Exploring the origins of echo-time-dependent quantitative susceptibility mapping (QSM) measurements in healthy tissue and cerebral microbleeds

Paramagnetic susceptibility measured by magnetic resonance imaging as an in vivo biomarker for iron pathology in epilepsy

Epilepsy, a neurological disorder marked by recurrent, unprovoked seizures, is often linked to dysregulated iron metabolism, resulting in iron overload and subsequent cellular dysfunction or death within epileptogenic regions. We proposed a specific, noninvasive technique using paramagnetic susceptibility imaging via magnetic resonance imaging to quantify in vivo brain iron levels, aiming to enhance our understanding of epilepsy pathology and improve diagnostic accuracy. Our imaging and histopathological studies demonstrated that paramagnetic susceptibility is a sensitive biomarker for iron quantification in epilepsy. This method effectively detects iron abnormality from various causes and highlights that iron alters within epileptogenic zones, indicating the presence of potentially salvageable tissue. Furthermore, iron accumulation was observed to disrupt cortical laminar structures in epileptogenic zones and was associated with the proliferation of central nervous system cells, particularly astrocytes. Paramagnetic susceptibility imaging provides previously unknown insights into epilepsy, offering potential applications in diagnostics, monitoring, and personalized treatment strategies.

Quantitative Susceptibility Mapping MRI with Computer Vision Metrics to Reduce Scan Time for Brain Hemorrhage Assessment

Purpose

Optimizing clinical imaging parameters balances scan time and image quality. Quantitative Susceptibility Mapping (QSM) MRI, particularly for detecting intracranial hemorrhage (ICH), involves multiple echo times (TEs), leading to longer scan durations that can impact patient comfort and imaging efficiency. This study evaluates the necessity of specific TEs for QSM MRI in ICH patients and identifies shorter scan protocols using Computer Vision Metrics (CVMs) to maintain diagnostic accuracy.

Approach

54 patients with suspected ICH were retrospectively recruited. Multi-echo Gradient Recalled Echo (mGRE) sequences with 11 TEs were used for QSM MRI (reference). Subsets of TEs compatible with producing QSM MRI images were generated, producing 71 subgroups per patient. QSM images from each subgroup were compared to reference images using 14 CVMs. Linear regression and Wilcoxon Signed-Rank tests identified optimal subgroups minimizing scan time while preserving image quality as part of the computer vision Optimized Rapid Imaging (CORI) method described.

Results

CVM based analysis demonstrated subgroup 1 (TE1-3) to be optimal using several CVMs, supporting a reduction in scan time from 4.5 to 1.23 minutes (73% reduction). Other CVMs suggested longer maximum TE subgroups as optimal, achieving scan time reductions of 9% to 37%. Visual assessments by a neuroradiologist and trained research assistant confirmed no significant difference in ICH area measurements between reference and CORI identified optimal subgroup derived QSM, while CORI identified worst subgroups derived QSM differed significantly (p < 0.05).

Conclusions

The findings support using shorter QSM MRI protocols for ICH evaluation and suggest CVMs may aid optimization efforts for other clinical imaging protocols.

Multiband accelerated 2D EPI for multi-echo brain QSM at 3 T

PURPOSE

Data for QSM are typically acquired using multi-echo 3D gradient echo (GRE), but EPI can be used to accelerate QSM and provide shorter acquisition times. So far, EPI-QSM has been limited to single-echo acquisitions, which, for 3D GRE, are known to be less accurate than multi-echo sequences. Therefore, we compared single-echo and multi-echo EPI-QSM reconstructions across a range of parallel imaging and multiband acceleration factors.

METHODS

Using 2D single-shot EPI in the brain, we compared QSM from single-echo and multi-echo acquisitions across combined parallel-imaging and multiband acceleration factors ranging from 2 to 16, with volume pulse TRs from 21.7 to 3.2 s, respectively. For single-echo versus multi-echo reconstructions, we investigated the effect of acceleration factors on regional susceptibility values, temporal noise, and image quality. We introduce a novel masking method based on thresholding the magnitude of the local field gradients to improve brain masking in challenging regions.

RESULTS

At 1.6-mm isotropic resolution, high-quality QSM was achieved using multi-echo 2D EPI with a combined acceleration factor of 16 and a TR of 3.2 s, which enables functional applications. With these high acceleration factors, single-echo reconstructions are inaccurate and artefacted, rendering them unusable. Multi-echo acquisitions greatly improve QSM quality, particularly at higher acceleration factors, provide more consistent regional susceptibility values across acceleration factors, and decrease temporal noise compared with single-echo QSM reconstructions.

CONCLUSION

Multi-echo acquisition is more robust for EPI-QSM across parallel imaging and multiband acceleration factors than single-echo acquisition. Multi-echo EPI can be used for highly accelerated acquisition while preserving QSM accuracy and quality relative to gold-standard 3D-GRE QSM.

Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo

T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2: 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0 of 3 T or higher with no additional time cost, when standard T2*-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.

Central Vein Sign and Paramagnetic Rim Lesions: Susceptibility Changes in Brain Tissues and Their Implications for the Study of Multiple Sclerosis Pathology

Multiple sclerosis (MS) is the most common acquired inflammatory and demyelinating disease in adults. The conventional diagnostic of MS and the follow-up of inflammatory activity is based on the detection of hyperintense foci in T2 and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) and lesions with brain-blood barrier (BBB) disruption in the central nervous system (CNS) parenchyma. However, T2/FLAIR hyperintense lesions are not specific to MS and the MS pathology and inflammatory processes go far beyond focal lesions and can be independent of BBB disruption. MRI techniques based on the magnetic susceptibility properties of the tissue, such as T2*, susceptibility-weighted images (SWI), and quantitative susceptibility mapping (QSM) offer tools for advanced MS diagnostic, follow-up, and the assessment of more detailed features of MS dynamic pathology. Susceptibility-weighted techniques are sensitive to the paramagnetic components of biological tissues, such as deoxyhemoglobin. This capability enables the visualization of brain parenchymal veins. Consequently, it presents an opportunity to identify veins within the core of multiple sclerosis (MS) lesions, thereby affirming their venocentric characteristics. This advancement significantly enhances the accuracy of the differential diagnostic process. Another important paramagnetic component in biological tissues is iron. In MS, the dynamic trafficking of iron between different cells, such as oligodendrocytes, astrocytes, and microglia, enables the study of different stages of demyelination and remyelination. Furthermore, the accumulation of iron in activated microglia serves as an indicator of latent inflammatory activity in chronic MS lesions, termed paramagnetic rim lesions (PRLs). PRLs have been correlated with disease progression and degenerative processes, underscoring their significance in MS pathology. This review will elucidate the underlying physical principles of magnetic susceptibility and their implications for the formation and interpretation of T2*, SWI, and QSM sequences. Additionally, it will explore their applications in multiple sclerosis (MS), particularly in detecting the central vein sign (CVS) and PRLs, and assessing iron metabolism. Furthermore, the review will discuss their role in advancing early and precise MS diagnosis and prognostic evaluation, as well as their utility in studying chronic active inflammation and degenerative processes.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Exploiting gradient-echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility-induced frequency for quantitative susceptibility mapping

PURPOSE

This work is to investigate the microstructure-induced frequency shift in white matter (WM) with crossing fibers and to separate the microstructure-related frequency shift from the bulk susceptibility-induced frequency shift by model fitting the gradient-echo (GRE) frequency evolution for potentially more accurate quantitative susceptibility mapping (QSM).

METHODS

A hollow-cylinder fiber model (HCFM) with two fiber populations was developed to investigate GRE frequency evolutions in WM voxels with microstructural orientation dispersion. The simulated and experimentally measured TE-dependent local frequency shift was then fitted to a simplified frequency evolution model to obtain a microstructure-related frequency difference parameter (∆ f $$ \Delta f $$ ) and a TE-independent bulk susceptibility-induced frequency shift (C f $$ {C}_f $$ ). The obtainedC f $$ {C}_f $$ was then used for QSM reconstruction. Reconstruction performances were evaluated using a numerical head phantom and in vivo data and then compared to other multi-echo combination methods.

RESULTS

GRE frequency evolutions and∆ f $$ \Delta f $$ -based tissue parameters in both parallel and crossing fibers determined from our simulations were comparable to those observed in vivo. The TE-dependent frequency fitting method outperformed other multi-echo combination methods in estimatingC f $$ {C}_f $$ in simulations. The fitted∆ f $$ \Delta f $$ ,C f $$ {C}_f $$ , and QSM could be improved further by navigator-based B0 fluctuation correction.

CONCLUSION

A HCFM with two fiber populations can be used to characterize microstructure-induced frequency shifts in WM regions with crossing fibers. HCFM-based TE-dependent frequency fitting provides tissue contrast related to microstructure (∆ f $$ \Delta f $$ ) and in addition may help improve the quantification accuracy ofC f $$ {C}_f $$ and the corresponding QSM.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

Optimal echo times for quantitative susceptibility mapping: A test-retest study on basal ganglia and subcortical brain nuclei

Quantitative Susceptibility Mapping (QSM) is a recent MRI-technique able to quantify the bulk magnetic susceptibility of myelin, iron, and calcium in the brain. Its variability across different acquisition parameters has prompted the need for standardisation across multiple centres and MRI vendors. However, a high level of agreement between repeated imaging acquisitions is equally important. With this study we aimed to assess the inter-scan repeatability of an optimised multi-echo GRE sequence in 28 healthy volunteers. We extracted and compared the susceptibility measures from the scan and rescan acquisitions across 7 bilateral brain regions (i.e., 14 regions of interest (ROIs)) relevant for neurodegeneration. Repeatability was first assessed while reconstructing QSM with a fixed number of echo times (i.e., 8). Excellent inter-scan repeatability was found for putamen, globus pallidus and caudate nucleus, while good performance characterised the remaining structures. An increased variability was instead noted for small ROIs like red nucleus and substantia nigra. Secondly, we assessed the impact exerted on repeatability by the number of echoes used to derive QSM maps. Results were impacted by this parameter, especially in smaller regions. Larger brain structures, on the other hand, showed more consistent performance. Nevertheless, with either 8 or 7 echoes we managed to obtain good inter-scan repeatability on almost all ROIs. These findings indicate that the designed acquisition/reconstruction protocol has wide applicability, particularly in clinical or research settings involving longitudinal acquisitions (e.g. rehabilitation studies).

Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group

This article provides recommendations for implementing quantitative susceptibility mapping (QSM) for clinical brain research. It is a consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available give rise to the need in the neuroimaging community for guidelines on implementation. This article describes relevant considerations and provides specific implementation recommendations for all steps in QSM data acquisition, processing, analysis, and presentation in scientific publications. We recommend that data be acquired using a monopolar 3D multi-echo GRE sequence, that phase images be saved and exported in DICOM format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields should be removed within the brain mask using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of whole brain as a region of interest in the analysis, and QSM results should be reported with - as a minimum - the acquisition and processing specifications listed in the last section of the article. These recommendations should facilitate clinical QSM research and lead to increased harmonization in data acquisition, analysis, and reporting.

Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework

High-resolution magnetic resonance imaging (MRI) affords unique image contrasts to nondestructively probe the tissue microstructure; validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impedes accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multigradient recalled-echo and multishell diffusion MRI datasets at 25-μm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common three-dimensional (3D) space. The T2*, quantitative susceptibility mapping, diffusion tensor imaging, and neurite orientation dispersion and density imaging parameters were compared with both serial two-photon tomography images and 3D Nissl staining images in the CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.

Simulated and experimental phantom data for multi-center quality assurance of quantitative susceptibility maps at 3 T, 7 T and 9.4 T

PURPOSE

To develop methods for quality assurance of quantitative susceptibility mapping (QSM) using MRI at different magnetic field strengths, and scanners, using different MR-sequence protocols, and post-processing pipelines.

METHODS

We built a custom phantom based on iron in two forms: homogeneous susceptibility ('free iron') and with fine-scaled variations in susceptibility ('clustered iron') at different iron concentrations. The phantom was measured at 3.0 T (two scanners), 7.0 T and 9.4 T using multi-echo, gradient echo acquisition sequences. A digital phantom analogue to the iron-phantom, tailored to obtain similar results as in experimentation was developed, with similar geometry and susceptibility values. Morphology enabled dipole inversion was applied to the phase images to obtain QSM for experimental and simulated data using the MEDI + 0 approach for background regularization.

RESULTS

Across all scanners, QSM-values showed a linear increase with iron concentrations. The QSM-relaxivity was 0.231 ± 0.047 ppm/mM for free and 0.054 ± 0.013 ppm/mM for clustered iron, with adjusted determination coefficients (DoC) ≥ 0.87. Similarly, the simulations yielded linear increases (DoC ≥ 0.99). In both the experimental and digital phantoms, the estimated molar susceptibility was lower with clustered iron, because clustering led to highly localized field effects.

CONCLUSION

Our iron phantom can be used to evaluate the capability of QSM to detect local variations in susceptibility across different field strengths, when using different MR-sequence protocols. The devised simulation method captures the effect of iron clustering in QSM as seen experimentally and could be used in the future to optimize QSM processing pipelines and achieve higher accuracy for local field effects, as also seen in Alzheimer's beta-amyloid plaques.

Multi-echo dipole inversion for magnetic susceptibility mapping

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.

Phase-based masking for quantitative susceptibility mapping of the human brain at 9.4T

PURPOSE

To develop improved tissue masks for QSM.

METHODS

Masks including voxels at the brain surface were automatically generated from the magnitude alone (MM) or combined with test functions from the first (PG) or second (PB) derivative of the sign of the wrapped phase. Phase images at 3T and 9.4T were simulated at different TEs and used to generate a mask, PItoh , with between-voxel phase differences less than π. MM, PG, and PB were compared with PItoh . QSM were generated from 3D multi-echo gradient-echo data acquired at 9.4T (21 subjects aged: 20-56y), and from the QSM2016 challenge 3T data using different masks, unwrapping, background removal, and dipole inversion algorithms. QSM contrast was quantified using age-based iron concentrations.

RESULTS

Close to air cavities, phase wraps became denser with increasing field and echo time, yielding increased values of the test functions. Compared with PItoh , PB had the highest Dice coefficient, while PG had the lowest and MM the highest percentage of voxels outside PItoh. Artifacts observed in QSM at 9.4T with MM were mitigated by stronger background filters but yielded a reduced QSM contrast. With PB, QSM contrast was greater and artifacts diminished. Similar results were obtained with challenge data, evidencing larger effects of mask close to air cavities.

CONCLUSION

Automatic, phase-based masking founded on the second derivative of the sign of the wrapped phase, including cortical voxels at the brain surface, was able to mitigate artifacts and restore QSM contrast across cortical and subcortical brain regions.

Multi-echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla

Purpose

To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal.

Methods

Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests).

Results

Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of χ and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions.

Conclusion

For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.

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Diagnostic accuracy of quantitative susceptibility mapping in multiple system atrophy: The impact of echo time and the potential of histogram analysis

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We performed histogram analysis on χ maps at different TEs on MSA patients and HC.

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We found altered χ distribution in Pu, SN, GP, CN for MSAp and in SN, DN for MSAc.

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QSM diagnostic accuracy is TE-dependent and is enhanced at short TEs.

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Short TEs capture rapidly-decaying contributions of high χ sources.

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Histogram features detect χ spatial heterogeneities improving diagnostic accuracy.

The non-invasive quantification of iron stores via Quantitative Susceptibility Mapping (QSM) could play an important role in the diagnosis and the differential diagnosis of atypical Parkinsonisms. However, the susceptibility (χ) values measured via QSM depend on echo time (TE). This effect relates to the microstructural organization within the voxel, whose composition can be altered by the disease. Moreover, pathological iron deposition in a brain area may not be spatially uniform, and conventional Region of Interest (ROI)-based analysis may fail in detecting alterations. Therefore, in this work we evaluated the impact of echo time on the diagnostic accuracy of QSM on a population of patients with Multiple System Atrophy (MSA) of either Parkinsonian (MSAp) or cerebellar (MSAc) phenotypes. In addition, we tested the potential of histogram analysis to improve QSM classification accuracy.

We enrolled 32 patients (19 MSAp and 13 MSAc) and 16 healthy controls, who underwent a 7T MRI session including a gradient-recalled multi-echo sequence for χ mapping. Nine histogram features were extracted from the χ maps computed for each TE in atlas-based ROIs covering deep brain nuclei, and compared among groups.

Alterations of susceptibility distribution were found in the Putamen, Substantia Nigra, Globus Pallidus and Caudate Nucleus for MSAp and in the Substantia Nigra and Dentate Nucleus for MSAc. Increased iron deposition was observed in a larger number of ROIs for the two shortest TEs and the standard deviation, the 75^th and the 90^th percentile were the most informative features yielding excellent diagnostic accuracy with area under the ROC curve > 0.9.

In conclusion, short TEs may enhance QSM diagnostic performances, as they can capture variations in rapidly-decaying contributions of high χ sources. The analysis of histogram features allowed to reveal fine heterogeneities in the spatial distribution of susceptibility alteration, otherwise undetected by a simple evaluation of ROI χ mean values.

Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T

Quantitative susceptibility mapping (QSM) has the potential for being a biomarker for various diseases because of its ability to measure tissue susceptibility related to iron deposition, myelin, and hemorrhage from the phase signal of a T2 *-weighted MRI. Despite its promise as a quantitative marker, QSM is faced with many challenges, including its dependence on preprocessing of the raw phase data, the relatively weak tissue signal, and the inherently ill posed relationship between the magnetic dipole and measured phase. The goal of this study was to evaluate the effects of background field removal and dipole inversion algorithms on noise characteristics, image uniformity, and structural contrast for cerebral microbleed (CMB) quantification at both 3T and 7T. We selected four widely used background phase removal and five dipole field inversion algorithms for QSM and applied them to volunteers and patients with CMBs, who were scanned at two different field strengths, with ground truth QSM reference calculated using multiple orientation scans. 7T MRI provided QSM images with lower noise than did 3T MRI. QSIP and VSHARP + iLSQR achieved the highest white matter homogeneity and vein contrast, with QSIP also providing the highest CMB contrast. Compared with ground truth COSMOS QSM images, overall good correlations between susceptibility values of dipole inversion algorithms and the COSMOS reference were observed in basal ganglia regions, with VSHARP + iLSQR achieving the susceptibility values most similar to COSMOS across all regions. This study can provide guidance for selecting the most appropriate QSM processing pipeline based on the application of interest and scanner field strength.

Simultaneous Quantitative Susceptibility Mapping of Articular Cartilage and Cortical Bone of Human Knee Joint Using Ultrashort Echo Time Sequences

BACKGROUND

It is of great clinical importance to assess the microstructure of the articular cartilage and cortical bone of the human knee joint. While quantitative susceptibility mapping (QSM) is a promising tool for investigating the knee joint, however, previous QSM studies using conventional gradient recalled echo sequences or ultrashort echo time (UTE) sequences only focused on mapping the magnetic susceptibility of the articular cartilage or cortical bone, respectively. Simultaneously mapping the underlying susceptibilities of the articular cartilage and cortical bone of human in vivo has not been explored and reported.

METHOD

Three-dimensional multi-echo radial UTE sequences with the shortest TE of 0.07 msec and computed tomography (CT) were performed on the bilateral knee joints of five healthy volunteers for this prospective study. UTE-QSM was reconstructed from the local field map after water-fat separation and background field removal. Spearman's correlation analysis was used to explore the relationship between the magnetic susceptibility and CT values in 158 representative regions of interest of cortical bone.

RESULT

The susceptibility properties of the articular cartilage and cortical bone were successfully quantified by UTE-QSM. The laminar structure of articular cartilage was characterized by the difference of susceptibility value in each layer. Susceptibility was mostly diamagnetic in cortical bone. A significant negative correlation (r=-0.43, p<0.001) between the susceptibility value and CT value in cortical bone was observed.

CONCLUSION

UTE-QSM enables simultaneous susceptibility mapping of the articular cartilage and cortical bone of human in vivo. Good association between susceptibility and CT values in cortical bone suggests the potential of UTE-QSM for bone mapping for further clinical application.

Complementing canonical fMRI with functional Quantitative Susceptibility Mapping (fQSM) in modern neuroimaging research

Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and "On/Off" paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.

Comparison of Phase Estimation Methods for Quantitative Susceptibility Mapping Using a Rotating-Tube Phantom

Quantitative Susceptibility Mapping (QSM) is an MRI tool with the potential to reveal pathological changes from magnetic susceptibility measurements. Before phase data can be used to recover susceptibility (Δχ), the QSM process begins with two steps: data acquisition and phase estimation. We assess the performance of these steps, when applied without user intervention, on several variations of a phantom imaging task. We used a rotating-tube phantom with five tubes ranging from Δχ=0.05 ppm to Δχ=0.336 ppm. MRI data was acquired at nine angles of rotation for four different pulse sequences. The images were processed by 10 phase estimation algorithms including Laplacian, region-growing, branch-cut, temporal unwrapping, and maximum-likelihood methods, resulting in approximately 90 different combinations of data acquisition and phase estimation methods. We analyzed errors between measured and expected phases using the probability mass function and Cumulative Distribution Function. Repeatable acquisition and estimation methods were identified based on the probability of relative phase errors. For single-echo GRE and segmented EPI sequences, a region-growing method was most reliable with Pr (relative error <0.1) = 0.95 and 0.90, respectively. For multiecho sequences, a maximum-likelihood method was most reliable with Pr (relative error <0.1) = 0.97. The most repeatable multiecho methods outperformed the most repeatable single-echo methods. We found a wide range of repeatability and reproducibility for off-the-shelf MRI acquisition and phase estimation approaches, and this variability may prevent the techniques from being widely integrated in clinical workflows. The error was dominated in many cases by spatially discontinuous phase unwrapping errors. Any postprocessing applied on erroneous phase estimates, such as QSM's background field removal and dipole inversion, would suffer from error propagation. Our paradigm identifies methods that yield consistent and accurate phase estimates that would ultimately yield consistent and accurate Δχ estimates.

Investigating Optimal Echo Times for Quantitative Susceptibility Mapping of Basal Ganglia Nuclei in the Healthy Brain

BACKGROUND

Quantitative susceptibility mapping (QSM) technique had been used to measure the magnetic susceptibility of brain tissue in clinical practice. However, QSM presented echo-time (TE) dependence, and an appropriate number of echo-times (nTEs) for QSM became more important to obtain the reliable susceptibility value.

OBJECTIVE

The aim of the study was to explore the optimal nTEs for quantitative susceptibility mapping (QSM) measurements of basal ganglia nuclei in the healthy brain.

METHODS

3D multi-echo enhanced gradient recalled echo T2 star weighted angiography (ESWAN) sequence was acquired on a 3.0T MR scanner for QSM analysis. Regions of interests (ROIs) were drawn along the margin of the head of the caudate nucleus (HCN), putamen (Pu) and globus pallidus (GP). The mean susceptibility value and standard deviation of the ROIs were derived from the pixels within each region.

RESULTS

CV analysis demonstrated that TE6, TE8 and TE14 ESWAN sequences presented consistent lower CV value (< 1) for QSM measure of HCN, Pu and GP. ANOVA identified that susceptibility value showed no significant difference between TE6 and TE8 in HCN, Pu and GP (P > 0.05). ICC analysis demonstrated that the susceptibility value of TE6-TE8 had the highest ICC value as compared with TE6-TE14 and TE8-TE14 in HCN, Pu and GP. Combined with the timeefficiency of MRI scanning, TE6 sequence could not only provide the reliable QSM measurement but also short imaging time.

CONCLUSION

The current study identified that the optimal nTEs of ESWAN were 6 TEs (2.9ms ~ 80.9ms) for QSM measurement of basal ganglia nuclei in the healthy brain.

The Effect of Deep Learning-Based QSM Magnetic Resonance Imaging on the Subthalamic Nucleus

In order to study the influence of quantitative magnetic susceptibility mapping (QSM) on them. A 2.5D Attention U-Net Network based on multiple input and multiple output, a method for segmenting RN, SN, and STN regions in high-resolution QSM images is proposed, and deep learning realizes accurate segmentation of deep nuclei in brain QSM images. Experimental results show data first cuts each layer of 0 100 case data, based on the image center, from 384 × 288 to the size of 128 × 128. Image combination: each layer of the image in the layer direction combines with two adjacent images into a 2.5D image, i.e., (It - m It; It + i), where It represents the layer i image. At this time, the size of the image changes from 128 × 128 to 128 × 128 × 3, in which 3 represents three consecutive layers of images. The SNR of SWP I to STN is twice that of SWI. The small deep gray matter nuclei (RN, SN, and STN) in QSM images of the brain and the pancreas with irregular shape and large individual differences in abdominal CT images can be automatically segmented.

On the separation of susceptibility sources in quantitative susceptibility mapping: Theory and phantom validation with an in vivo application to multiple sclerosis lesions of different age

PURPOSE

In biological tissue, phase contrast is determined by multiple substances such as iron, myelin or calcifications. Often, these substances occur co-located within the same measurement volume. However, quantitative susceptibility mapping can solely measure the average susceptibility per voxel. To provide new insight in disease progression and mechanisms in neurological diseases, where multiple processes such as demyelination and iron accumulation occur simultaneously in the same location, a separation of susceptibility sources is desirable to disentangle the underlying susceptibility proportions.

METHODS

The basic concept of separating the susceptibility effects from sources with different sign within one voxel is to include information on relaxation rate ΔR₂^∗ in the quantitative susceptibility mapping reconstruction pipeline. The presented reconstruction algorithm is implemented as a constrained minimization problem and solved using conjugate gradients. The algorithm is evaluated using a software phantom and validated in MRI measurements with a phantom containing mixtures of microscopic positive and negative susceptibility sources. Data from three multiple sclerosis patients are used to show in vivo feasibility.

RESULTS

In numerical simulations, the feasibility of disentangling susceptibility sources within the same voxel was confirmed provided the critera of the static dephasing regime were fulfilled. In phantom experiments, the magnitude decay kernel, which is an essential reconstruction parameter of the algorithm, was determined to be D_m=194.5T^-1s^-1ppm^-1, and susceptibility sources could be separated in MRI measurement data.

CONCLUSIONS

In conclusion, in this study a detailed description of the implementation of an algorithm for the separation of positive and negative susceptibility sources within the same volume element as well as its limitations is presented and validated quantitatively in both simulation and phantom experiments for the first time. An application to multiple sclerosis lesions shows promising results for in vivo usability.

Decompose quantitative susceptibility mapping (QSM) to sub-voxel diamagnetic and paramagnetic components based on gradient-echo MRI data

PURPOSE

A method named DECOMPOSE-QSM is developed to decompose bulk susceptibility measured with QSM into sub-voxel paramagnetic and diamagnetic components based on a three-pool complex signal model.

METHODS

Multi-echo gradient echo signal is modeled as a summation of three weighted exponentials corresponding to three types of susceptibility sources: reference susceptibility, diamagnetic and paramagnetic susceptibility relative to the reference. Paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS) maps are constructed to represent the sub-voxel compartments by solving for linear and nonlinear parameters in the model.

RESULTS

Numerical forward simulation and phantom validation confirmed the ability of DECOMPOSE-QSM to separate the mixture of paramagnetic and diamagnetic components. The PCS obtained from temperature-variant brainstem imaging follows the Curie's Law, which further validated the model and the solver. Initial in vivo investigation of human brain images showed the ability to extract sub-voxel PCS and DCS sources that produce visually enhanced contrast between brain structures comparing to threshold QSM.

In vivo assessment of anisotropy of apparent magnetic susceptibility in white matter from a single orientation acquisition

Multiple studies have reported a significant dependence of the effective transverse relaxation rate constant (R₂^*) and the phase of gradient-echo based (GRE) signal on the orientation of white matter fibres in the human brain. It has also been hypothesized that magnetic susceptibility, as obtained by single-orientation quantitative susceptibility mapping (QSM), exhibits such a dependence. In this study, we investigated this hypothesized relationship in a cohort of healthy volunteers. We show that R₂^* follows the predicted orientation dependence consistently across white matter regions, whereas the apparent magnetic susceptibility is related differently to fibre orientation across the brain and often in a complex non-monotonic manner. In addition, we explored the effect of fractional anisotropy measured by diffusion-weighted MRI on the strength of the orientation dependence and observed only a limited influence in many regions. However, with careful consideration of such an impact and the limitations imposed by the ill-posed nature of the dipole inversion process, it is possible to study magnetic susceptibility anisotropy in specific brain regions with a single orientation acquisition.

Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning

INTRODUCTION

Quantitative Susceptibility Mapping (QSM) is generally acquired with full brain coverage, even though many QSM brain-iron studies focus on the deep grey matter (DGM) region only. Reducing the spatial coverage to the DGM vicinity can substantially shorten the scan time or enhance the spatial resolution without increasing scan time; however, this may lead to significant DGM susceptibility underestimation.

METHOD

A recently proposed deep learning-based QSM method, namely xQSM, is investigated to assess the accuracy of dipole inversion on reduced brain coverages. The xQSM method is compared with two conventional dipole inversion methods using simulated and in vivo experiments from 4 healthy subjects at 3T. Pre-processed magnetic field maps are extended symmetrically from the centre of globus pallidus in the coronal plane to simulate QSM acquisitions of difference spatial coverages, ranging from 100% (∼32mm) to 400% (∼128mm) of the actual DGM physical size.

RESULTS

The proposed xQSM network led to the lowest DGM contrast loss in both simulated and in vivo subjects, with the smallest susceptibility variation range across all spatial coverages. For the digital brain phantom simulation, xQSM improved the DGM susceptibility underestimation more than 20% in small spatial coverages, as compared to conventional methods. For the in vivo acquisition, less than 5% DGM susceptibility error was achieved in 48mm axial slabs using the xQSM network, while a minimum of 112mm coverage was required for conventional methods. It is also shown that the background field removal process performed worse in reduced brain coverages, which further deteriorated the subsequent dipole inversion.

CONCLUSION

The recently proposed deep learning-based xQSM method significantly improves the accuracy of DGM QSM from small spatial coverages as compared with conventional QSM algorithms, which can shorten DGM QSM acquisition time substantially.

Single-step calculation of susceptibility through multiple orientation sampling

Quantitative susceptibility mapping (QSM) was developed to estimate the spatial distribution of magnetic susceptibility from MR signal phase acquired using a gradient echo (GRE) sequence. The field-to-susceptibility inversion in QSM is known to be ill-posed and needs numerical stabilization through either regularization or data oversampling. The calculation of susceptibility through the multiple orientation sampling (COSMOS) method uses phase data acquired at three or more head orientations to achieve a well-conditioned field-to-susceptibility inversion and is often considered the gold standard for in vivo QSM. However, the conventional COSMOS approach, here named multistep COSMOS (MSCOSMOS), solves the dipole inversion from the local field derived from raw GRE phase through multiple steps of phase preprocessing. Error propagations between these consecutive phase processing steps can thus affect the final susceptibility quantification. On the other hand, recently proposed single-step QSM (SSQSM) methods aim to solve an integrated inversion from unprocessed or total phase to mitigate such error propagations but have been limited to single orientation QSM. This study therefore aimed to test the feasibility of using single-step COSMOS (SSCOSMOS) to jointly perform background field removal and dipole inversion with multiple orientation sampling, which could serve as a better standard for gauging SSQSM methods. We incorporated multiple spherical mean value (SMV) kernels of various radii with the dipole inversion in SSCOSMOS. QSM reconstructions with SSCOSMOS and MSCOSMOS were compared using both simulations with a numerical head phantom and in vivo human brain data. SSCOSMOS permitted integrated background removal and dipole inversion without the need to adjust any regularization parameters. In addition, with sufficiently large SMV kernels, SSCOSMOS performed consistently better than MSCOSMOS in all the tested error metrics in our simulations, giving better susceptibility quantification and smaller reconstruction error. Consistent tissue susceptibility values were obtained between SSCOSMOS and MSCOSMOS.

Asymmetric susceptibility tensor imaging

PURPOSE

To investigate the symmetry constraint in susceptibility tensor imaging.

THEORY

The linear relationship between the MRI frequency shift and the magnetic susceptibility tensor is derived without constraining the tensor to be symmetric. In the asymmetric case, the system matrix is shown to be maximally rank 6. Nonetheless, relaxing the symmetry constraint may still improve tensor estimation because noise and image artifacts do not necessarily follow the constraint.

METHODS

Gradient echo phase data are obtained from postmortem mouse brain and kidney samples. Both symmetric and asymmetric tensor reconstructions are applied to the data. The reconstructions are then used for susceptibility tensor imaging fiber tracking. Simulations with ground truth and at various noise levels are also performed. The reconstruction methods are compared qualitatively and quantitatively.

RESULTS

Compared to regularized and unregularized symmetric reconstructions, the asymmetric reconstruction shows reduced noise and streaking artifacts, better contrast, and more complete fiber tracking. In simulation, the asymmetric reconstruction achieves better mean squared error and better angular difference in the presence of noise. Decomposing the asymmetric tensor into its symmetric and antisymmetric components confirms that the underlying susceptibility tensor is symmetric and that the main sources of asymmetry are noise and streaking artifacts.

CONCLUSION

Whereas the susceptibility tensor is symmetric, asymmetric reconstruction is more effective in suppressing noise and artifacts, resulting in more accurate estimation of the susceptibility tensor.

Multi-compartment analysis of the complex gradient-echo signal quantifies myelin breakdown in premanifest Huntington's disease

White matter (WM) alterations have been identified as a relevant pathological feature of Huntington's disease (HD). Increasing evidence suggests that WM changes in this disorder are due to alterations in myelin-associated biological processes. Multi-compartmental analysis of the complex gradient-echo MRI signal evolution in WM has been shown to quantify myelin in vivo, therefore pointing to the potential of this technique for the study of WM myelin changes in health and disease. This study first characterized the reproducibility of metrics derived from the complex multi-echo gradient-recalled echo (mGRE) signal across the corpus callosum in healthy participants, finding highest reproducibility in the posterior callosal segment. Subsequently, the same analysis pipeline was applied in this callosal region in a sample of premanifest HD patients (n = 19) and age, sex and education matched healthy controls (n = 21). In particular, we focused on two myelin-associated derivatives: i. the myelin water signal fraction (fm), a parameter dependent on myelin content; and ii. The difference in frequency between myelin and intra-axonal water pools (Δω), a parameter dependent on the ratio between the inner and the outer axonal radii. fm was found to be lower in HD patients (β = -0.13, p = 0.03), while Δω did not show a group effect. Performance in tests of working memory, executive function, social cognition and movement was also assessed, and a greater age-related decline in executive function was detected in HD patients (β = -0.06, p = 0.006), replicating previous evidence of executive dysfunction in HD. Finally, the correlation between fm, executive function, and proximity to disease onset was explored in patients, and a positive correlation between executive function and fm was detected (r = 0.542; p = 0.02). This study emphasises the potential of complex mGRE signal analysis for aiding understanding of HD pathogenesis and progression. Moreover, expanding on evidence from pathology and animal studies, it provides novel in vivo evidence supporting myelin breakdown as an early feature of HD.

Multi-centre, multi-vendor reproducibility of 7T QSM and R2* in the human brain: Results from the UK7T study

Introduction

We present the reliability of ultra-high field T₂* MRI at 7T, as part of the UK7T Network's “Travelling Heads” study. T₂*-weighted MRI images can be processed to produce quantitative susceptibility maps (QSM) and R₂* maps. These reflect iron and myelin concentrations, which are altered in many pathophysiological processes. The relaxation parameters of human brain tissue are such that R₂* mapping and QSM show particularly strong gains in contrast-to-noise ratio at ultra-high field (7T) vs clinical field strengths (1.5–3T). We aimed to determine the inter-subject and inter-site reproducibility of QSM and R₂* mapping at 7T, in readiness for future multi-site clinical studies.

Methods

Ten healthy volunteers were scanned with harmonised single- and multi-echo T₂*-weighted gradient echo pulse sequences. Participants were scanned five times at each “home” site and once at each of four other sites. The five sites had 1× Philips, 2× Siemens Magnetom, and 2× Siemens Terra scanners. QSM and R₂* maps were computed with the Multi-Scale Dipole Inversion (MSDI) algorithm (https://github.com/fil-physics/Publication-Code). Results were assessed in relevant subcortical and cortical regions of interest (ROIs) defined manually or by the MNI152 standard space.

Results and Discussion

Mean susceptibility (χ) and R₂* values agreed broadly with literature values in all ROIs. The inter-site within-subject standard deviation was 0.001–0.005 ppm (χ) and 0.0005–0.001 ms⁻¹ (R₂*). For χ this is 2.1–4.8 fold better than 3T reports, and 1.1–3.4 fold better for R₂*. The median ICC from within- and cross-site R₂* data was 0.98 and 0.91, respectively. Multi-echo QSM had greater variability vs single-echo QSM especially in areas with large B₀ inhomogeneity such as the inferior frontal cortex. Across sites, R₂* values were more consistent than QSM in subcortical structures due to differences in B₀-shimming. On a between-subject level, our measured χ and R₂* cross-site variance is comparable to within-site variance in the literature, suggesting that it is reasonable to pool data across sites using our harmonised protocol.

Conclusion

The harmonized UK7T protocol and pipeline delivers on average a 3-fold improvement in the coefficient of reproducibility for QSM and R₂* at 7T compared to previous reports of multi-site reproducibility at 3T. These protocols are ready for use in multi-site clinical studies at 7T.

MRI phase offset correction method impacts quantitative susceptibility mapping

Individual channel ultra-high field (7T) phase images have to be phase offset corrected prior to the mapping of magnetic susceptibility of tissue. Whilst numerous methods have been proposed for gradient recalled echo MRI phase offset correction, it remains unclear how they affect quantitative magnetic susceptibility values derived from phase images. Methods already proposed either employ a single or multiple echo time MRI data. In terms of the latter, offsets can be derived using an ultra-short echo time acquisition, or by estimating the offset based on two echo points with the assumption of linear phase evolution with echo time. Our evaluation involved 32 channel multi-echo time 7T GRE (Gradient Recalled Echo) and ultra-short echo time PETRA (Pointwise Encoding Time Reduction with Radial Acquisition) MRI data collected for a susceptibility phantom and three human brains. The combined phase images generated using four established offset correction methods (two single and two multiple echo time) were analysed, followed by an assessment of quantitative susceptibility values obtained for a phantom and human brains. The effectiveness of each method in removing the offsets was shown to reduce with increased echo time, decreased signal intensity and reduced overlap in coil sensitivity profiles. Quantitative susceptibility values and how they change with echo time were found to be method specific. Phase offset correction methods based on single echo time data have a tendency to produce more accurate and less noisy quantitative susceptibility maps in comparison with methods employing multiple echo time data.

Serial assessment of iron in the motor cortex in limb-onset amyotrophic lateral sclerosis using quantitative susceptibility mapping

BACKGROUND

Dysregulation of iron in the cerebral motor areas has been hypothesized to occur in individuals with amyotrophic lateral sclerosis (ALS). There is still limited knowledge regarding iron dysregulation in the progression of ALS pathology. Our objectives were to use magnetic resonance based quantitative susceptibility mapping (QSM) to investigate the association between iron dysregulation in the motor cortex and clinical manifestations in patients with limb-onset ALS, and to examine changes in the iron concentration in the motor cortex in these patients over a 6-month period.

METHODS

Iron concentration was investigated using magnetic resonance based QSM in the primary motor cortex and the pre-motor area in 13 limb-onset ALS patients (including five lumbar onset, six cervical onset and two flail arm patients), and 11 age- and sex-matched control subjects. Nine ALS patients underwent follow-up scans at 6 months.

RESULTS

Significantly increased QSM values were observed in the left posterior primary motor area (P=0.02, Cohen's d =0.9) and right anterior primary motor area (P=0.02, Cohen's d =0.92) in the group of limb-onset ALS patients compared to that of control subjects. Increased QSM was observed in the primary motor and pre-motor area at baseline in patients with lumbar onset ALS patients, but not cervical limb-onset ALS patients, compared to control subjects. No significant change in QSM was observed at the 6-month follow-up scans in the ALS patients.

CONCLUSIONS

The findings suggest that iron dysregulation can be detected in the motor cortex in limb-onset ALS, which does not appreciably change over a further 6 months. Individuals with lumbar onset ALS appear to be more susceptible to motor cortex iron dysregulation compared to the individuals with cervical onset ALS. Importantly, this study highlights the potential use of QSM as a quantitative radiological indicator in early disease diagnosis in limb-onset ALS and its subtypes. Our serial scans results suggest a longer period than 6 months is needed to detect significant quantitative changes in the motor cortex.

Investigating the accuracy and precision of TE-dependent versus multi-echo QSM using Laplacian-based methods at 3 T

PURPOSE

Multi-echo gradient-recalled echo acquisitions for QSM enable optimizing the SNR for several tissue types through multi-echo (TE) combination or investigating temporal variations in the susceptibility (potentially reflecting tissue microstructure) by calculating one QSM image at each TE (TE-dependent QSM). In contrast with multi-echo QSM, applying Laplacian-based methods (LBMs) for phase unwrapping and background field removal to single TEs could introduce nonlinear temporal variations (independent of tissue microstructure) into the measured susceptibility. Here, we aimed to compare the effect of LBMs on the QSM susceptibilities in TE-dependent versus multi-echo QSM.

METHODS

TE-dependent recalled echo data simulated in a numerical head phantom and gradient-recalled echo images acquired at 3 T in 10 healthy volunteers. Several QSM pipelines were tested, including four distinct LBMs: sophisticated harmonic artifact reduction for phase data (SHARP), variable-radius sophisticated harmonic artifact reduction for phase data (V-SHARP), Laplacian boundary value background field removal (LBV), and one-step total generalized variation (TGV). Results from distinct pipelines were compared using visual inspection, summary statistics of susceptibility in deep gray matter/white matter/venous regions of interest, and, in the healthy volunteers, regional susceptibility bias analysis and nonparametric tests.

RESULTS

Multi-echo versus TE-dependent QSM had higher regional accuracy, especially in high-susceptibility regions and at shorter TEs. Everywhere except in the veins, a processing pipeline incorporating TGV provided the most temporally stable TE-dependent QSM results with an accuracy similar to multi-echo QSM.

CONCLUSIONS

For TE-dependent QSM, carefully choosing LBMs can minimize the introduction of LBM-related nonlinear temporal susceptibility variations.

Field strength influences on gradient recalled echo MRI signal compartment frequency shifts

Different trends of echo time dependent gradient recalled echo MRI signals in different brain regions have been attributed to signal compartments in image voxels. It remains unclear how variations in gradient recalled echo MRI signals change as a function of MRI field strength, and how data processing may impact signal compartment parameters. We used two popular quantitative susceptibility mapping methods of processing raw phase images (Laplacian and path-based unwrapping with V-SHARP) and expressed values in the form of induced frequency shifts (in Hz) in six specific brain regions at 3T and 7T. We found the frequency shift curves to vary with echo time, and a good overlap between 3T and 7T mean frequency shift curves was present. However, the amount of variation across participants was greater at 3T, and we were able to obtain better compartment model fits of the signal at 7T. We also found the temporal trends in the signal and compartment frequency shifts to change with the method used to process images. The inter-participant averaged trends were consistent between 3T and 7T for each quantitative susceptibility pipeline. However, signal compartment frequency shifts generated using different pipelines may not be comparable.

Quantitative Susceptibility Mapping: MRI at 7T versus 3T

BACKGROUND AND PURPOSE

Ultrahigh-field 7T promises more than doubling the signal-to-noise ratio (SNR) of 3T for magnetic resonance imaging (MRI), particularly for MRI of magnetic susceptibility effects induced by B₀ . Quantitative susceptibility mapping (QSM) is based on deconvolving the induced phase (or field) and would therefore benefit substantially from 7T. The purpose of this work was to compare QSM performance at 7T versus 3T in an intrascanner test-retest experiment with varying echo numbers (5 and 10 echoes).

METHODS

A prospective study in N = 10 healthy subjects was carried out at both 3T and 7T field strengths. Gradient echo data using 5 and 10 echoes were acquired twice in each subject. Test-retest reproducibility was assessed using Bland-Altman and regression analysis of region of interest measurements. Image quality was scored by an experienced neuroradiologist.

RESULTS

Intrascanner bias was below 3.6 parts-per-billion (ppb) with correlation R² > .85. Interscanner bias was below 10.9 ppb with correlation R² > .8. The image quality score for the 3T 10 echo protocol was not different from the 7T 5 echo protocol (P = .65).

CONCLUSION

Excellent image quality and good reproducibility was observed. 7T allows equivalent image quality of 3T in half of the scan time.

Quantitative Iron Neuroimaging Can Be Used to Assess the Effects of Minocycline in an Intracerebral Hemorrhage Minipig Model

Iron-mediated toxicity is a key factor causing brain injury after intracerebral hemorrhage (ICH). This study was performed to investigate the noninvasive neuroimaging method for quantifying brain iron content using a minipig ICH model and assess the effects of minocycline treatment on ICH-induced iron overload and brain injury. The minipig ICH model was established by injecting 2 ml of autologous blood into the right basal ganglia, which were then subjected to the treatments of minocycline and vehicle. Furthermore, the quantitative susceptibility mapping (QSM) was used to quantify iron content, and diffusion tensor imaging (DTI) was performed to evaluate white matter tract. Additionally, we also performed immunohistochemistry, Western blot, iron assay, Perl's staining, brain water content, and neurological score to evaluate the iron overload and brain injury. Interestingly, we found that the ICH-induced iron overload could be accurately quantified by the QSM. Moreover, the minocycline was quite beneficial for protecting brain injury by reducing the lesion volume and brain edema, preventing brain iron accumulation, downsizing ventricle enlargement, and alleviating white matter injury and neurological deficits. In summary, we suggest that the QSM be an accurate and noninvasive method for quantifying brain iron level, and the minocycline may be a promising therapeutic agent for patients with ICH.

Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths

Quantitative Susceptibility Mapping (QSM) provides a way of measuring iron concentration and myelination non-invasively and has the potential of becoming a tool of paramount importance in the study of a host of different pathologies. However, several experimental factors and the physical properties of magnetic susceptibility (χ) can impair the reliability of QSM, and it is therefore essential to assess QSM reproducibility for repeated acquisitions and different field strength. In particular, it has recently been demonstrated that QSM measurements strongly depend on echo time (TE): the same tissue, measured on the same scanner, exhibits different apparent frequency shifts depending on the TE used. This study aims to assess the influence of TE on intra-scanner and inter-scanner reproducibility of QSM, by using MRI systems operating at 3T and 7T. To maximize intra-scanner reproducibility it is necessary to match the TEs of the acquisition protocol, but the application of this rule leads to inconsistent QSM values across scanners operating at different static magnetic field. This study however demonstrates that, provided a careful choice of acquisition parameters, and in particular by using TEs at 3T that are approximately 2.6 times longer than those at 7T, highly reproducible whole-brain χ maps can be achieved also across different scanners, which renders QSM a suitable technique for longitudinal follow-up in clinical settings and in multi-center studies.

Appropriate echo time selection for quantitative susceptibility mapping

The purpose of our study was to clarify the dependence of quantitative susceptibility mapping (QSM) on echo time (TE). We constructed a phantom consisting of six tubes; three tubes were filled with different concentrations (0.5, 1.0, and 2.5 mM) of gadopentetate dimeglumine (Gd-DTPA), and three were filled with different concentrations (100, 200, and 350 mg/mL) of calcium hydroxyapatite. Real and imaginary images from multi-echo spoiled gradient-echo data (12 echoes) were acquired. We then used four datasets with three serial echoes. The QSM procedure consists of four steps: field map estimation, phase unwrapping, background removal, and dipole inversion. For each sample, we compared the measured mean susceptibility value with the theoretical susceptibility value and conducted a linear regression analysis. Accordingly, the relationship between the measured susceptibility and concentration of Gd-DTPA was shown to agree well with the theoretical values (TEs = 16.4, 20.8, and 25.2 ms; slope = 0.24, R² = 1.00). Furthermore, the relationship between the measured susceptibility and concentration of hydroxyapatite also showed good linearity (TEs = 16.4, 20.8, and 25.2 ms; slope = - 0.00121, R² = 1.00). In conclusion, the optimization of the TE in QSM makes it possible to obtain more detailed information regarding the susceptibility of biomaterials.

The effect of low resolution and coverage on the accuracy of susceptibility mapping

PURPOSE

Quantitative susceptibility mapping (QSM) has found increasing clinical applications. However, to reduce scan time, clinical acquisitions often use reduced resolution and coverage, particularly in the through-slice dimension. The effect of these factors on QSM has begun to be assessed using only balloon phantoms and downsampled brain images. Here, we investigate the effects (and their sources) of low resolution or coverage on QSM using both simulated and acquired images.

METHODS

Brain images were acquired at 1 mm isotropic resolution and full brain coverage, and low resolution (up to 6 mm slice thickness) or coverage (down to 20 mm) in 5 healthy volunteers. Images at reduced resolution or coverage were also simulated in these volunteers and in a new, anthropomorphic, numerical phantom. Mean susceptibilities in 5 brain regions, including white matter, were investigated over varying resolution and coverage.

RESULTS

The susceptibility map contrast decreased with increasing slice thickness and spacing, and with decreasing coverage below ~40 mm for 2 different QSM pipelines. Our simulations showed that calculated susceptibility values were erroneous at low resolution or very low coverage, because of insufficient sampling and overattenuation of the susceptibility-induced field perturbations. Susceptibility maps calculated from simulated and acquired images showed similar behavior.

CONCLUSIONS

Both low resolution and low coverage lead to loss of contrast and errors in susceptibility maps. The widespread clinical practice of using low resolution and coverage does not provide accurate susceptibility maps. Simulations in images of healthy volunteers and in a new, anthropomorphic numerical phantom were able to accurately model low-resolution and low-coverage acquisitions.

Imaging beta amyloid aggregation and iron accumulation in Alzheimer's disease using quantitative susceptibility mapping MRI

Beta amyloid is a protein fragment snipped from the amyloid precursor protein (APP). Aggregation of these peptides into amyloid plaques is one of the hallmarks of Alzheimer's disease. MR imaging of beta amyloid plaques has been attempted using various techniques, notably with T2* contrast. The non-invasive detectability of beta amyloid plaques in MR images has so far been largely attributed to focal iron deposition accompanying the plaques. It is believed that the T2* shortening effects of paramagnetic iron are the primary source of contrast between plaques and surrounding tissue. Amyloid plaque itself has been reported to induce no magnetic susceptibility effect. We hypothesized that aggregations of beta amyloid would increase electron density and induce notable changes in local susceptibility value, large enough to generate contrast relative to surrounding normal tissues that can be visualized by quantitative susceptibility mapping (QSM) MR imaging. To test this hypothesis, we first demonstrated in a phantom that beta amyloid is diamagnetic and can generate strong contrast on susceptibility maps. We then conducted experiments on a transgenic mouse model of Alzheimer's disease that is known to mimic the formation of human beta amyloid but without neurofibrillary tangles or neuronal death. Over a period of 18 months, we showed that QSM can be used to longitudinally monitor beta amyloid accumulation and accompanied iron deposition in vivo. Individual beta amyloid plaque can also be visualized ex vivo in high resolution susceptibility maps. Moreover, the measured negative susceptibility map and positive susceptibility map could provide histology-like image contrast for identifying deposition of beta amyloid plaques and iron. Finally, we demonstrated that the diamagnetic susceptibility of beta amyloid can also be observed in brain specimens of AD patients. The ability to assess beta amyloid aggregation non-invasively with QSM MR imaging may aid the diagnosis of Alzheimer's disease.

Frequency difference mapping applied to the corpus callosum at 7T

Purpose

Frequency difference mapping (FDM) is a phase processing technique which characterizes the nonlinear temporal evolution of the phase of gradient echo (GE) signals. Here, a novel FDM‐processing algorithm is introduced, which is shown to reveal information about white matter microstructure. Unlike some other phase‐processing techniques, the FDM algorithm presented here does not require the use of phase unwrapping or sophisticated image processing. It uses a series of scaled complex divisions to unwrap phase and remove background fields.

Methods

Ten healthy subjects underwent a series of single‐slice, sagittal multi‐echo GE scans at 7T with the slice positioned at the midline. Phase data were processed with the novel FDM algorithm, and the temporal evolution of the magnitude signal and frequency difference was examined in 5 regions of the corpus callosum (CC; genu, anterior body, middle body, posterior body, and splenium).

Results

Consistent frequency difference contrast relative to surrounding tissue was observed in all subjects in the CC and in other white matter regions where the nerve fibers run perpendicular to B0, such as the superior cerebellar peduncle. Examination of the frequency difference curves shows distinct variations over the CC, with the genu and splenium displaying larger frequency differences than the other regions (in addition to a faster decay of signal magnitude).

Conclusion

The novel FDM algorithm presented here yields images sensitive to tissue microstructure and microstructural differences over the CC in a simple manner, without the requirement for phase unwrapping or sophisticated image processing.

Quantitative susceptibility mapping (QSM) with an extended physical model for MRI frequency contrast in the brain: a proof-of-concept of quantitative susceptibility and residual (QUASAR) mapping

Quantitative susceptibility mapping (QSM) aims to calculate the tissue's magnetic susceptibility distribution from its perturbing effect on the MRI static main magnetic field. The method is increasingly being applied to study iron and myelin in clinical and preclinical settings. However, recent experimental and theoretical findings have challenged the fundamental theoretical assumptions that form the basis of current numerical implementations of QSM algorithms. The present work introduces a new class of susceptibility mapping algorithms, termed quantitative susceptibility and residual mapping (QUASAR), which takes into account frequency contributions not related to the spatial variation of bulk magnetic susceptibility in the Lorentz sphere model. We present a simple proof-of-concept QUASAR algorithm that, unlike most of the QSM algorithms currently used widely, results in an improved anatomical accuracy of the susceptibility distribution without any a priori assumptions about the susceptibility distribution during the field-to-source inversion. The algorithm was evaluated both in silico and in vivo in the preclinical setting. Our preliminary application of QUASAR in rodents provides the first in vivo evidence that the susceptibility-field model traditionally used in the QSM field cannot fully explain the frequency contrast in brain tissues. Only when an additional local frequency contribution is added to the physical model can the frequency contrast in the brain be related properly to the underlying anatomy.

A robust multi-scale approach to quantitative susceptibility mapping

Quantitative Susceptibility Mapping (QSM), best known as a surrogate for tissue iron content, is becoming a highly relevant MRI contrast for monitoring cellular and vascular status in aging, addiction, traumatic brain injury and, in general, a wide range of neurological disorders. In this study we present a new Bayesian QSM algorithm, named Multi-Scale Dipole Inversion (MSDI), which builds on the nonlinear Morphology-Enabled Dipole Inversion (nMEDI) framework, incorporating three additional features: (i) improved implementation of Laplace's equation to reduce the influence of background fields through variable harmonic filtering and subsequent deconvolution, (ii) improved error control through dynamic phase-reliability compensation across spatial scales, and (iii) scalewise use of the morphological prior. More generally, this new pre-conditioned QSM formalism aims to reduce the impact of dipole-incompatible fields and measurement errors such as flow effects, poor signal-to-noise ratio or other data inconsistencies that can lead to streaking and shadowing artefacts. In terms of performance, MSDI is the first algorithm to rank in the top-10 for all metrics evaluated in the 2016 QSM Reconstruction Challenge. It also demonstrated lower variance than nMEDI and more stable behaviour in scan-rescan reproducibility experiments for different MRI acquisitions at 3 and 7 Tesla. In the present work, we also explored new forms of susceptibility MRI contrast making explicit use of the differential information across spatial scales. Specifically, we show MSDI-derived examples of: (i) enhanced anatomical detail with susceptibility inversions from short-range dipole fields (hereby referred to as High-Pass Susceptibility Mapping or HPSM), (ii) high specificity to venous-blood susceptibilities for highly regularised HPSM (making a case for MSDI-based Venography or VenoMSDI), (iii) improved tissue specificity (and possibly statistical conditioning) for Macroscopic-Vessel Suppressed Susceptibility Mapping (MVSSM), and (iv) high spatial specificity and definition for HPSM-based Susceptibility-Weighted Imaging (HPSM-SWI) and related intensity projections.

Neonate and infant brain development from birth to 2 years assessed using MRI-based quantitative susceptibility mapping

The human brain rapidly develops during the first two years following birth. Quantitative susceptibility mapping (QSM) provides information of iron and myelin variations. It is considered to be a valuable tool for studying brain development in early life. In the present work, QSM is performed on neonates, 1-year and 2-year old infants, as well as a group of adults for the purpose of reference. Age-specific templates representing common brain structures are built for each age group. The neonate and infant QSM templates have shown some unique findings compared to conventional T1w and T2w imaging techniques. The contrast between the gray and white matters on the QSM images did not change through brain development from neonate to adult. A linear correlation was found between brain myelination determined in this study and the microscopic myelin degree determined by a previous autopsy study. Also, the magnetic susceptibility values of the cerebral spinal fluid (CSF) exhibit a gradually decreasing trend from birth to 2 years old and to adulthood. The findings suggest that the macromolecular content, myelin, and iron may play the most important contributing factors for the magnetic susceptibility of neonate and infant brain. QSM can be a powerful means to study early brain development and related pathologies that involve alterations in macromolecular content, iron, or brain myelination.