Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM)

Purpose: The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts. Methods: QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages. Results: The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups. Conclusion: The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers

A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field

Objective The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition. Materials and methods Thirty-nine Subjects were scanned at 7 T, using 3D T2*-weighted and T1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm. Results Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast. Conclusions Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings

Quantitative susceptibility mapping: Report from the 2016 reconstruction challenge

PURPOSE: The aim of the 2016 quantitative susceptibility mapping (QSM) reconstruction challenge was to test the ability of various QSM algorithms to recover the underlying susceptibility from phase data faithfully. METHODS: Gradient-echo images of a healthy volunteer acquired at 3T in a single orientation with 1.06 mm isotropic resolution. A reference susceptibility map was provided, which was computed using the susceptibility tensor imaging algorithm on data acquired at 12 head orientations. Susceptibility maps calculated from the single orientation data were compared against the reference susceptibility map. Deviations were quantified using the following metrics: root mean squared error (RMSE), structure similarity index (SSIM), high-frequency error norm (HFEN), and the error in selected white and gray matter regions. RESULTS: Twenty-seven submissions were evaluated. Most of the best scoring approaches estimated the spatial frequency content in the ill-conditioned domain of the dipole kernel using compressed sensing strategies. The top 10 maps in each category had similar error metrics but substantially different visual appearance. CONCLUSION: Because QSM algorithms were optimized to minimize error metrics, the resulting susceptibility maps suffered from over-smoothing and conspicuity loss in fine features such as vessels. As such, the challenge highlighted the need for better numerical image quality criteria

Evaluation of Brain Iron Content Based on Magnetic Resonance Imaging (MRI): Comparison among Phase Value, R2* and Magnitude Signal Intensity

Background and Purpose: Several magnetic resonance imaging (MRI) techniques are being exploited to measure brain iron levels increasingly as iron deposition has been implicated in some neurodegenerative diseases. However, there remains no unified evaluation of these methods as postmortem measurement isn’t commonly available as the reference standard. The purpose of this study was to make a comparison among these methods and try to find a new index of brain iron. Methods: We measured both phase values and R2 * in twenty-four adults, and performed correlation analysis among the two methods and the previously published iron concentrations. We also proposed a new method using magnitude signal intensity and compared it with R2 * and brain iron. Results: We found phase value correlated with R2 * in substantia nigra (r = 20.723, p,0.001) and putamen (r = 20.514, p = 0.010), while no correlations in red nucleus (r = 20.236, p = 0.268) and globus pallidus (r = 20.111, p = 0.605). And the new magnitude method had significant correlations in red nucleus (r = 20.593, p = 0.002), substantia nigra (r = 20.521, p = 0.009), globus pallidus (r = 20.750, p,0.001) and putamen (r = 20.547, p = 0.006) with R2*. A strong inverse correlation was also found between the new magnitude method and previously published iron concentrations in seven brain regions (r = 20.982, P,0.001). Conclusions: Our study indicates that phase value may not be used for assessing the iron content in some brain region

Characterization of multifocal T2*-weighted MRI hypointensities in the basal ganglia of elderly, community-dwelling subjects

AbstractMultifocal T2*-weighted (T2*w) hypointensities in the basal ganglia, which are believed to arise predominantly from mineralized small vessels and perivascular spaces, have been proposed as a biomarker for cerebral small vessel disease. This study provides baseline data on their appearance on conventional structural MRI for improving and automating current manual segmentation methods. Using a published thresholding method, multifocal T2*w hypointensities were manually segmented from whole brain T2*w volumes acquired from 98 community-dwelling subjects in their early 70s. Connected component analysis was used to derive the average T2*w hypointensity count and load per basal ganglia nucleus, as well as the morphology of their connected components, while nonlinear spatial probability mapping yielded their spatial distribution. T1-weighted (T1w), T2-weighted (T2w) and T2*w intensity distributions of basal ganglia T2*w hypointensities and their appearance on T1w and T2w MRI were investigated to gain further insights into the underlying tissue composition. In 75/98 subjects, on average, 3 T2*w hypointensities with a median total volume per intracranial volume of 50.3ppm were located in and around the globus pallidus. Individual hypointensities appeared smooth and spherical with a median volume of 12mm3 and median in-plane area of 4mm2. Spatial probability maps suggested an association between T2*w hypointensities and the point of entry of lenticulostriate arterioles into the brain parenchyma. T1w and T2w and especially the T2*w intensity distributions of these hypointensities, which were negatively skewed, were generally not normally distributed indicating an underlying inhomogeneous tissue structure. Globus pallidus T2*w hypointensities tended to appear hypo- and isointense on T1w and T2w MRI, whereas those from other structures appeared iso- and hypointense. This pattern could be explained by an increased mineralization of the globus pallidus. In conclusion, the characteristic spatial distribution and appearance of multifocal basal ganglia T2*w hypointensities in our elderly cohort on structural MRI appear to support the suggested association with mineralized proximal lenticulostriate arterioles and perivascular spaces

Bioavailable Trace Metals in Neurological Diseases

Medical treatment in Wilson’s disease includes chelators (d-penicillamine and trientine) or zinc salts that have to be maintain all the lifelong. This pharmacological treatment is categorised into two phases; the first being a de-coppering phase and the second a maintenance one. The best therapeutic approach remains controversial, as only a few non-controlled trials have compared these treatments. During the initial phase, progressive increase of chelators’ doses adjusted to exchangeable copper and urinary copper might help to avoid neurological deterioration. Liver transplantation is indicated in acute fulminant liver failure and decompensated cirrhosis; in cases of neurologic deterioration, it must be individually discussed. During the maintenance phase, the most important challenge is to obtain a good adherence to lifelong medical therapy. Neurodegenerative diseases that lead to a mislocalisation of iron can be caused by a culmination of localised overload (pro-oxidant siderosis) and localised deficiency (metabolic distress). A new therapeutic concept with conservative iron chelation rescues iron-overloaded neurons by scavenging labile iron and, by delivering this chelated metal to endogenous apo-transferrin, allows iron redistribution to avoid systemic loss of iron

Lithium suppression of tau induces brain iron accumulation and neurodegeneration

Lithium is a first-line therapy for bipolar affective disorder. However, various adverse effects, including a Parkinson-like hand tremor, often limit its use. The understanding of the neurobiological basis of these side effects is still very limited. Nigral iron elevation is also a feature of Parkinsonian degeneration that may be related to soluble tau reduction. We found that magnetic resonance imaging T2 relaxation time changes in subjects commenced on lithium therapy were consistent with iron elevation. In mice, lithium treatment lowers brain tau levels and increases nigral and cortical iron elevation that is closely associated with neurodegeneration, cognitive loss and parkinsonian features. In neuronal cultures lithium attenuates iron efflux by lowering tau protein that traffics amyloid precursor protein to facilitate iron efflux. Thus, tau- and amyloid protein precursor-knockout mice were protected against lithium-induced iron elevation and neurotoxicity. These findings challenge the appropriateness of lithium as a potential treatment for disorders where brain iron is elevated (for example, Alzheimer’s disease), and may explain lithium-associated motor symptoms in susceptible patients

Brain iron deposits and lifespan cognitive ability

Several studies have reported associations between brain iron deposits and cognitive status, and cardiovascular and neurodegenerative diseases in older individuals, but the mechanisms underlying these associations remain unclear. We explored the associations between regional brain iron deposits and different factors of cognitive ability (fluid intelligence, speed and memory) in a large sample (n = 662) of individuals with a mean age of 73 years. Brain iron deposits in the corpus striatum were extracted automatically. Iron deposits in other parts of the brain (i.e., white matter, thalamus, brainstem and cortex), brain tissue volume and white matter hyperintensities (WMH) were assessed separately and semi-automatically. Overall, 72.8 % of the sample had iron deposits. The total volume of iron deposits had a small but significant negative association with all three cognitive ability factors in later life (mean r = −0.165), but no relation to intelligence in childhood (r = 0.043, p = 0.282). Regression models showed that these iron deposit associations were still present after control for a variety of vascular health factors, and were separable from the association of WMH with cognitive ability. Iron deposits were also associated with cognition across the lifespan, indicating that they are relevant for cognitive ability only at older ages. Iron deposits might be an indicator of small vessel disease that affects the neuronal networks underlying higher cognitive functioning. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11357-015-9837-2) contains supplementary material, which is available to authorized users

Metacognitive ability correlates with hippocampal and prefrontal microstructure

The ability to introspectively evaluate our experiences to form accurate metacognitive beliefs, or insight, is an essential component of decision-making. Previous research suggests individuals vary substantially in their level of insight, and that this variation is related to brain volume and function, particularly in the anterior prefrontal cortex (aPFC). However, the neurobiological mechanisms underlying these effects are unclear, as qualitative, macroscopic measures such as brain volume can be related to a variety of microstructural features. Here we leverage a high-resolution (800 µm isotropic) multi-parameter mapping technique in 48 healthy individuals to delineate quantitative markers of in vivo histological features underlying metacognitive ability. Specifically, we examined how neuroimaging markers of local grey matter myelination and iron content relate to insight as measured by a signal-theoretic model of subjective confidence. Our results revealed a pattern of microstructural correlates of perceptual metacognition in the aPFC, precuneus, hippocampus, and visual cortices. In particular, we extend previous volumetric findings to show that right aPFC myeloarchitecture positively relates to metacognitive insight. In contrast, decreased myelination in the left hippocampus correlated with better metacognitive insight. These results highlight the ability of quantitative neuroimaging to reveal novel brainbehaviour correlates and may motivate future research on their environmental and developmental underpinnings