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MRI Brain

OXVASC T2*-GRE Microbleed Set

Oxford Vascular Study (OXVASC) T2*-weighted GRE cerebral microbleed segmentation set

3 T 2D T2*-weighted GRE brain MRI of 74 Oxford Vascular Study patients after minor stroke or TIA, with manual voxel segmentations of 366 cerebral microbleeds in the 36 patients who had them. Shared on request to the OXVASC PI.

Overview

This entry covers a labelled subset of the Oxford Vascular Study (OXVASC), not the whole OXVASC imaging cohort. OXVASC is a population-based study at the Wolfson Centre for the Prevention of Stroke and Dementia in Oxford that has followed patients with vascular events from eight Oxfordshire general practices since 2002. Sundaresan et al. (2023) used T2*-weighted gradient echo scans of 74 OXVASC patients, with manual cerebral microbleed segmentations, to train and test a deep learning microbleed detector. The rest of the OXVASC imaging data is not part of this entry.

Composition

74 patients who had recently had a minor non-disabling stroke or a transient ischaemic attack; the paper does not split them by diagnosis. 36 are women and 38 are men, aged 39.6 to 91.2 years (mean 69.8, median 67.3). 36 patients have at least one microbleed, 366 microbleeds in total (mean 10.2, median 3 per patient). The other 38 have none and serve as negative cases. The paper describes T2*-weighted GRE images for every patient.

Acquisition

Scans were acquired on a 3 T Siemens Verio: 2D single-echo T2*-weighted GRE with GRAPPA 2, TR 504 ms, TE 15 ms, flip angle 20 degrees, 0.9 x 0.8 mm in-plane resolution, 5 mm slices and a 640 x 640 x 25 matrix. The study was approved by the South Central Oxford A Research Ethics Committee (05/Q1604/70).

Annotations

Microbleeds were segmented manually on the T2*-GRE images for all 36 positive patients, giving voxel masks. The paper does not say who drew them or which rating rules were used. The authors' detection code is public at github.com/v-sundaresan/microbleed-detection, without a license file.

Known limitations

  • Not public. Requests go to the OXVASC principal investigator and are judged case by case; no data use terms are published.
  • One scanner model and one protocol, with thick 5 mm slices.
  • Rater, protocol and inter-rater agreement for the masks are not reported.
  • The paper does not say whether other sequences or clinical data come with the T2*-GRE scans.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 74 subjects.

Sex

  • Female 36 49%
  • Male 38 51%

Age

mean 69.8± 14.6 · range 39.6 to 91.2

No age bins reported.

Contrast combinations

How many subjects have exactly each set of contrasts.

T2starwSubjects with exactly this set
74

Contrast / sequence

subjects, values can overlap

  • T2*-weighted 74 100%

Condition

subjects, values can overlap

  • Cerebral microbleeds 36 49%

Scanner vendor

subjects

  • Siemens Healthineers 74 100%

Field strength

subjects

  • 3 T 74 100%

Country

subjects

  • United Kingdom 74 100%

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
On request

Ask the authors or the data holder. No published process or terms, and access is at their discretion

Access page

No published license or data use terms

The data holder has published no license and no data use terms. Any use, sharing or commercial right has to be agreed with the data holder, and nothing can be assumed to be allowed. Default copyright and data protection law still apply.

The paper's data availability statement says requests for OXVASC data are considered by the PI, Peter Rothwell, in line with data protection laws. The OXVASC web page adds that fully anonymised data "may be shared with other organisations outside the University of Oxford for research to improve healthcare delivery (not NHS data) and subject to appropriate agreements being in place and approval by the Principal Investigator". No agreement text is published.

Original license text Checked 2026-10-08

What you can do

  • Commercial use Not stated
  • Train ML models Not stated
  • Create derived data Not stated
  • Publish results Not stated

What you can share

  • Share the data Not stated
  • Share derived data Not stated
  • Share trained models Not stated

What you must do

  • Cite or credit Not stated
  • Share alike Not stated
  • Sign an agreement Not stated
  • Ethics approval Not stated
  • Manuscript review Not stated
  • Release code Not stated
  • Return results Not stated
  • Delete after use Not stated

Limits

  • No re-identification Not stated
  • Location limits Not stated

Citation

Sundaresan V, Arthofer C, Zamboni G, Murchison AG, Dineen RA, Rothwell PM, Auer DP, Wang C, Miller KL, Tendler BC, Alfaro-Almagro F, Sotiropoulos SN, Sprigg N, Griffanti L, Jenkinson M. Automated detection of cerebral microbleeds on MR images using knowledge distillation framework. Frontiers in Neuroinformatics 17, 1204186 (2023). doi:10.3389/fninf.2023.1204186

All numbers

Every number on this page, as stored in stats.csv, with its source.

MeasureBreakdownValueSource
Subjectstotal
OXVASC participants with a recent minor non-disabling stroke or transient ischaemic attack
74sundaresan2023
Section 3.2
Subjectscontrast=T2starw
2D single-echo T2*-weighted GRE
74sundaresan2023
Section 3.2
Subjectscontrast_set=T2starw
the paper describes only the T2*-GRE images for this set
74sundaresan2023
Section 3.2
Subjectscondition=cerebral_microbleeds
all 36 have manual microbleed segmentations; 366 microbleeds in total, median 3 per subject
36sundaresan2023
Section 3.2
Subjectssex=female
reported as F:M = 36:38, which sums to the 74 subjects
36sundaresan2023
Section 3.2
Subjectssex=male
reported as F:M = 36:38, which sums to the 74 subjects
38sundaresan2023
Section 3.2
Subjectsfield_strength=3
3 T Siemens Verio
74sundaresan2023
Section 3.2
Subjectsvendor=siemens 74sundaresan2023
Section 3.2
Subjectscountry=GB
OXVASC recruits patients registered with general practices in Oxfordshire
74oxvasc-page
Mean agetotal
SD 14.6
69.8sundaresan2023
Section 3.2
Age SDtotal 14.6sundaresan2023
Section 3.2
Median agetotal 67.3sundaresan2023
Section 3.2
Minimum agetotal 39.6sundaresan2023
Section 3.2
Maximum agetotal 91.2sundaresan2023
Section 3.2

Sources

The keys used in the table above.