St George's COPD and CAD brain cohort
Factors associated with brain damage in smoking-related diseases: chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD)
Brain MRI (T1, FLAIR, diffusion tensor, arterial spin labelling) and retinal photographs of smokers with chronic obstructive pulmonary disease or coronary artery disease, collected to find vascular, respiratory and inflammatory causes of brain damage. Only derived measures are open.
Overview
This cohort comes from St George's, University of London, where patients with chronic obstructive pulmonary disease (COPD) and coronary artery disease (CAD) had multi-modal brain MRI, retinal photography, lung function tests, vascular measurements and blood tests at one study visit. The aim was to work out whether brain changes in these smoking-related diseases track respiratory, vascular or inflammatory factors. Spilling et al. (PLoS ONE, 2021) report the main analysis. Two figshare records share spreadsheets of derived values for the same 100 patients under CC BY 4.0; the images themselves are not released.
Composition
Patients were recruited from respiratory and cardiology outpatient clinics of St George's Hospital NHS Foundation Trust between December 2015 and October 2017 through two complementary studies (NoVasC2 and NoVasC3). Inclusion required age over 40 and at least 10 pack-years of smoking. Of 103 enrolled, 100 had MRI: 53 with COPD only, 24 with CAD only and 23 with both. The cohort is 69% male with a mean age of 68 years (SD 8).
Acquisition
All brain MRI was done on a 3 T Philips Achieva dual TX: sagittal 3D T1-weighted fast field echo (1 x 1 x 1.25 mm), axial FLAIR (1 x 1 x 3 mm), diffusion tensor imaging with 32 directions at b = 1000 s/mm2 acquired twice (2 mm isotropic), and pseudo-continuous arterial spin labelling with a proton density reference image. Retinal fundus photographs were taken with a Topcon 50IX camera after pupil dilation; images of 16 patients could not be graded.
Annotations
No image annotations are shared. The spreadsheets hold per-patient grey matter, white matter, CSF and ventricle volumes, white matter hyperintensity volume, fractional anisotropy and mean diffusivity histogram measures, grey matter blood flow, retinal vessel calibre, tortuosity, branching angle and fractal dimension, plus clinical, blood and (in the 2022 record) Montreal Cognitive Assessment scores.
Known limitations
- MR images and retinal photographs are not shared, and no request route is published.
- Age and sex were removed from the open spreadsheets.
- No control group without COPD or CAD.
- Per-sequence counts here come from non-missing derived values, so a missing value may reflect failed processing rather than a missing scan.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 100 subjects.
Sex
- Female 31 31%
- Male 69 69%
Table 1 in Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465)
Contrast / sequence
Groups can overlap
- T1-weighted 100 100%
- FLAIR 99 99%
- Diffusion-weighted 99 99%
- Arterial spin labeling 94 94%
Grey matter volume column, White matter hyperintensity volume column, Median Fractional Anisotropy column, Median Cerebral Blood Flow column in COPD_&_CAD_data.xlsx, sheet 1, from figshare record 14510190 (CC BY 4.0)
Scanner vendor
- Philips 100 100%
MRI acquisition in Spilling et al. 2021, S1 Appendix (supplementary methods)
Country
- United Kingdom 100 100%
Methods, Participants in Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465)
Age
mean 68 ± 8
No age bins reported.
Table 1 in Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465)
Modality
- Fundus photography 84 84%
Results, Principal component analysis in Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465)
Condition
Groups can overlap
- COPD 76 76%
- Coronary artery disease 47 47%
Patient Group column in COPD_&_CAD_data.xlsx, sheet 1, from figshare record 14510190 (CC BY 4.0); Methods, Participants in Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465)
Field strength
- 3 T 100 100%
MRI acquisition in Spilling et al. 2021, S1 Appendix (supplementary methods)
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
The data are not available outside the institution or study that holds them
Two figshare records of St George's research data repository hold spreadsheets of derived values for the same 100 patients under CC BY 4.0: 10.24376/rd.sgul.14510190 (2021, 81 variables including brain tissue, white matter hyperintensity, diffusion and blood flow measures and retinal vessel measures) and 10.24376/rd.sgul.20067605 (2022, 15 variables including white matter lesion volume, diffusion measures and MoCA). The readmes state that age, sex and brain scans are not provided. No route to the images is published.
Different parts of the data carry different licenses. The summary on the right shows the most restrictive answer per rule.
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.
Neither figshare record nor the paper offers the images or states terms for them.
What you can do
- Commercial use Not stated
- 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
Creative Commons Attribution 4.0 International
Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- Yes
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
Spilling CA, Dhillon M-PK, Burrage DR, Ruickbie S, Baker EH, Barrick TR, Jones PW. Factors affecting brain structure in smoking-related diseases: Chronic Obstructive Pulmonary Disease (COPD) and coronary artery disease. PLoS ONE 16(11), e0259375 (2021). doi:10.1371/journal.pone.0259375
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.
- Spilling et al. 2021, PLoS ONE 16(11), e0259375 (PMC8570465) paper
- Spilling et al. 2021, S1 Appendix (supplementary methods) paper
- figshare record 10.24376/rd.sgul.14510190, data supporting the 2021 paper website
- figshare record 10.24376/rd.sgul.20067605, COPD_&_CAD_data website
- COPD_&_CAD_data.xlsx, sheet 1, from figshare record 14510190 (CC BY 4.0) computed