Introduction
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.
Methods
The instrumental validation of imaging‐based biomarker kits included inter‐rater reliability among participating sites, test–retest repeatability, and inter‐scanner reproducibility across three types of magnetic resonance imaging (MRI) scanners using intra‐class correlation coefficients (ICC).
Results
The three biomarkers demonstrated excellent inter‐rater reliability (ICC >0.94,
P
‐values < .001), very high agreement between test and retest sessions (ICC >0.98,
P
‐values < .001), and were extremely consistent across the three scanners (ICC >0.98,
P
‐values < .001).
Discussion
The three biomarker kits demonstrated very high inter‐rater reliability, test–retest repeatability, and inter‐scanner reproducibility, offering robust biomarkers suitable for future multi‐site observational studies and clinical trials in the context of vascular cognitive impairment and dementia (VCID).
Acquiring and processing Diffusion MRI in spinal cord present inherent challenges. Differences in magnetic susceptibility between soft tissues, air and bone make the magnetic field of spinal cord non-uniform and inhomogeneous. In this context various procedures were proposed for correcting this distortion. In this work, we propose novel geometric statistics to measure the alignment of the reconstructed diffusion model with the apparent centerline of the spine. In parallel of the correlation with an anatomical T2-weighted image, we show the utility of these statistics to study and evaluate the impact of distortion correction by comparing 3 distortion correction methods from reversed gradient polarity strategy.
Introduction
Neuroimaging heterogeneity in dementia has been examined using single modalities. We evaluated the associations of magnetic resonance imaging (MRI) atrophy and flortaucipir positron emission tomography (PET) clusters across the Alzheimer's disease (AD) spectrum.
Methods
We included 496 Alzheimer's Disease Neuroimaging Initiative participants with brain MRI, flortaucipir PET scan, and amyloid beta biomarker measures obtained. We applied a novel robust collaborative clustering (RCC) approach on the MRI and flortaucipir PET scans. We derived indices for AD‐like (SPARE‐AD index) and brain age (SPARE‐BA) atrophy.
Results
We identified four tau (I–IV) and three atrophy clusters. Tau clusters were associated with the apolipoprotein E genotype. Atrophy clusters were associated with white matter hyperintensity volumes. Only the hippocampal sparing atrophy cluster showed a specific association with brain aging imaging index. Tau clusters presented stronger clinical associations than atrophy clusters. Tau and atrophy clusters were partially associated.
Conclusions
Each neuroimaging modality captured different aspects of brain aging, genetics, vascular changes, and neurodegeneration leading to individual multimodal phenotyping.
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