A group-level comparison of volumetric and combined volumetric-surface normalization for whole brain analyses of myelin and iron maps

Magnetic Resonance T1w/T2w Ratio in the Putamen and Cerebellum as a Marker of Cognitive Impairment in MSA: a Longitudinal Study

The exact pathophysiology of cognitive impairment in multiple system atrophy (MSA) is unclear. In our longitudinal study, we aimed to analyze (I) the relationships between cognitive functions and some subcortical structures, such as putamen and cerebellum assessed by voxel-based morphometry (VBM) and T1-weighted/T2-weighted (T1w/T2w) ratio, and (II) the neuroimaging predictors of the progression of cognitive deficits. Twenty-six patients with MSA underwent a comprehensive neuropsychological battery, motor examination, and brain MRI at baseline (T0) and 1-year follow-up (T1). Patients were then divided according to cognitive status into MSA with normal cognition (MSA-NC) and MSA with mild cognitive impairment (MCI). At T1, we divided the sample according to worsening/non worsening of cognitive status compared to baseline evaluation. Logistic regression analysis showed that age (β =  - 9.45, p = .02) and T1w/T2w value in the left putamen (β = 230.64, p = .01) were significant predictors of global cognitive status at T0, explaining 65% of the variance. Logistic regression analysis showed that ∆-values of WM density in the cerebellum/brainstem (β = 2188.70, p = .02) significantly predicted cognitive worsening at T1, explaining 64% of the variance. Our results suggest a role for the putamen and cerebellum in the cognitive changes of MSA, probably due to their connections with the cortex. The putaminal T1w/T2w ratio may deserve further studies as a marker of cognitive impairment in MSA.

Magnetic resonance T1w/T2w ratio and voxel-based morphometry in multiple system atrophy

Diagnosis of multiple system atrophy (MSA) may be improved by using multimodal imaging approaches. We investigated the use of T1-weighted/T2-weighted (T1w/T2w) images ratio combined with voxel-based morphometry to evaluate brain tissue integrity in MSA compared to Parkinson’s disease (PD) and healthy controls (HC). Twenty-six patients with MSA, 43 patients with PD and 56 HC were enrolled. Whole brain voxel-based and local regional analyses were performed to evaluate gray and white matter (GM and WM) tissue integrity and mean regional values were used for patients classification using logistic regression. Increased mean regional values of T1w/T2w in bilateral putamen were detected in MSA-P compared to PD and HC. The combined use of regional GM and T1w/T2w values in the right and left putamen showed the highest accuracy in discriminating MSA-P from PD and good accuracy in discriminating MSA from PD and HC. A good accuracy was also found in discriminating MSA from PD and HC by either combining regional GM and T1w/T2w values in the cerebellum or regional WM and T1w/T2w in the cerebellum and brainstem. The T1w/T2w image ratio alone or combined with validated MRI parameters can be further considered as a potential candidate biomarker for differential diagnosis of MSA.

Structural Alterations in Deep Brain Structures in Type 1 Diabetes

Even though well known in type 2 diabetes, the existence of brain changes in type 1 diabetes (T1D) and both their neuroanatomical and clinical features are less well characterized. To fill the void in the current understanding of this disease, we sought to determine the possible neural correlate in long-duration T1D at several levels, including macrostructural, microstructural cerebral damage, and blood flow alterations. In this cross-sectional study, we compared a cohort of 61 patients with T1D with an average disease duration of 21 years with 54 well-matched control subjects without diabetes in a multimodal MRI protocol providing macrostructural metrics (cortical thickness and structural volumes), microstructural measures (T1-weighted/T2-weighted [T1w/T2w] ratio as a marker of myelin content, inflammation, and edema), and cerebral blood flow. Patients with T1D had higher T1w/T2w ratios in the right parahippocampal gyrus, the executive part of both putamina, both thalami, and the cerebellum. These alterations were reflected in lower putaminal and thalamic volume bilaterally. No cerebral blood flow differences between groups were found in any of these structures, suggesting nonvascular etiologies of these changes. Our findings implicate a marked nonvascular disruption in T1D of several essential neural nodes engaged in both cognitive and motor processing.

Brain iron content in systemic iron overload: A beta-thalassemia quantitative MRI study

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Iron overload is a life-threatening condition in beta-thalassemia.

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Data on brain involvement in systemic iron overload are conflicting.

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MRI quantification of brain tissue iron content is feasible in a voxel-based approach.

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No iron tissue excess is evident in beta-thalassemia but in the choroid plexuses.

Objective

Multisystem iron poisoning is a major concern for long-term beta-thalassemia management. Quantitative MRI-based techniques routinely show iron overload in heart, liver, endocrine glands and kidneys. However, data on the brain are conflicting and monitoring of brain iron content is still matter of debate.

Methods

This 3T-MRI study applied a well validated high-resolution whole-brain quantitative MRI assessment of iron content on 47 transfusion-dependent (mean-age: 36.9 ± 10.3 years, 63% females), 23 non-transfusion dependent (mean-age: 29.2 ± 11.7 years, 56% females) and 57 healthy controls (mean-age: 33.9 ± 10.8 years, 65% females). Clinical data, Wechsler Adult Intelligence Scale scores and treatment regimens were recorded. Beside whole-brain R2* analyses, regional R2*-values were extracted in putamen, globus pallidum, caudate nucleus, thalamus and red nucleus; hippocampal volumes were also determined.

Results

Regional analyses yielded no significant differences between patients and controls, except in those treated with deferiprone that showed lower R2*-values (p<0.05). Whole-brain analyses of R2*-maps revealed strong age-R2* correlations (r²=0.51) in both groups and clusters of significantly increased R2*-values in beta-thalassemia patients in the hippocampal formations and around the Luschka foramina; transfusion treatment was associated with additional R2* increase in dorsal thalami. Hippocampal formation R2*-values did not correlate with hippocampal volume; hippocampal volume did not differ between patients and controls. All regions with increased R2*-values shared a strict anatomical contiguity with choroid plexuses suggesting a blooming effect as the likely cause of R2* increase, in agreement with the available histopathologic literature evidence.

Conclusion

According to our MRI findings and the available histopathologic literature evidence, concerns about neural tissue iron overload in beta-thalassemia appear to be unjustified.

hMRI - A toolbox for quantitative MRI in neuroscience and clinical research

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.