Quantitative gradient recalled echo (qGRE) MRI enables in vivo measurement of pre-atrophic neurodegeneration in a mouse model of Alzheimer's disease.

Robust methods are needed for preclinical evaluation of novel Alzheimer Disease (AD) therapies to accelerate drug discovery. Quantitative Gradient Recalled Echo (qGRE) MRI has shown promise to provide insight into neurodegeneration in AD prior to atrophy development in humans, highlighting areas of low neuronal density. In this study a novel qGRE method (20 echoes, TE=2-40ms) is shown to non-invasively measure the longitudinal neuronal loss in the hippocampus of a mouse model of AD tauopathy Tg4510. Tg4510 (n=10) and wild type (WT, n=6) mice underwent MRI (7T field strength) at 3-7 months old. 3D qGRE approach was used to generate brain-specific R* maps free of magnetic field inhomogeneity artifacts. Light-sheet microscopy of the brains stained with NeuN and MBP served to visualize neuronal nuclei and myelin content respectively. Significant decrease in NeuN staining between 3mo and 5mo was observed in the hippocampus of Tg4510, validating the mouse AD model. Longitudinal analysis showed clear decreases in R* metric of qGRE signal in the Tg4510 mice hippocampus undergoing neurodegeneration between 3 and 5 months old. Histogram analysis revealed an upward trend in patterns of low R* value (Dark Matter, DM), and broadening of R* distribution. These were quantified as significant increase in both DM Volume Fraction (DMVF) and R* Standard Deviation (SD) in Tg4510 mice (p=0.004/p=0.016 DMVF/SD) but not in WT controls (p>0.25). Further monotonical increase was also observed in both metrics in time. A significant negative correlation was observed between the DMVF and myelin content (p=0.01, r=-0.76), suggesting sensitivity of the technique to the loss of myelinated axons. The presented qGRE technique, validated by histological measurements, can be readily applied as in vivo tool in preclinical models of neurodegeneration for pharmacodynamics and mechanism of action assessment.