1.5t scanner

MRI studies were performed on 1.5T scanners (GE Medical Systems, Milwaukee, Wis at three field sites; Siemens Medical Solutions, Ehrlangen, Germany at 1 field site) using a bilateral 4-element phased array carotid coil (Machnet, The Netherlands). Details of the carotid MRI protocol have been previously described.^{13 (link),17 (link)} Briefly, a 3D time-of-flight MR angiogram was acquired through both carotid bifurcations. BBRMI imaging was achieved using a 2D cardiac-gated double-inversion recovery fast spin-echo sequence with fat signal suppression before and after an intravenous injection of gadodiamide (Omniscan, GE Amersham, Buckinghamshire, England; 0.1 mmol/kg body weight). Sixteen BBMRI slices were oriented perpendicular to the vessel and centered through the thickest part of the carotid plaque on the side with the thicker wall (acquired resolution, 0.51×0.58×2.00 mm³).^{13 (link)}Seven readers who were blinded to patient characteristics were certified to interpret the MRI images using semi-automated software (VesselMASS, Leiden University Medical Center). Post-contrast images were used to draw contours to delineate the lipid core and outer wall, as contrast helps delineate these features. The semi-automated software divided vessel walls into 12 radial segments, of which the maximum segmental wall thickness was used for analysis.^{13 (link)}

Participants underwent a high-resolution MRI scans of the brain on 1.5 T scanners from General Electric, Siemens, or Philips (Milwaukee, WI, USA; Germany; the Netherlands respectively) across multiple scanners using a standardized MRI protocol for 3D MP-RAGE sequences (Jack, et al., 2008a (link)) and following parameters: TR= 2400 ms, minimum full TE, TI=1000 ms, flip angle= 8°, 24 cm field of view, acquisition matrix of 192 ×192 ×166 and yielding 1.25 ×1.25 ×1.2 mm³.

All data had been obtained for clinical purposes from 1.5T scanners
(General Electric Medical Systems). For the majority of cases, the
diffusion-weighting (b-value) was 1000 s/mm². (Please see
Supplemental
Methods for details.)

T1-weighted MRI data were collected with General Electric 1.5T scanners at Johns Hopkins University (n=30); Mt. Sinai School of Medicine (n=25); University of California at San Diego (n=47); University of Texas Medical Branch (n=29) and the University of Washington (n=8). 3D T1-weighted images were acquired sagittally with spoiled gradient recall (SPGR), TR = 20ms, TE = 6ms, flip angle = 30°, field-of-view = 240mm,124 slices of 1.3mm, in-plane resolution 0.94x0.94mm as previously described.^{4 (link)}3D T1 images were pre-processed as described previously using SPM12 (University College London, UK).^{6 (link)} Briefly, images were bias corrected, segmented into grey matter, white matter and cerebrospinal fluid (CSF), volumes calculated with the sum representing the total intracranial volume (TICV). Segmented images were then registered to a custom template, normalised to Montreal Neurological Institute (MNI) space using the DARTEL algorithm,^{23 (link)} modulated to retain the volumetric characteristics of the original data and smoothed with a 6mm full width half maximum kernel. To take advantage of the complementary data provided by grey and white matter, spatially normalised grey and white matter volumetric maps were spatially concatenated prior to multivariate analysis.

All MRI scans were obtained using 1.5T scanners (General Electric or Picker) producing 5-mm contiguous axial T1, T2, and proton density-weighted images. Infarcts were identified and defined by size and location on T2 and proton density-weighted images. Consistent with recent CSVD research recommendations [10 (link)] and previous ARIC investigations [7 (link), 8 (link)], “smaller infarcts” were defined as those <3mm on right-to-left or anterior-to-posterior size and “larger infarcts” were defined as those ≥3mm but <20mm. Care was taken to distinguish smaller infarcts from perivascular spaces by considering absence of mass effect and hyperintensity to gray matter. Late midlife infarct burden was categorized as presence of smaller infarcts only (n=50), presence of larger infarcts only (n=185), presence of both (n=35), or infarct-free (n=1611). Consideration of count of infarcts was only possible for “larger infarcts” and was tabulated as either “Single Larger Infarct” or “Multiple Larger Infarcts” (≥2). In a sensitivity model to consider multi-infarct burden, we used six infarct exposure groups: [infarct-free (referent; n=1611), smaller only (n=50), single larger (n=129), multiple larger (n=56), smaller + single larger (n=17), and smaller + multiple larger (n=18)]. All infarcts were considered subclinical as no participant in the current study had a prevalent stroke history.

The WB-MRI methodology used in this study has been previously described.[12 (link)] Briefly, using T1 and short-tau inversion recovery (STIR) technique on one of several 1.5T scanners (GE Healthcare, Milwaukee, Wisconsin), the entire body was imaged in the axial plane and then the spine and central base of the skull were imaged in the sagittal plane. Additionally, the axial diffusion-weighted imaging was performed in the axial plane (b-value 0 and 1,000 s/mm²). Overlapping acquisition field of views were confirmed to ensure complete anatomic coverage of the entire body, axial and appendicular skeleton, and adjacent soft tissues.Qualitative image evaluation was performed by a single dedicated onco-radiologist (EL) with approximately twenty years of experience reading WB-MRI. All reported reads are based on the clinical read at the time of imaging; the single false negative finding was re-read retrospectively.