White matter hyperintensities (WMHs) are common to advancing age and likely reflect brain vascular injury among older individuals. WMH and to a lesser extent, magnetic resonance (MR) infarcts, affect risk for transition to cognitive impairment.

We describe the properties of a brain gray matter region ("Union Signature") that is derived from four behavior-specific, data-driven signatures in a discovery cohort.

Objective: To examine environmental influences by testing whether time-dependent secular differences occurred in cranial and brain volumes and cortical thickness over birth decades spanning 1930 to 1970.

We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.

We identified and validated a magnetic resonance imaging (MRI) signature for Alzheimer’s disease (AD) and related dementias (ARDR).

In this study, we propose MISPEL (Multi-scanner Image harmonization via Structure Preserving Embedding Learning), a supervised multi-scanner harmonization method that is naturally extendable to more than two scanners.

In this validation study, we produced signature models that replicated model fits to outcome and outperformed other commonly used measures.

Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

To describe the protocol and findings of the instrumental validation of three imaging-based biomarker kits selected by the MarkVCID consortium: free water (FW) and peak width of skeletonized mean diffusivity (PSMD), both derived from diffusion tensor imaging (DTI), and white matter hyperintensity (WMH) volume derived from fluid attenuation inversion recovery and T1-weighted imaging.

We lay out the methods by which we have achieved consistently high quality, high throughput computation of intra-cranial segmentation from whole head magnetic resonance images