Magnetic Susceptibility Mapping Research Articles

Simultaneous Arterial and Venous Imaging Using 3D Quantitative Parameter Mapping.

To increase the number of images that can be acquired in MR examinations using quantitative parameters, we developed a method for obtaining arterial and venous images with mapping of proton density (PD), RF inhomogeneity (B1), longitudinal relaxation time (T1), apparent transverse relaxation time (T2*), and magnetic susceptibility through calculation, all with the same spatial resolution. The proposed method uses partially RF-spoiled gradient echo sequences to obtain 3D images of a subject with multiple scan parameters. The PD, B1, T1, T2*, and magnetic susceptibility maps are estimated using the quantification method we previously developed. Arterial images are obtained by adding images using optimized weights to emphasize the arteries. A morphology filter is used to obtain venous images from the magnetic susceptibility maps. For evaluation, images obtained from four out of five healthy volunteers were used to optimize the weights used in the arterial-image calculation, and the optimized weights were applied to the images from the fifth volunteer to obtain an arterial image. Arterial images of the five volunteers were calculated using the leave-one-out method, and the contrast between the arterial and background regions defined using the reference time-of-flight (TOF) method was evaluated using the area under the receiver operation characteristic curve (AUC). The contrast between venous and background regions defined by a reference quantitative susceptibility mapping (QSM) method was also evaluated for the venous image. The AUC to discriminate blood vessels and background using the proposed method was 0.905 for the arterial image and 0.920 for the venous image. The results indicate that the arterial images and venous images have high signal intensity at the same region as determined from the reference TOF and QSM methods, demonstrating the possibility of acquiring vasculature images with quantitative parameter mapping through calculation in an integrated manner.

Magnetic Characterization of Fine Sediment in the Solo Basin Indonesia

The magnetic characteristics of fine sediment samples from the Solo Basin are reported in this paper. Magnetic fine sediment was identified by magnetic susceptibility mapping based on sampling of 182 points. Then, a depth analysis (on 7 selected sampling points) was performed using X-ray fluorescence spectrometry, which showed an iron oxide content of up to 55.42%, while X-ray diffractometry confirmed magnetite minerals with crystallite size ≤100 nm. Further, the vibrating sample magnetometry results verified the magnetic characteristics under a single-domain configuration. The characteristic magnetic susceptibility map showed that there is a lithogenic effect on sediment in the Solo Basin. In addition, anthropogenic activities seem to play a pivotal role in distributing magnetic materials.

Moderating role of physical activity on hippocampal iron deposition and memory outcomes in typically aging older adults

Physical activity (PA) is linked to better cognitive and brain health, though its mechanisms are unknown. While brain iron is essential for normal function, levels increase with age and, when excessive, can cause detrimental neural effects. We examined how objectively measured PA relates to cerebral iron deposition and memory functioning in normal older adults. Sixty-eight cognitively unimpaired older adults from the UCSF Memory and Aging Center completed neuropsychological testing and brain magnetic resonance imaging, followed by 30-day Fitbit monitoring. Magnetic resonance imaging quantitative susceptibility mapping (QSM) quantified iron deposition. PA was operationalized as average daily steps. Linear regression models examined memory as a function of hippocampal QSM, PA, and their interaction. Higher bilateral hippocampal iron deposition correlated with worse memory but was not strongly related to PA. Covarying for demographics, PA moderated the relationship between bilateral hippocampal iron deposition and memory such that the negative effect of hippocampal QSM on memory performances was no longer significant above 9120 daily steps. PA may mitigate adverse iron-related pathways for memory health.

Brain intrinsic magnetic susceptibility mapping depicts whole-brain functional connectivity balance of normal aging in lifespan.

We hypothesized that brain normal aging maintains a balanced whole-brain functional connectivity (FC) in lifetime: some connections decline while other connections increase or retain, in a summation balance as a result of the cancellation of positive and negative connections. We validated this hypothesis through the use of the brain intrinsic magnetic susceptibility source (denoted by χ) as reconstructed from fMRI phase data. In implementation, we first acquired brain fMRI magnitude (m) and phase (p) data from a cohort of 245 healthy subjects in an age span of 20-60years, then sought MRI-free brain χ source data by computationally solving an inverse mapping problem, thereby obtained triple datasets {χ, m, p} as brain images in different measurements. We performed GIG-ICA for brain function decomposition and constructed the FC matrices (χFC, mFC, pFC} (in size of 50 × 50 for a selection of 50 ICA nodes), followed by a comparative analysis on brain FC agings using {χ, m, p} data. In the results, we found that: (i) χFC aging upholds a FC balance in life span, in an intermediator between mFC and pFC agings by: mean(pFC) = -0.011 < mean(χFC) = 0.015 < mean(mFC) = 0.036; and (ii) the χFC aging exhibits a slight decline with a slightly downward fitting line in intermediation between the two slightly upward fitting lines for the mFC and pFC agings. On the rationale of the χ-depicted MRI-free brain functional state, the brain χFC aging is closer to the brain FC aging truth than the MRI-borne mFC and pFC agings.

Multi‐echo dipole inversion for magnetic susceptibility mapping

Magnetic Resonance in MedicineVolume 89, Issue 6 p. 1-1 COVER IMAGEFree Access Multi-echo dipole inversion for magnetic susceptibility mapping First published: 27 March 2023 https://doi.org/10.1002/mrm.29651AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume89, Issue6June 2023Pages 1-1 RelatedInformation

Multi-echo dipole inversion for magnetic susceptibility mapping.

Reconstructing tissue magnetic susceptibility (QSM) from MRI phase data involves solving multiple consecutive ill-posed inverse problems such as phase unwrapping, background field removal, and field-to-source inversion. Multi-echo acquisitions present an additional challenge, as the magnetization field is typically computed from the multiple phase data prior to reconstructing the susceptibility map. Processing the multiple phase data introduces errors during the field estimation, violating assumptions of the subsequent inverse problems, manifesting as streaking artifacts in the susceptibility map. To address this challenge, we propose a multi-echo field-to-source forward model that forgoes the field estimation step. Moreover, we propose a fully general underestimation correction step to recover susceptibility sources that were regularized away during the field-to-source inversion. The multi-echo forward model and correction step were validated on the QSM Challenge 2.0 datasets and compared to the standard single field-to-source model in in vivo human brains using different types of deconvolution algorithms. On the QSM Challenge 2.0 datasets the multi-echo forward model and correction step attain state-of-the-art results on all metrics by a wide margin. Experiments in in vivo brains show that the multi-echo model is in agreement with the single field-to-source model and that the proposed forward model and correction step can be used with any available dipole inversion method. A multi-echo field-to-source forward model forgoes the need to fit multi-echo phase data and achieves state-of-the-art results on the QSM Challenge 2.0 data. Underestimated low-frequency susceptibility distributions can be partially recovered using a correction step.

Evaluation of iron deposition in the motor CSTC loop of a Chinese family with paroxysmal kinesigenic dyskinesia using quantitative susceptibility mapping.

Previous studies have revealed structural, functional, and metabolic changes in brain regions inside the cortico-striatal-thalamo-cortical (CSTC) loop in patients with paroxysmal kinesigenic dyskinesia (PKD), whereas no quantitative susceptibility mapping (QSM)-related studies have explored brain iron deposition in these areas. A total of eight familial PKD patients and 10 of their healthy family members (normal controls) were recruited and underwent QSM on a 3T magnetic resonance imaging system. Magnetic susceptibility maps were reconstructed using a multi-scale dipole inversion algorithm. Thereafter, we specifically analyzed changes in local mean susceptibility values in cortical regions and subcortical nuclei inside the motor CSTC loop. Compared with normal controls, PKD patients had altered brain iron levels. In the cortical gray matter area involved with the motor CSTC loop, susceptibility values were generally elevated, especially in the bilateral M1 and PMv regions. In the subcortical nuclei regions involved with the motor CSTC loop, susceptibility values were generally lower, especially in the bilateral substantia nigra regions. Our results provide new evidence for the neuropathogenesis of PKD and suggest that an imbalance in brain iron levels may play a role in PKD.

Incomplete spectrum QSM using support information.

Reconstructing a bounded object from incomplete k-space data is a well posed problem, and it was recently shown that this incomplete spectrum approach can be used to reconstruct undersampled MRI images with similar quality to compressed sensing approaches. Here, we apply this incomplete spectrum approach to the field-to-source inverse problem encountered in quantitative magnetic susceptibility mapping (QSM). The field-to-source problem is an ill-posed problem because of conical regions in frequency space where the dipole kernel is zero or very small, which leads to the kernel's inverse being ill-defined. These "ill-posed" regions typically lead to streaking artifacts in QSM reconstructions. In contrast to compressed sensing, our approach relies on knowledge of the image-space support, more commonly referred to as the mask, of our object as well as the region in k-space with ill-defined values. In the QSM case, this mask is usually available, as it is required for most QSM background field removal and reconstruction methods. We tuned the incomplete spectrum method (mask and band-limit) for QSM on a simulated dataset from the most recent QSM challenge and validated the QSM reconstruction results on brain images acquired in five healthy volunteers, comparing incomplete spectrum QSM to current state-of-the art-methods: FANSI, nonlinear dipole inversion, and conventional thresholded k-space division. Without additional regularization, incomplete spectrum QSM performs slightly better than direct QSM reconstruction methods such as thresholded k-space division (PSNR of 39.9 vs. 39.4 of TKD on a simulated dataset) and provides susceptibility values in key iron-rich regions similar or slightly lower than state-of-the-art algorithms, but did not improve the PSNR in comparison to FANSI or nonlinear dipole inversion. With added (ℓ1-wavelet based) regularization the new approach produces results similar to compressed sensing based reconstructions (at sufficiently high levels of regularization). Incomplete spectrum QSM provides a new approach to handle the "ill-posed" regions in the frequency-space data input to QSM.

Investigating the effect of oblique image acquisition on the accuracy of QSM and a robust tilt correction method.

Quantitative susceptibility mapping (QSM) is used increasingly for clinical research where oblique image acquisition is commonplace, but its effects on QSM accuracy are not well understood. The QSM processing pipeline involves defining the unit magnetic dipole kernel, which requires knowledge of the direction of the main magnetic field with respect to the acquired image volume axes. The direction of is dependent on the axis and angle of rotation in oblique acquisition. Using both a numerical brain phantom and in vivo acquisitions in 5 healthy volunteers, we analyzed the effects of oblique acquisition on magnetic susceptibility maps. We compared three tilt-correction schemes at each step in the QSM pipeline: phase unwrapping, background field removal and susceptibility calculation, using the RMS error and QSM-tuned structural similarity index. Rotation of wrapped phase images gave severe artifacts. Background field removal with projection onto dipole fields gave the most accurate susceptibilities when the field map was first rotated into alignment with . Laplacian boundary value and variable-kernel sophisticated harmonic artifact reduction for phase data background field removal methods gave accurate results without tilt correction. For susceptibility calculation, thresholded k-space division, iterative Tikhonov regularization, and weighted linear total variation regularization, all performed most accurately when local field maps were rotated into alignment with before susceptibility calculation. For accurate QSM, oblique acquisition must be taken into account. Rotation of images into alignment with should be carried out after phase unwrapping and before background-field removal. We provide open-source tilt-correction code to incorporate easily into existing pipelines: https://github.com/o-snow/QSM_TiltCorrection.git.

An exceptional sedimentary record of initial rifting on the East African Plateau in the Miocene: Lessons from depositional cyclicity and palaeoenvironmental proxies

AbstractKnowledge about the initial tectonic and depositional dynamics, as well as the influence of early rifting on climate and environmental evolution remains speculative to a large extent, because sediments are usually deeply buried. Within the East African Rift System, inversion tectonics uplifted a few of these successions to the surface hence presenting rare windows into the pre‐rift depositional history. One such example, an exceptional 700 m long and up to 60 m high fresh road cut provided the opportunity to study in detail initial rift successions of the southern Albertine Rift (Western Uganda). This focusses on the basal and poorly known Middle to Late Miocene in order to unravel the climatic, environmental, hydrological and tectonic evolution of the initial Albertine Rift. A large and robust multi‐proxy dataset was gathered comprising 169 m of stratigraphic thickness, which spans from 14.5 to 4.9 Ma according to a revised lithostratigraphic model. Fieldwork comprised logging of the sedimentary record, spectral gamma ray, magnetic susceptibility and 2D wall mapping with photomosaics. Additionally, the sections were sampled for bulk mineral and clay mineral analysis. The succession exposes a suite of lithofacies and architectural elements detailing the evolution of a fluvio‐lacustrine system. Five depositional environments were identified which show an overall back‐stepping trend from an alluvial plain to a delta plain and finally palustrine/shallow lacustrine conditions. Mesoscale base‐level cycles, preservation potential of architectural elements, and stacking pattern exhibit limited accommodation space. However, it increases over time. This overall trend indicates increasing tectonic subsidence, which can be explained by flexural downwarp within the pre‐rift phase and in the upper part grading into fault‐controlled crustal extension of the syn‐rift phase, which more and more disrupted a large‐scale river system. From the Middle Miocene up to the early Pliocene, this study revealed that palaeoclimate trends become marked by increasing and more fluctuating Th concentrations, loss of feldspar, intercalated lenses of hydroxosulphate minerals, and a shift from smectite‐dominated to kaolinite‐dominated clays. These signals are all interpreted as detrital except for the hydroxosulphates, and they mirror the increasing intensity of chemical weathering and stripping of soils in the catchment. A trend towards increasing humidity is supported by an increase in lacustrine sediment facies and a lake‐level rise. Nevertheless, intercalation of hydroxosulphate, ferricretes and pedogenised horizons prove ongoing seasonality and dry intervals. Finally, based on a revised stratigraphic model a sequence stratigraphic correlation of the outcrop's depositional cycles with basin‐scale cycles is presented. According to these cycles, transition from the pre‐rift to the syn‐rift stage is marked by an unconformity and a tectonic pulse in the latest Miocene. However, the response of fluvial supply, the depositional system as well as climate conditions are less punctuated and characterised by gradual trends and temporal delays. The long pre‐rift phase (ca 10 Myr) and the gradual transition to the syn‐rift phase is in accordance with the active rifting model, which is based on thermal thinning of the lithosphere by asthenospheric upwelling.

Quantitative susceptibility mapping (QSM) and R2* of silent cerebral infarcts in sickle cell anemia.

Silent cerebral infarction (SCI) is the most commonly reported radiological abnormality in patients with sickle cell anemia (SCA) and is associated with future clinical stroke risk. To date, there have been few histological and quantitative MRI studies of SCI and multiple radiological definitions exist. As a result, the tissue characteristics and composition of SCI remain elusive. The objective of this work was therefore to investigate the composition of segmented SCI lesions using quantitative MRI for R and quantitative magnetic susceptibility mapping (QSM). 211 SCI lesions were segmented from 32 participants with SCA and 6 controls. SCI were segmented according to two definitions (FLAIR+/-T1w-based threshold) using a semi-automated pipeline. Magnetic susceptibility (χ) and R maps were calculated from a multi-echo gradient echo sequence and mean SCI values were compared to an equivalent region of interest in normal appearing white matter (NAWM). SCI χ and R were investigated as a function of SCI definition, patient demographics, anatomical location, and cognition. Compared to NAWM, SCI were significantly less diamagnetic (χ = -0.0067 ppm vs. -0.0153 ppm, p < 0.001) and had significantly lower R (16.7 s-1 vs. 19.2 s-1, p < 0.001). SCI definition had a significant effect on the mean SCI χ and R , with lesions becoming significantly less diamagnetic and having significantly lower R after the application of a more stringent T1w-based threshold. SCI-NAWM R decrease was significantly greater in patients with SCA compared with controls (-2.84 s-1 vs. -0.64 s-1, p < 0.0001). No significant association was observed between mean SCI-NAWM χ or R2* differences and subject age, lesion anatomical location, or cognition. The increased χ and decreased R in SCI relative to NAWM observed in both patients and controls is indicative of lower myelin or increased water content within the segmented lesions. The significant SCI-NAWM R differences observed between SCI in patients with SCA and controls suggests there may be differences in tissue composition relative to NAWM in SCI in the two populations. Quantitative MRI techniques such as QSM and R mapping can be used to enhance our understanding of the pathophysiology and composition of SCI in patients with SCA as well as controls.

Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks

Quantitative susceptibility mapping (QSM) is an MRI post-processing technique that produces spatially resolved magnetic susceptibility maps from phase data. However, the traditional QSM reconstruction pipeline involves multiple non-trivial steps, including phase unwrapping, background field removal, and dipole inversion. These intermediate steps not only increase the reconstruction time but accumulates errors. This study aims to overcome existing limitations by developing a Laplacian-of-Trigonometric-functions (LoT) enhanced deep neural network for near-instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MRI phase data. The proposed iQFM and iQSM methods were compared with established reconstruction pipelines on simulated and in vivo datasets. In addition, experiments on patients with intracranial hemorrhage and multiple sclerosis were also performed to test the generalization of the proposed neural networks. The proposed iQFM and iQSM methods in healthy subjects yielded comparable results to those involving the intermediate steps while dramatically improving reconstruction accuracies on intracranial hemorrhages with large susceptibilities. High susceptibility contrast between multiple sclerosis lesions and healthy tissue was also achieved using the proposed methods. Comparative studies indicated that the most significant contributor to iQFM and iQSM over conventional multi-step methods was the elimination of traditional Laplacian unwrapping. The reconstruction time on the order of minutes for traditional approaches was shortened to around 0.1 s using the trained iQFM and iQSM neural networks.

Magnetic Susceptibility Source Separation Solely from Gradient Echo Data: Histological Validation.

Quantitative susceptibility mapping (QSM) facilitates mapping of the bulk magnetic susceptibility of tissue from the phase of complex gradient echo (GRE) MRI data. QSM phase processing combined with an model of magnitude of multiecho gradient echo data () allows separation of dia- and para-magnetic components (e.g., myelin and iron) that contribute constructively to value but destructively to the QSM value of a voxel. This technique is validated against quantitative histology—optical density of myelin basic protein and Perls’ iron histological stains of rim and core of 10 ex vivo multiple sclerosis lesions, as well as neighboring normal appearing white matter. We found that source maps are in good qualitative agreement with histology, e.g., showing increased iron concentration at the edge of the rim+ lesions and myelin loss in the lesions’ core. Furthermore, our results indicate statistically significant correlation between paramagnetic and diamagnetic tissue components estimated with and optical densities of Perls’ and MPB stains. These findings provide direct support for the use of magnetic source separation based solely on GRE complex data to characterize MS lesion composition.

Assessing Mild Cognitive Impairment in Parkinson’s Disease by Magnetic Resonance Quantitative Susceptibility Mapping Combined Voxel-Wise and Radiomic Analysis

Background: The relationship between iron accumulation in the central nervous system and cognitive decline in Parkinson’s disease (PD) has not been fully elucidated. This study aimed to explore the value of quantitative susceptibility mapping in assessment of mild cognitive impairment (MCI) in PD. Methods: Sixteen PD patients with MCI (PD-MCI), sixteen normal cognition PD patients (PD-NC), and 28 healthy controls (HCs) were included. The differences in the magnetic susceptibility and Radiomic indicators among groups and their correlations with Montreal Cognitive Assessment-Basic (MoCA-B) scores and Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) were analyzed. Receiver operating characteristic curves were used to evaluate the diagnostic performance. Results: Higher iron deposition was observed in the cortical and subcortical structures of the PD patients compared with HCs, including limbic system, orbitofrontal cortex, cuneus, red nucleus, and substantia nigra. Combined magnetic susceptibility and texture index in hippocampus achieved the best diagnostic performance (area under curves: 0.828) in differentiating PD-MCI from PD-NC. The magnetic susceptibilities of the substantia nigra, red nucleus, putamen, globus pallidus, hippocampus, and thalamus were negatively correlated with the MoCA-B scores (all p < 0.05), and of the putamen and amygdala were positively correlated with the UPDRS-III scores (both p < 0.05). Conclusion: Higher iron deposition was observed in the cortical and subcortical structures of the PD-MCI and PD-NC groups. The susceptibility values of vulnerable brain subregions shown significant correlation with MoCA-B and UPDRS-III. Together with the texture index, magnetic susceptibility values could provide robust performance in distinguishing PD-MCI patients from PD-NC.

Region-specific disturbed iron redistribution in Cushing's disease measured by magnetic resonance imaging-based quantitative susceptibility mapping.

Cushing's disease (CD) is most common endogenous Cushing's syndrome. This study aimed to assess iron alternations in deep grey matter in CD. A cross-sectional study was performed. In this study, 48 active CD patients, 39 remitted CD patientsand 52 healthy control (HC) subjects underwent magnetic resonance imaging. Quantitative susceptibility mapping (QSM). Decreased susceptibility values were found in the bilateral putamen, caudate, red nucleus, subthalamic nucleusand pulvinar nuclei of the thalamus (TL-PLV) in active and remitted patients with CD compared with HCs. Interestingly, in remitted patients with CD, altered susceptibility values were significantly correlated with altered brain volumes in TL-PLV, while TL-PLV may play an essential role as a general regulatory hub for adaptive and flexible cognition. Chronic exposure to hypercortisolism may be related to iron distribution and significantly correlated with altered brain volumes and clinical features in patients with CD.

Penumbra Detection With Oxygen Extraction Fraction Using Magnetic Susceptibility in Patients With Acute Ischemic Stroke.

BackgroundThe oxygen extraction fraction (OEF) has been applied to identify ischemic penumbral tissue, but is difficult to use in an urgent care setting. This study aimed to investigate whether an OEF map generated via magnetic resonance quantitative susceptibility mapping (QSM) could help identify the ischemic penumbra in patients with acute ischemic stroke.Materials and MethodsThis prospective imaging study included 21 patients with large anterior circulation vessel occlusion who were admitted <24 h after stroke onset and 21 age-matched healthy controls. We identified the ischemic penumbra as the region with a Tmax of >6 s during dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI) and calculated the perfusion-core mismatch ratio between the ischemic penumbra and infarct core volumes. The OEF values were measured based on magnetic susceptibility differences between the venous structures and brain tissues using rapid QSM acquisition. Volumes with increased OEF values were compared to the ischemic penumbra volumes using an anatomical template.ResultsEleven patients had a perfusion-core mismatch ratio of ≥1.8, and reperfusion therapy was recommended. In these patients, the volumes with increased OEF values of >51.5%, which was defined using the anterior circulation territory OEF values from the 21 healthy controls, were positively correlated with the ischemic penumbra volumes (r = 0.636, 95% CI: 0.059 to 0.895, P = 0.035) and inversely correlated with the 30-day change in the National Institutes of Health Stroke Scale scores (r = −0.624, 95% CI: −0.891 to −0.039, P = 0.041).ConclusionTissue volumes with increased OEF values could predict ischemic penumbra volumes based on DSC-MRI, highlighting the potential of the QSM-derived OEF map as a penumbra biomarker to guide treatment selection in patients with acute ischemic stroke.

Preliminary Investigation of Soil and Sediments Using Magnetic Susceptibility Method in Kogi State, Nigeria

Over the years, there has been significant increase in population and urbanization in Kogi State as a result of rural - urban migration. This has become a major threat to soil sustainability which is a natural non-renewable resource. The aim of this research is to carry out magnetic susceptibility mapping on the surface and subsurface soil of Kogi State using environmental magnetism techniques and geochemical analysis. The susceptibility test on rock samples and background soil samples within the study area shows an average of about 112.0 × 10^-5 SI. The magnetic susceptibility measurement on soil from Kogi State shows magnetic susceptibility enhancement of about (450.0 - 700.0) × 10^-5 SI. These values were dominant along the major towns, road pavements and commercial areas at the surface to a depth of about 50.0 cm in soil profiles. The 2D spatial distribution of magnetic susceptibility with depth reveals that these magnetic grains are distributed in the subsurface as a result of anthropogenic loading. The frequency-dependence of magnetic susceptibility (χfd%) values are very low (2 - 10.0 %) in most of the areas on the surface soil. These values indicate that the magnetic properties are predominantly contributed by the coarse multi-domain (MD) and stable single-domain (SSD) grains of anthropogenic origin. Atomic Absorbtion Spectrometer (AAS) analysis of these soil samples indicates the presence of Lead (300.0 - 900.0) mg/l and Cadmium (20.0 - 60.0) mg/l in large concentration at the surface soil in most part of the Kogi State. While Chromium show relatively low concentration on the surface soil. From the statistical correlation analysis, Lead and Cadmium show high positive correlation with magnetic susceptibility. These results suggests that the high enhancement of magnetic susceptibility on the surface and sub-surface soil in most part of Kogi State arise from anthropogenic activities rather than lithological and pedogenic processes and most likely cause by high concentration of Lead and Cadmium.

A Pilot Study in Archaeological Metal Detector Geophysical Survey

Abstract Metal detection (MD) has traditionally been viewed as a limited geophysical survey method for the identification of metal objects below the surface. However, this pilot study examines techniques utilizing the “ground balance” function, common to most modern metal detectors, to identify subsurface magnetic anomalies. The results of surveys have yielded inconclusive results on the use of metal detectors for feature identification. However, the results of this study suggest a high potential for more efficient and more productive archaeological reconnaissance surveys. The ground balance function, when combined with systematic sampling and geographic information systems interpolation methods, yields low-resolution subsoil magnetic susceptibility maps. Compared to other geophysical methods, such as gradiometry or electrical resistivity, the depth range of MD is limited. However, this technique, in upland contexts with shallow subsoils or sites with high potential for recent ground disturbing activities, can reveal subtle changes in the subsurface that traditional MD techniques would miss. Further studies are recommended to explore the many situations in which a metal detector can provide an informative alternative, though not a replacement, for other geophysical survey methods. This pilot study was funded by the National Geographic Society’s Early Career Grant program.

Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction.

Compared with conventional magnetic resonance imaging methods, the quantitative magnetic susceptibility mapping (QSM) technique can quantitatively measure the magnetic susceptibility distribution of tissues, which has an important clinical application value in the investigations of brain micro-bleeds, Parkinson's, and liver iron deposition, etc. However, the quantitative susceptibility mapping algorithm is an ill-posed inverse problem due to the near-zero value in the dipole kernel, and high-quality QSM reconstruction with effective streaking artifact suppression remains a challenge. In recent years, the performance of sparse representation has been well validated in improving magnetic resonance image (MRI) reconstruction. In this study, by incorporating feature learning into sparse representation, we propose an edge prior guided dictionary learning-based reconstruction method for the dipole inversion in quantitative susceptibility mapping reconstruction. The structure feature dictionary relies on magnitude images for susceptibility maps have similar structures with magnitude images, and this structure feature dictionary and edge prior information are used in the dipole inversion step. The performance of the proposed algorithm is assessed through in vivo human brain clinical data, leading to high-quality susceptibility maps with improved streaking artifact suppression, structural recovery, and quantitative metrics. The proposed edge prior guided dictionary learning method for dipole inversion in QSM achieves improved performance in streaking artifacts suppression, structural recovery and deep gray matter reconstruction.

Three-dimensional simultaneous brain mapping of T1,T2, and magnetic susceptibility with MR Multitasking.

To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan. The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined. High quality, co-registered T1 , T2 , and susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images. The MR Multitasking-based 3D brain mapping of T1 , T2 , , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.