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R2* relaxometry of the brain is a quantitative magnetic resonance technique which is influenced by iron and myelin content across different brain regions. Multiple sclerosis (MS) is a common inflammatory, demyelinating disease affecting both white and grey matter regions of the CNS. Using R2*, increased iron deposition has been described in deep gray matter of MS patients. Iron accumulation might promote oxidative stress in the brain, which can lead to cell death and neurodegeneration. However, recent histological work indicates that iron may be reduced within the normal appearing white matter (WM) in MS. In the present study we analyzed the R2* signal across the white matter in 39 patients with MS, 31 asymptomatic age matched siblings of patients and 30 age-matched controls. The measurement of R2* in white matter is affected by the signal's dependency on white matter fibre orientation with respect to the main magnetic field which can be accounted using diffusion tensor imaging. We observed a clear separation of the three study groups in R2*. The values in the MS group were significantly lower compared to the siblings and controls, while the siblings group presented with significantly higher R2* values than both unrelated healthy controls and patients. Furthermore, we found significantly decreased normal-appearing white matter R2* values in patients with more severe disease course. Angle resolved analysis of R2* improves the sensitivity for detecting subtle differences in WM R2* compared to standard histogram based analyses. Our findings suggest that the decreased R2* values in MS are due to diffuse tissue damage and decreased myelin in the normal appearing and diffusely abnormal WM. The increased R2* in unaffected siblings may identify a predisposition to increased iron and the potential for oxidative stress as a risk factor for developing MS.

Quantitative susceptibility mapping (QSM) is a post-processing technique of gradient echo phase data that attempts to map the spatial distribution of local tissue magnetic susceptibilities. To obtain these maps, an ill-posed field-to-source inverse problem must be solved to remove non-local magnetic field perturbations. Current state-of-the-art algorithms which aim to solve the dipole inversion problem are plagued by the trade-off between reconstruction speed and accuracy. A two-step dipole inversion algorithm is proposed to bridge this gap. Our approach first addresses the well-conditioned k-space region, which is reconstructed using a Krylov subspace solver. Then the ill-conditioned k-space region is reconstructed by solving a constrained l1-minimization problem. The proposed pipeline does not incorporate a priori information, but utilizes sparsity constraints in the second step. We compared our method to well-established QSM algorithms with respect to COSMOS in in vivo volunteer datasets. Compared to MEDI and HEIDI the proposed algorithm produces susceptibility maps with a lower root-mean-square error and a higher coefficient of determination, with respect to COSMOS, while being 50 times faster. Our two-step dipole inversion algorithm without a priori information yields improved QSM reconstruction quality at reduced computation times compared to current state-of-the-art methods. •A rapid two-step dipole inversion algorithm is proposed.•50 times faster when compared to MEDI and HEIDI in one healthy volunteer data set.•High-quality susceptibility maps from low resolution clinical data set.

Magnetic resonance imaging (MRI) of focal or diffuse myelin damage or remyelination may provide important insights into disease progression and potential treatment efficacy in multiple sclerosis (MS). We performed post‐mortem MRI and histopathological myelin measurements in seven progressive MS cases to evaluate the ability of three myelin‐sensitive MRI scans to distinguish different stages of MS pathology, particularly chronic demyelinated and remyelinated lesions. At 3 Tesla, we acquired two different myelin water imaging (MWI) scans and magnetisation transfer ratio (MTR) data. Histopathology included histochemical stainings for myelin phospholipids (LFB) and iron as well as immunohistochemistry for myelin proteolipid protein (PLP), CD68 (phagocytosing microglia/macrophages) and BCAS1 (remyelinating oligodendrocytes). Mixed‐effects modelling determined which histopathological metric best predicted MWF and MTR in normal‐appearing and diffusely abnormal white matter, active/inactive, inactive, remyelinated and ischemic lesions. Both MWI measures correlated well with each other and histology across regions, reflecting the different stages of MS pathology. MTR data showed a considerable influence of components other than myelin and a strong dependency on tissue storage duration. Both MRI and histology revealed increased myelin densities in inactive compared with active/inactive lesions. Chronic inactive lesions harboured single scattered myelin fibres indicative of low‐level remyelination. Mixed‐effects modelling showed that smaller differences between white matter areas were linked to PLP densities and only to a small extent confounded by iron. MWI reflects differences in myelin lipids and proteins across various levels of myelin densities encountered in MS, including low‐level remyelination in chronic inactive lesions.

A large proportion of Alzheimer's disease (AD) patients have coexisting subcortical vascular dementia (SVaD), a condition referred to as mixed dementia (MixD). Brain imaging features of MixD presumably include those of cerebrovascular disease and AD pathology, but are difficult to characterize due to their heterogeneity. To perform an exploratory analysis of conventional and non-conventional structural magnetic resonance imaging (MRI) abnormalities in MixD and to compare them to those observed in AD and SVaD. We conducted a cross-sectional, region-of-interest-based analysis of 1) hyperintense white-matter signal abnormalities (WMSA) on T2-FLAIR and hypointense WMSA on T1-weighted MRI; 2) diffusion tensor imaging; 3) quantitative susceptibility mapping; and 4) effective transverse relaxation rate (R2*) in N = 17 participants (AD:5, SVaD:5, MixD:7). General linear model was used to explore group differences in these brain imaging measures. Model findings suggested imaging characteristics specific to our MixD group, including 1) higher burden of WMSAs on T1-weighted MRI (versus both AD and SVaD); 2) frontal lobar preponderance of WMSAs on both T2-FLAIR and T1-weighted MRI; 3) higher fractional anisotropy values within normal-appear white-matter tissues (versus SVaD, but not AD); and 4) lower R2* values within the T2-FLAIR WMSA areas (versus both AD and SVaD). These findings suggest a preliminary picture of the location and type of brain imaging characteristics associated with MixD. Future imaging studies may employ region-specific hypotheses to distinguish MixD more rigorously from AD or SVaD.

Anomalies de l’imagerie du cerveau dans la maladie d’Alzheimer et la démence vasculaire sous-corticale mixte.

Radiation necrosis mostly occurs in and near the radiation field. We used magnetic resonance imaging to study radiation‐induced necrosis of atypical onset, severity, and extent following stereotactic radiosurgery for a symptomatic arteriovenous malformation. Susceptibility‐sensitive imaging, T1‐relaxation, myelin water imaging, and magnetic resonance spectroscopy were acquired three times up to 52 months postradiosurgery. Increasing water content outside the radiation field, contralateral neuronal loss, and gliosis were detected over time. Our findings suggest that radiation‐induced vasculopathic changes spread more diffusely than previously described. An autoimmune response to brain antigens could underlie white matter changes outside the initial radiation field.

Multicomponent T2-mapping using a gradient and spin-echo (GraSE) acquisition has become standard for myelin water imaging at 3T. Higher magnetic field strengths promise SNR benefits but face specific absorption rate limits and shortened T2 times. This study investigates compartmental T2 times in vivo and addresses advantages and challenges of multi-component T2-mapping at 7T. We acquired 3D multi-echo GraSE data in seven healthy adults at 7T, with three subjects scanned also at 3T. Stimulated echoes arising from B+1 inhomogeneities were accounted for by the extended phase graph (EPG) algorithm. We used the computed T2 distributions to determine T2 times that identify different water pools and assessed signal-to-noise and fit-to-noise characteristics of the signal estimation. We compared short T2 fractions and T2 properties of the intermediate water pool at 3T and 7T. Flip angle mapping confirmed that EPG accurately determined the larger inhomogeneity at 7T. Multi-component T2 analysis demonstrated shortened T2 times at 7T compared to 3T. Fit-to-noise and signal-to-noise ratios were improved at 7T but depended on B1 homogeneity. Lowering the shortest T2 to 8 ms and adjusting the T2 threshold that separates different water compartments to 20 ms, yielded short T2 fractions at 7T that conformed to 3T data. Short T2 fractions in myelin-rich white matter regions were lower at 7T than at 3T, and higher in iron-rich structures. Adjusting the T2 compartment boundaries was required due to the shorter T2 relaxation times at 7T. Shorter echo spacing would better sample the fast decaying signal but would increase peripheral nerve stimulation. We used a multi-echo 3D-GraSE sequence to characterize the multi-exponential T2 decay at 7T. We adapted T2 parameters for evaluation of the short T2 fraction. Obtained 7T multicomponent T2-maps were in good agreement with 3T data.

Multi-compartment T2-mapping has gained particular relevance for the study of myelin water in brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T2 data has been widely employed for the computation of the myelin water fraction (MWF) and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T2 and MWF maps. We generated multi-echo spin-echo T2 decay curves following the approach of Carr-Purcell-Meiboom-Gill for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean (gm) T2. MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1. Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+-inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow to better characterize the T2 distribution, including the myelin water, in vivo.