admitted at a National Stroke Center

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2022-05-16

2022-12-07 Making PI readme available for public download.

2022-12-05 Updating zip packages and README.

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