Quantitative Susceptibility Mapping (QSM) MRI at 7 Tesla and 11-Carbon Pittsburgh-Compound-B PET were used for investigating the relationship between brain iron and Amyloid beta (Aβ) plaque-load in a context of increased risk for Alzheimer's disease (AD), as reflected by the Apolipoprotein E ε4 (APOE-e4) allele and mild cognitive impairment (MCI) in elderly subjects. Carriers of APOE-e4 with normal cognition had higher cortical Aβ-plaque-load than non-carriers. In MCI an association between APOE-e4 and higher Aβ-plaque-load was observable both for cortical and subcortical brain-regions. APOE-e4 and MCI was also associated with higher cortical iron. Moreover, cerebral iron significantly affected functional coupling, and was furthermore associated with increased Aβ-plaque-load (R²-adjusted = 0.80, p < 0.001) and APOE-e4 carrier status (p < 0.001) in MCI. This study confirms earlier reports on an association between increased brain iron-burden and risk for neurocognitive dysfunction due to AD, and indicates that disease-progression is conferred by spatial colocalization of brain iron deposits with Aβ-plaques.

BACKGROUND AND PURPOSE: In patients with premanifest (nonsymptomatic) and advanced Huntington disease, changes in brain iron levels in the basal ganglia have been previously reported, especially in the striatum. Quantitative susceptibility mapping by using MR phase imaging allows in vivo measurements of tissue magnetic susceptibility, which has been shown to correlate well with iron levels in brain gray matter and is believed to be more specific than other imaging-based iron measures. The purpose of this study was to investigate the use of magnetic susceptibility as a biomarker of disease progression. MATERIALS AND METHODS: Fifteen subjects with premanifest Huntington disease and 16 age-matched healthy controls were scanned at 7T. Magnetic susceptibility, effective relaxation, and tissue volume in deep gray matter structures were quantified and compared with genetic and clinical measures. RESULTS: Subjects with premanifest Huntington disease showed significantly higher susceptibility values in the caudate nucleus, putamen, and globus pallidus, indicating increased iron levels in these structures. Significant decreases in magnetic susceptibility were found in the substantia nigra and hippocampus. In addition, significant volume loss (atrophy) and an increase effective relaxation were observed in the caudate nucleus and putamen. Susceptibility values in the caudate nucleus and putamen were found to be inversely correlated with structure volumes and directly correlated with the genetic burdens, represented by cytosine-adenine-guanine repeat age-product-scaled scores. CONCLUSIONS: The significant magnetic susceptibility differences between subjects with premanifest Huntington disease and controls and their correlation with genetic burden scores indicate the potential use of magnetic susceptibility as a biomarker of disease progression in premanifest Huntington disease.

We have conducted computer simulation and experimental studies on magnetoacoustic-tomography with magnetic induction (MAT-MI) for electrical impedance imaging. In MAT-MI, the object to be imaged is placed in a static magnetic field, while pulsed magnetic stimulation is applied in order to induce eddy current in the object. In the static magnetic field, the Lorentz force acts upon the eddy current and causes acoustic vibrations in the object. The propagated acoustic wave is then measured around the object to reconstruct the electrical impedance distribution. In the present simulation study, a two-layer spherical model is used. Parameters of the model such as sample size, conductivity values, strength of the static and pulsed magnetic field, are set to simulate features of biological tissue samples and feasible experimental constraints. In the forward simulation, the electrical potential and current density are solved using Poisson's equation, and the acoustic pressure is calculated as the forward solution. The electrical impedance distribution is then reconstructed from the simulated pressure distribution surrounding the sample. The present computer simulation results suggest that MAT-MI can reconstruct conductivity images of biological tissue with high spatial resolution and high contrast. The feasibility of MAT-MI in providing high spatial resolution images containing impedance-related information has also been demonstrated in a phantom experiment