32 channel rf receive head coil

At both sites, structural MRI scans were acquired on a 3T Siemens Skyra scanner with a standard Siemens 32‐channel RF receive head coil. 3D T1‐weighted MRI scans were obtained using a 3D MPRAGE acquisition sequence with the following parameters: inversion time / repetition time = 880/2000 ms, voxel size = 1 mm isotropic, field of view = 208 mm × 256 mm × 256 mm, in‐plane acceleration factor = 2. Further details on the acquisition protocol are available on the UK Biobank website (http://biobank.ctsu.ox.ac.uk/crystal/refer.cgi?id=1977) and in Miller et al. (2016).

MRI data were acquired during the third (2014+) and fourth assessment (2019+) visits at three imaging centers, equipped with identical scanners (Siemens Skyra 3T running VD13A SP4 with a Siemens 32-channel RF receive head coil, Munich, Germany). The average interval between the assessments was 3 years. Structural magnetic resonance (MR) imaging was utilized to estimate the total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), hippocampus volume (HV) and white matter high-intensity volume (WMHV). The MR imaging protocols have been detailed elsewhere [17 (link)]. All the information on the structural image segmentation and data normalization is available elsewhere [22 (link)]. Publicly available image processing tools, primarily from the FMRIB Software Library, were employed for data processing, utilizing the output of the standard biobank processing pipeline. All data were normalized for head size. Additionally, a new variable, representing the rate of change in brain structure markers, was calculated to depict the longitudinal changes in the brain structure of the participants. A smaller value of the rate of change between the two measurements indicates a faster decrease in brain volume.
The rate of longitudinal change in brain structural markers = [brain image data (2019+) − brain image data (2014+)]/brain image data (2014+).

Details of the image acquisition are available online [34 ]. Magnetic resonance imaging (MRI) was performed using a Siemens Skyra 3T running VD13A SP4 (Siemens Healthcare, Erlangen, Germany) with a Siemens 32-channel RF receive head coil. Diffusion MRI images were obtained using a Stejskal-Tanner pulse sequence with two b-values (b = 1000 and 2000 s/mm²), and a 2mm spatial resolution (3× multislice acquisition, 100 distinct diffusion-encoding directions, and a field-of-view of 104×104×72). T1-weighted structural brain images were obtained using a three-dimensional MPRAGE sequence with a slice thickness of 1mm and a field-of-view of 208×256×256.

Table 1 reports the details of the brain MRI sequences included in the multiorgan COVID-19 protocol, in comparison with the UKB protocol. Below we describe the rationale for the inclusion of these MRI sequences and, where applicable, deviations from the UKB protocol.
The scanner used in UKB is a standard Siemens Skyra 3T running VD13A, with a standard Siemens 32-channel RF receive head coil. The multiorgan COVID-19 protocol was setup on a Siemens Prisma 3T running VE11C, with a Siemens 20-channel head coil.

Brain magnetic resonance imaging (MRI) data were collected for a subsample of UK Biobank participants at four study sites (Stockport (Cheadle), Reading, Newcastle, and Bristol), and raw imaging data were further processed by the UK Biobank to provide image-derived phenotypes for researchers’ use [23 (link)]. Details on the imaging procedures, processing pipeline and derivation of imaging-derived phenotypes have been discussed in prior studies [23 (link),24 (link)]. Briefly, brain imaging was carried out using a Siemens Skyra 3T scanner (running on VD13A SP4 software) with a standard Siemens 32-channel RF receive head coil and with the scan covering from the top of the cranium to the neck/mouth region [23 (link)]. T1-weighted and T2-FLAIR structural imaging were acquired using straight sagittal orientation and were centrally preprocessed to derive brain volumetric measures including total brain volume, grey matter volume, white matter volume, hippocampal volume, and volume of white matter hyperintensities, which we used in this study. The brain volumes were calculated using FreeSurfer software, and we normalized for participant head size using a T1-based head sizing scaling factor (scaled brain volume = brain volume × head size scaling factor) [23 (link)], and log-transformed the volume of white matter hyperintensities for approximating normal distribution.

The UK Biobank is an effort led to collect diverse phenotypic data to promote population-level assessments of lifestyle, environment, and genetics on biology and health presentation. A subset of subjects enrolled in the study participated in brain imaging, from which the first imaging session’s data were retrieved (https://www.ukbiobank.ac.uk)^{37 (link),38 (link)}.
Scanner acquisition of brain structural MRI is detailed elsewhere (https://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/brain_mri.pdf). In brief, all three scanning sites used standard Siemens Skyra 3T scanners with a Siemens 32-channel RF receive head coil. T1 and T2-FLAIR acquisitions were both downloaded to support gray and white matter tissue segmentation. T1 acquisition involved a five-minute 3D MPRAGE session at 1×1×1 mm resolution, in-plane acceleration iPAT=2, and prescan-normalization. T2-FLAIR acquisition involved a six-minute 3D SPACE session at 1.05×1×1 mm resolution, in-plane acceleration iPAT=2, partial Fourier = 7/8, fat saturation, elliptical k-space scanning, and pre-scan normalization^{78 (link)}.