Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications

Alterations in magnetic susceptibility correlate with higher cerebral blood flow in the right amygdala of patients with major depressive disorder

BACKGROUND

The amygdala plays a crucial role in emotion processing and is a key target for understanding the mechanisms underlying major depressive disorder (MDD). This study aimed to investigate the magnetic susceptibility of the amygdala in MDD and examine its association with structural and cerebral blood flow (CBF) changes.

METHODS

A total of 158 individuals were included in the study, comprising 86 patients with MDD and 72 healthy controls. Depression severity was assessed using Hamilton Depression Rating Scale. Quantitative susceptibility mapping (QSM), T1-weighted, and arterial spin labeling scans were conducted to measure amygdala magnetic susceptibility, volume, and CBF, respectively. Group differences were compared, and associations between susceptibility, volume, and CBF were examined.

RESULTS

The median susceptibility of the amygdala was significantly higher in MDD patients than in controls (all p < 0.01). In the MDD group, increased QSM value in the right amygdala was associated with higher CBF (r = 0.28, p = 0.01), whereas no significant correlation was found between QSM value and volume (p = 0.76). Increased QSM value in the right amygdala was associated with worse depressed mood (r = 0.30, p < 0.01).

LIMITATION

Retrospective cross-sectional study conducted at a single center.

CONCLUSION

The magnetic susceptibility of the amygdala was higher in MDD patients with than in controls. QSM changes in the right amygdala correlated with increased CBF and worse depressed mood, indicating both microstructural and functional alterations. Our results encourage further use of the QSM technique in the elucidation of MDD pathophysiology.

MR perfusion source mapping depicts venous territories and reveals perfusion modulation during neural activation

The cerebral venous system plays a crucial role in neurological and vascular conditions, yet its hemodynamics remain underexplored due to its complexity and variability across individuals. To address this, we develop a venous perfusion source mapping method using Displacement Spectrum MRI, a non-contrast technique that leverages blood water as an endogenous tracer. Our technique encodes spatial information into the magnetization of blood water spins during tagging and detects it once the tagged blood reaches the brain's surface, where the signal-to-noise ratio is 3-4 times higher. We resolve the sources of blood entering the imaging slice across short (10 ms) to long (3 s) evolution times, effectively capturing perfusion sources in reverse. This approach enables the measurement of slow venous blood flow, including potential contributions from capillary beds and surrounding tissue. We demonstrate perfusion source mapping in the superior cerebral veins, verify its sensitivity to global perfusion modulation induced by caffeine, and establish its specificity by showing repeatable local perfusion modulation during neural activation. From all blood within the imaging slice, our method localizes the portion originating from an activated region upstream.

Combined MR Volumetry and T2* Relaxometry Reveals the Olfactory System as an Iron-Dependent Structure Affected by Radiation

Background/Objectives: Radiation therapy can often lead to structural and functional changes in the brain resulting in radiation-induced brain injury. This study investigates the MRI-detectable effects of whole-brain irradiation across all neuroanatomical structures in adult mice, with a specific focus on T2* MRI measurements, to evaluate regions that may be particularly sensitive to iron accumulation. Methods: One year following irradiation or sham treatment, mice were imaged with a 7T MRI to evaluate changes in regional volume and T2* relaxation times across more than 652 neuroanatomical using the DSURQE mouse brain atlas. Results: Statistical analysis identified 301 altered regions with respect to regional volume and 85 regions with respect to T2* relaxation showing significant differences relative to the control group (p < 0.05). Further data refinement, including the consolidation of redundant, bi-lateral structures revealed 18 subregions with significant changes in both volume and T2*. The data refinement revealed that the most represented system was the olfactory system (8/18 regions, 44%). The olfactory regions also showed the most pronounced changes and greatest correlation between the two metrics. Conclusions: These findings are suggestive that ionizing radiation may cause a pronounced disruption in the olfactory system that coincides with potential iron accumulation.

Effect of moderate hyperbilirubinemia on an infant's brain: a quantitative susceptibility mapping and 1H-MRS study

Objective

The effects of moderate neonatal hyperbilirubinemia (NHB) remain unknown. The aim of this work was to investigate whether moderate NHB has an impact on an infant's brain and explore the relationship between brain magnetic susceptibility, brain metabolites, and biochemical tests in moderate NHB using quantitative susceptibility mapping (QSM) and magnetic resonance spectroscopy (MRS).

Materials and methods

In total, 28 term babies with moderate levels of blood bilirubin were enrolled in the NHB group, and 16 term infants were enrolled in the control group. All the patients underwent biochemical tests, 1H-MRS, and QSM examinations. Biochemical test results [e.g., direct bilirubin (DBiL)], metabolite ratios [e.g., glycerophosphocholine (GPC)], and susceptibility values were collected. The Mann-Whitney U-test was used to assess the differences between the NHB and control groups. Partial least square correlation (PLSC) analyses were performed to analyze the correlations between the biochemical results and the metabolite ratios and susceptibility values.

Results

The Mann-Whitney U-test showed that significant differences were observed in the biochemical results, susceptibility values of the left putamen, and absolute concentrations of GPC between the NHB group and the controls. No significant differences were found in the metabolite ratios between the two groups. The PLSC analysis demonstrated that the ratios of myo-inositol (Ins), N-acetylaspartate (NAA), and GPC relative to creatine and phosphocreatine had a robust correlation with DBiL in the NHB group. Furthermore, increasing susceptibility values of putamen, globus pallidus, caudate nucleus, and thalamus had a moderate correlation with decreasing DBiL and increasing TSH concentrations in the NHB group.

Conclusion

This study demonstrated that moderate hyperbilirubinemia could induce metabolic and susceptibility changes in an infant's brain (e.g., decreased susceptibility values and metabolite values) and these changes have a correlation with biochemical test results.

Quantitative susceptibility mapping via deep neural networks with iterative reverse concatenations and recurrent modules

BACKGROUND

Quantitative susceptibility mapping (QSM) is a post-processing magnetic resonance imaging (MRI) technique that extracts the distribution of tissue susceptibilities and holds significant promise in the study of neurological diseases. However, the ill-conditioned nature of dipole inversion often results in noise and artifacts during QSM reconstruction from the tissue field. Deep learning methods have shown great potential in addressing these issues; however, most existing approaches rely on basic U-net structures, leading to limited performances and reconstruction artifacts sometimes.

PURPOSE

This study aims to develop a novel deep learning-based method, IR2QSM, for improving QSM reconstruction accuracy while mitigating noise and artifacts by leveraging a unique network architecture that enhances latent feature utilization.

METHODS

IR2QSM, an advanced U-net architecture featuring four iterations of reverse concatenations and middle recurrent modules, was proposed to optimize feature fusion and improve QSM accuracy, and comparative experiments based on both simulated and in vivo datasets were carried out to compare IR2QSM with two traditional iterative methods (iLSQR, MEDI) and four recently proposed deep learning methods (U-net, xQSM, LPCNN, and MoDL-QSM).

RESULTS

In this work, IR2QSM outperformed all other methods in reducing artifacts and noise in QSM images. It achieved on average the lowest XSIM (84.81%) in simulations, showing improvements of 12.80%, 12.68%, 18.66%, 10.49%, 25.57%, and 19.78% over iLSQR, MEDI, U-net, xQSM, LPCNN, and MoDL-QSM, respectively, and yielded results with the least artifacts on the in vivo data and present the most visually appealing results. In the meantime, it successfully alleviated the over-smoothing and susceptibility underestimation in LPCNN results.

CONCLUSION

Overall, the proposed IR2QSM showed superior QSM results compared to iterative and deep learning-based methods, offering a more accurate QSM solution for clinical applications.

Characterizing positive and negative quantitative susceptibility values in the cortex following mild traumatic brain injury: a depth- and curvature-based study

Evidence has linked head trauma to increased risk factors for neuropathology, including mechanical deformation of the sulcal fundus and, later, perivascular accumulation of hyperphosphorylated tau adjacent to these spaces related to chronic traumatic encephalopathy. However, little is known about microstructural abnormalities and cellular dyshomeostasis in acute mild traumatic brain injury in humans, particularly in the cortex. To address this gap, we designed the first architectonically motivated quantitative susceptibility mapping study to assess regional patterns of net positive (iron-related) and net negative (myelin-, calcium-, and protein-related) magnetic susceptibility across 34 cortical regions of interest following mild traumatic brain injury. Bilateral, between-group analyses sensitive to cortical depth and curvature were conducted between 25 males with acute (<14 d) sports-related mild traumatic brain injury and 25 age-matched male controls. Results suggest a trauma-induced increase in net positive susceptibility focal to superficial, perivascular-adjacent spaces in the parahippocampal sulcus. Decreases in net negative susceptibility values in distinct voxel populations within the same region indicate a potential dual pathology of neural substrates. These mild traumatic brain injury-related patterns were distinct from age-related processes revealed by correlation analyses. Our findings suggest depth- and curvature-specific deposition of biological substrates in cortical tissue convergent with features of misfolded proteins in trauma-related neurodegeneration.

Conventional and Advanced Magnetic Resonance Imaging Biomarkers of Multiple Sclerosis in the Brain

Multiple sclerosis (MS) is a heterogeneous disease, and each MS patient exhibits different clinical symptoms that are reflected in their magnetic resonance imaging (MRI) results. Each MS lesion should be interpreted carefully and evaluated in conjunction with a clinical examination. MRI plays a major role in evaluating how MS lesions are aggregated in the central nervous system and how they change over time. There are several conventional MRI biomarkers of MS that could be utilized to evaluate each MS phenotype. MRI is useful for clinical decisions, aiding in the determination of disease-modifying treatment or disease prognosis. Despite its higher sensitivity, MRI provides low specificity due to the heterogeneity of MS lesions. However, advanced MRI biomarkers show promise in terms of defining MS lesions, as each imaging biomarker correlates differently with the clinical scenario of each MS phenotype. The aim of this review is to summarise the current state of MRI biomarkers for MS in the brain and how they relate to neurological disabilities.

MR Imaging Techniques for Microenvironment Mapping of the Glioma Tumors: A Systematic Review

RATIONALE AND OBJECTIVES

The tumor microenvironment (TME) is a critical regulator of cancer progression, metastasis, and treatment response. Currently, various imaging approaches exist to assess the pathophysiological features of the TME. This systematic review provides an overview of magnetic resonance imaging (MRI) methods used in clinical practice to characterize the pathophysiological features of the gliomas TME.

METHODS

This review involved a systematic comprehensive search of original open-access articles reporting the clinical use of MR imaging in glioma patients of all ages in the PubMed, Scopus, and Web of Science databases between January 2010 and December 2023. We restricted our research to papers published in the English language.

RESULTS

A total of 1137 studies were preliminarily identified through electronic database searches. After duplicate studies were removed, 44 studies met the eligibility criteria. The glioma TME was accompanied by alterations in metabolism, pH, vascularity, oxygenation, and extracellular matrix components, including tumor-associated macrophages, and sodium concentration.

CONCLUSION

Multiparametric MRI is capable of noninvasively assessing the pathophysiological features and tumor-supportive niches of the TME, which is in line with its application in personalized medicine.

Relationship between cognitive impairment and hippocampal iron overload: A quantitative susceptibility mapping study of a rat model

BACKGROUND

The aim of this study was to establish an iron overload rat model to simulate the elevated iron levels in patients with thalassemia and to investigate the potential association between hippocampal iron deposition and cognition.

METHODS

Two groups of iron overloaded rats and one group of control rats were used for this study. The Morris water maze (MWM) was used to test spatial reference memory indicated by escape latency time and number of MWM platform crossings. The magnetic susceptibility value of the hippocampal tissue, a measure of iron deposition, was assessed by quantitative susceptibility mapping (QSM) and was correlated with spatial reference memory performance. The iron content in hippocampal tissue sections of the rats were assessed using diaminobenzidine (DAB)-enhanced Perl's Prussian blue (PPB) staining.

RESULTS

The rat groups with iron overload including the Group H and Group L had higher hippocampal magnetic susceptibility values than the control rat group, i.e., Group D. In addition, the iron overloaded groups had longer MWM escape latency than the control group, and reduced number of MWM platform crossings. There was a positive correlation between the mean escape latency and the mean hippocampal magnetic susceptibility value, a negative correlation between the number of platform crossings and the mean hippocampal magnetic susceptibility value, and a negative correlation between the number of platform crossings and the latent escape time in Group H and Group L.

CONCLUSION

This rat model simulating iron overload in thalassemia showed hippocampal iron overload being associated with impairment of spatial reference memory. QSM could be used to quantify brain iron overload in vivo, highlighting its potential clinical application for assessing cognitive impairment in patients with thalassemia.

Diamagnetic Signature of Beta-Amyloid (Aβ) and Tau (τ) Tangle Pathology in Alzheimer's Disease: A Review

The complex interplay between diamagnetic and paramagnetic substances within the brain, particularly in the context of Alzheimer's disease (AD), offers a rich landscape for investigation using advanced quantitative neuroimaging techniques. Although conventional approaches have focused on the paramagnetic properties of iron, emerging and promising research has highlighted the significance of diamagnetic signatures associated with beta-amyloid (Aβ) plaques and Tau (τ) protein aggregates. Quantitative susceptibility mapping (QSM) is a complex post-processing technique that visualizes and characterizes these subtle alterations in brain border tissue composition, such as the gray-white matter interface. Through voxel-wise separation of the contributions of diamagnetic and paramagnetic sources, QSM enabled the identification and quantification of Aβ and τ aggregates, even in the presence of iron. However, several challenges remain in utilizing diamagnetic signatures of Aβ and τ for clinical applications. These include the relatively small magnitude of the diamagnetic signal compared to paramagnetic iron, the need for high-resolution imaging and sophisticated analysis techniques, and the standardization of QSM acquisition and analysis protocols. Further research is necessary to refine QSM techniques, optimize acquisition parameters, and develop robust analysis pipelines to improve the sensitivity and specificity of detecting the diamagnetic nature of Aβ and τ aggregates. As our understanding of the diamagnetic properties of Aβ and τ continues to evolve, QSM is expected to play a pivotal role in advancing our knowledge of AD and other neurodegenerative diseases.

Thalamic Magnetic Susceptibility (χ) Alterations in Neurodegenerative Diseases: A Systematic Review and Meta-Analysis of Quantitative Susceptibility Mapping Studies

BACKGROUND

Quantitative Susceptibility Mapping (QSM) provides a non-invasive post-processing method to investigate alterations in magnetic susceptibility (χ), reflecting iron content within brain regions implicated in neurodegenerative diseases (NDDs).

PURPOSE

To investigate alterations in thalamic χ in patients with NDDs using QSM.

STUDY TYPE

Systematic review and meta-analysis.

POPULATION

A total of 696 patients with NDDs and 760 healthy controls (HCs) were included in 27 studies.

FIELD STRENGTH/SEQUENCE

Three-dimensional multi-echo gradient echo sequence for QSM at mostly 3 Tesla.

ASSESSMENT

Studies reporting QSM values in the thalamus of patients with NDDs were included. Following PRISMA 2020, we searched the four major databases including PubMed, Scopus, Web of Science, and Embase for peer-reviewed studies published until October 2024.

STATISTICAL TESTS

Meta-analysis was conducted using a random-effects model to calculate the standardized mean difference (SMD) between patients and HCs.

RESULTS

The pooled SMD indicated a significant increase in thalamic χ in NDDs compared to HCs (SMD = 0.42, 95% CI: 0.05-0.79; k = 27). Notably, amyotrophic lateral sclerosis patients showed a significant increase in thalamic χ (1.09, 95% CI: 0.65-1.53, k = 2) compared to HCs. Subgroup analyses revealed significant χ alterations in younger patients (mean age ≤ 62 years; 0.56, 95% CI: 0.10-1.02, k = 11) and studies using greater coil channels (coil channels > 16; 0.64, 95% CI: 0.28-1.00, k = 9). Publication bias was not detected and quality assessment indicated that studies with a lower risk of bias presented more reliable findings (0.75, 95% CI: 0.32-1.18, k = 9). Disease type was the primary driver of heterogeneity, while other factors, such as coil type and geographic location, also contributed to variability.

DATA CONCLUSION

Our findings support the potential of QSM for investigating thalamic involvement in NDDs. Future research should focus on disease-specific patterns, thalamic-specific nucleus analysis, and temporal evolution.

PLAIN LANGUAGE SUMMARY

Our research investigated changes in iron levels within the thalamus, a brain region crucial for motor and cognitive functions, in patients with various neurodegenerative diseases (NDDs). The study utilized a specific magnetic resonance imaging technique called Quantitative Susceptibility Mapping (QSM) to measure iron content. It identified a significant increase in thalamic iron levels in NDD patients compared to healthy individuals. This increase was particularly prominent in patients with Amyotrophic Lateral Sclerosis, younger individuals, and studies employing advanced imaging equipment.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Spatiotemporal neurodegeneration of the substantia nigra and its connecting cortex and subcortex in Parkinson's disease

BACKGROUND AND PURPOSE

Neurodegeneration is uneven in Parkinson's disease (PD). This study aimed to investigate spatiotemporal neurodegeneration in functional subregions of the substantia nigra (SN) and their connected cortex and subcortex in people with PD.

METHODS

A total of 120 patients with early-stage PD, 45 patients with advanced PD, and 120 healthy controls (HCs) were enrolled. The SN, cortex, and subcortex were divided into sensorimotor, associative, and limbic regions, respectively. Iron deposition in the SN was assessed by quantitative susceptibility mapping (QSM). Cortex and subcortex volumes were calculated based on T1-weighted imaging. Region of interest (ROI) analysis and voxel-based analysis (VBA) were performed to explore spatiotemporal neurodegeneration in patients with PD. p values were corrected for false discovery rate.

RESULTS

In the ROI analysis, the QSM values for the limbic (p = 0.018) and sensorimotor SN subregions (p = 0.018) were higher in PD patients than in HCs, but were not higher in the associative SN subregion (p = 0.295). In VBA, all SN functional subregions had clusters with higher QSM values in PD patients than in HCs (p < 0.001). The limbic SN subregion was the only one in which iron deposition increased from early-stage to advanced PD (p = 0.023). The QSM values of VBA_limbic, sensorimotor, and associative SN had subregion-specific correlations with disease severity (p = 0.001 for the limbic and sensorimotor subregions, p = 0.003 for the associative subregion), motor symptoms (p = 0.057 for the limbic and sensorimotor subregion), and depression scores (p = 0.036 for the limbic subregion).

CONCLUSION

Iron deposition in SN functional subregions and atrophy of cortical and subcortical structures connected with the SN showed spatiotemporal selectivity. These findings reveal the potential pathogenesis of clinical heterogeneity in PD.

PET, SPECT, and MRI imaging for evaluation of Parkinson's disease

This review assesses the primary neuroimaging techniques used to evaluate Parkinson's disease (PD) - a neurological condition characterized by gradual dopamine-producing nerve cell degeneration. The neuroimaging techniques explored include positron emission tomography (PET), single-photon emission computed tomography (SPECT), and magnetic resonance imaging (MRI). These modalities offer varying degrees of insights into PD pathophysiology, diagnostic accuracy, specificity by way of exclusion of other Parkinsonian syndromes, and monitoring of disease progression. Neuroimaging is thus crucial for diagnosing and managing PD, with integrated multimodal approaches and novel techniques further enhancing early detection and treatment evaluation.

Mineralized tissue visualization with MRI: Practical insights and recommendations for optimized clinical applications

Magnetic resonance imaging (MRI) techniques that enhance the visualization of mineralized tissues (hereafter referred to as MT-MRI) are increasingly being incorporated into clinical practice, particularly in musculoskeletal imaging. These techniques aim to mimic the contrast provided by computed tomography (CT), while taking advantage of MRI's superior soft tissue contrast and lack of ionizing radiation. However, the variety of MT-MRI techniques, including three-dimensional gradient-echo, ultra-short and zero-echo time, susceptibility-weighted imaging, and artificial intelligence-generated synthetic CT, each offer different technical characteristics, advantages, and limitations. Understanding these differences is critical to optimizing clinical application. This review provides a comprehensive overview of the most commonly used MT-MRI techniques, categorizing them based on their technical principles and clinical utility. The advantages and disadvantages of each approach, including their performance in bone morphology assessment, fracture detection, arthropathy-related findings, and soft tissue calcification evaluation are discussed. Additionally, technical limitations and artifacts that may affect image quality and diagnostic accuracy, such as susceptibility effects, signal-to-noise ratio issues, and motion artifacts are addressed. Despite promising developments, MT-MRI remains inferior to conventional CT for evaluating subtle bone abnormalities and soft tissue calcification due to spatial resolution limitations. However, advances in deep learning and hardware innovations, such as artificial intelligence-generated synthetic CT and ultrahigh-field MRI, may bridge this gap in the future.

ProxiMO: Proximal Multi-operator Networks for Quantitative Susceptibility Mapping

Quantitative Susceptibility Mapping (QSM) is a technique that derives tissue magnetic susceptibility distributions from phase measurements obtained through Magnetic Resonance (MR) imaging. This involves solving an ill-posed dipole inversion problem, however, and thus time-consuming and cumbersome data acquisition from several distinct head orientations becomes necessary to obtain an accurate solution. Most recent (supervised) deep learning methods for single-phase QSM require training data obtained via multiple orientations. In this work, we present an alternative unsupervised learning approach that can efficiently train on single-orientation measurement data alone, named ProxiMO (Proximal Multi-Operator), combining Learned Proximal Convolutional Neural Networks (LP-CNN) with multi-operator imaging (MOI). This integration enables LP-CNN training for QSM on single-phase data without ground truth reconstructions. We further introduce a semi-supervised variant, which further boosts the reconstruction performance, compared to the traditional supervised fashions. Extensive experiments on multicenter datasets illustrate the advantage of unsupervised training and the superiority of the proposed approach for QSM reconstruction. Code is available at https://github.com/shmuelor/ProxiMO.

Leveraging ultra-high field (7T) MRI in psychiatric research

Non-invasive brain imaging has played a critical role in establishing our understanding of the neural properties that contribute to the emergence of psychiatric disorders. However, characterizing core neurobiological mechanisms of psychiatric symptomatology requires greater structural, functional, and neurochemical specificity than is typically obtainable with standard field strength MRI acquisitions (e.g., 3T). Ultra-high field (UHF) imaging at 7 Tesla (7T) provides the opportunity to identify neurobiological systems that confer risk, determine etiology, and characterize disease progression and treatment outcomes of major mental illnesses. Increases in scanner availability, regulatory approval, and sequence availability have made the application of UHF to clinical cohorts more feasible than ever before, yet the application of UHF approaches to the study of mental health remains nascent. In this technical review, we describe core neuroimaging methodologies which benefit from UHF acquisition, including high resolution structural and functional imaging, single (1H) and multi-nuclear (e.g., 31P) MR spectroscopy, and quantitative MR techniques for assessing brain tissue iron and myelin. We discuss advantages provided by 7T MRI, including higher signal- and contrast-to-noise ratio, enhanced spatial resolution, increased test-retest reliability, and molecular and neurochemical specificity, and how these have begun to uncover mechanisms of psychiatric disorders. Finally, we consider current limitations of UHF in its application to clinical cohorts, and point to ongoing work that aims to overcome technical hurdles through the continued development of UHF hardware, software, and protocols.

Advancing the Collaboration Between Imaging and Radiation Oncology

The fusion of cutting-edge imaging technologies with radiation therapy (RT) has catalyzed transformative breakthroughs in cancer treatment in recent decades. It is critical for us to review our achievements and preview into the next phase for future synergy between imaging and RT. This paper serves as a review and preview for fostering collaboration between these two domains in the forthcoming decade. Firstly, it delineates ten prospective directions ranging from technological innovations to leveraging imaging data in RT planning, execution, and preclinical research. Secondly, it presents major directions for infrastructure and team development in facilitating interdisciplinary synergy and clinical translation. We envision a future where seamless integration of imaging technologies into RT will not only meet the demands of RT but also unlock novel functionalities, enhancing accuracy, efficiency, safety, and ultimately, the standard of care for patients worldwide.

Quantitative Susceptibility Mapping Values Quantification in Deep Gray Matter Structures for Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-Analysis

BACKGROUND/OBJECTIVES

This systematic review and meta-analysis aimed to investigate the role of magnetic susceptibility (χ) in deep gray matter (DGM) structures, including the putamen (PUT), globus pallidus (GP), caudate nucleus (CN), and thalamus, in the most common types of multiple sclerosis (MS) and relapsing-remitting MS (RRMS), using quantitative susceptibility mapping (QSM).

METHODS

The literature was systematically reviewed up to November 2023, adhering to PRISMA guidelines. This study was conducted using a random-effects model to calculate the standardized mean difference (SMD) in QSM values between patients with RRMS and healthy controls (HCs). Publication bias and risk of bias were also assessed.

RESULTS

Nine studies involving 1074 RRMS patients with RRMS and 640 HCs were included in the meta-analysis. The results showed significantly higher QSM (χ) values in the PUT (SMD = 0.40, 95% confidence interval [CI] = 0.22-0.59, p = .000), GP (SMD = 0.60, 95% CI = 0.50-0.70, p = .00), and CN (SMD = 0.40, 95% CI = 0.15-0.66, p = .005) of RRMS patients compared to HCs. However, there were no significant differences in the QSM values in the thalamus between patients with RRMS and HCs (SMD = -0.33, 95% CI -0.67-0.01, p = .026). Age- and sex-based subgroup analysis demonstrated that younger patients (< 40 years) in the PUT, GP, and CN groups and larger male populations (> 25%) in the PUT and GP groups had more significant χ. Interestingly, thalamic QSM values were found to decrease in RRMS patients over 40 years of age and in higher male populations. Sex-based subgroup analysis indicated higher iron levels in the PUT and GP of RRMS patients regardless of sex. QSM values were higher in certain brain regions (PUT, GP, and CN) during the early stages (disease duration < 9.6 years) of RRMS, but lower in the thalamus during the later stages (disease duration > 9.6 years) than HCs.

DISCUSSION/CONCLUSION

QSM may serve as a biomarker for understanding χ value alterations such as iron dysregulation and its contribution to neurodegeneration in RRMS, especially in the basal ganglia nuclei including PUT, GP, and CN.

Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping

BACKGROUND

Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensitive sequences in MRI. Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI.

PURPOSE

To automatically detect CMB on QSM, we proposed a two-stage deep learning pipeline.

STUDY TYPE

Retrospective.

SUBJECTS

A total number of 1843 CMBs from 393 patients (69 ± 12) with cerebral small vessel disease were included in this study. Seventy-eight subjects (70 ± 13) were used as external testing.

FIELD STRENGTH/SEQUENCE

3 T/QSM.

ASSESSMENT

The proposed pipeline consisted of two stages. In stage I, 2.5D fast radial symmetry transform (FRST) algorithm along with a one-layer convolutional network was used to identify CMB candidate regions in QSM images. In stage II, the V-Net was utilized to reduce false positives. The V-Net was trained using CMB and non CMB labels, which allowed for high-level feature extraction and differentiation between CMBs and CMB mimics like vessels. The location of CMB was assessed according to the microbleeds anatomical rating scale (MARS) system.

STATISTICAL TESTS

The sensitivity and positive predicative value (PPV) were reported to evaluate the performance of the model. The number of false positive per subject was presented.

RESULTS

Our pipeline demonstrated high sensitivities of up to 94.9% at stage I and 93.5% at stage II. The overall sensitivity was 88.9%, and the false positive rate per subject was 2.87. With respect to MARS, sensitivities of above 85% were observed for nine different brain regions.

DATA CONCLUSION

We have presented a deep learning pipeline for detecting CMB in the CSVD cohort, along with a semi-automated MARS scoring system using the proposed method. Our results demonstrated the successful application of deep learning for CMB detection on QSM and outperformed previous handcrafted methods.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability. This work proposes a hybrid two-step reconstruction approach to improve deep learning based QSM reconstruction. The susceptibility map prediction obtained from the deep learning methods has been refined in the framework developed in this work to ensure consistency with the measured local field. The developed method was validated on existing deep learning and model-based deep learning methods for susceptibility mapping of the brain. The developed method resulted in improved reconstruction for MRI volumes obtained with different acquisition settings, including deep learning models trained on constrained (limited) data settings.

Advanced Brain Imaging in Central Nervous System Demyelinating Diseases

In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.

Clinical and neuroimaging characteristics of primary lateral sclerosis with overlapping features of progressive supranuclear palsy

BACKGROUND AND PURPOSE

Primary lateral sclerosis (PLS) is a neurodegenerative disorder that primarily affects the central motor system. In rare cases, clinical features of PLS may overlap with those of progressive supranuclear palsy (PSP). We investigate neuroimaging features that can help distinguish PLS with overlapping features of PSP (PLS-PSP) from PSP.

METHODS

Six patients with PLS-PSP were enrolled between 2019 and 2023. We compared their clinical and neuroimaging characteristics with 18 PSP-Richardson syndrome (PSP-RS) patients and 20 healthy controls. Magnetic resonance imaging, 18F-flortaucipir positron emission tomography (PET), quantitative susceptibility mapping, and diffusion tensor imaging tractography (DTI) were performed to evaluate eight brain regions of interest. Area under the receiver operating characteristic curve (AUROC) was calculated.

RESULTS

Five of the six PLS-PSP patients (83.3%) were male. Median age at symptom onset was 61.5 (52.5-63) years, and all had mixed features of PLS and PSP. Volumes of the pallidum, caudate, midbrain, and cerebellar dentate were smaller in PSP-RS than PLS-PSP, providing good discrimination (AUROC = 0.75 for all). The susceptibilities in pallidum, midbrain, and cerebellar dentate were greater in PSP-RS compared to PLS-PSP, providing excellent discrimination (AUROC ≥ 0.90 for all). On DTI, fractional anisotropy (FA) in the posterior limb of the internal capsule from the corticospinal tract was lower in PLS-PSP compared to PSP-RS (AUROC = 0.86), but FA in the superior cerebellar peduncle was lower in PSP-RS (AUROC = 0.95). Pallidum flortaucipir PET uptake was greater in PSP-RS compared to PLS-PSP (AUROC = 0.74).

CONCLUSIONS

Regional brain volume, tractography, and magnetic susceptibility, but not tau-PET, are useful in distinguishing PLS-PSP from PSP.

Arterial spin labelling magnetic resonance imaging and perfusion patterns in neurocognitive and other mental disorders: a systematic review

We reviewed 33 original research studies assessing brain perfusion, using consensus guidelines from a "white paper" issued by the International Society for Magnetic Resonance in Medicine Perfusion Study Group and the European Cooperation in Science and Technology Action BM1103 ("Arterial Spin Labelling Initiative in Dementia"; https://www.cost.eu/actions/BM1103/ ). The studies were published between 2011 and 2023 and included participants with subjective cognitive decline plus; neurocognitive disorders, including mild cognitive impairment (MCI), Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), dementia with Lewy bodies (DLB) and vascular cognitive impairment (VCI); as well as schizophrenia spectrum disorders, bipolar and major depressive disorders, autism spectrum disorder, attention-deficit/hyperactivity disorder, panic disorder and alcohol use disorder. Hypoperfusion associated with cognitive impairment was the major finding across the spectrum of cognitive decline. Regional hyperperfusion also was reported in MCI, AD, frontotemporal dementia phenocopy syndrome and VCI. Hypoperfused structures found to aid in diagnosing AD included the precunei and adjacent posterior cingulate cortices. Hypoperfused structures found to better diagnose patients with FTLD were the anterior cingulate cortices and frontal regions. Hypoperfusion in patients with DLB was found to relatively spare the temporal lobes, even after correction for partial volume effects. Hyperperfusion in the temporal cortices and hypoperfusion in the prefrontal and anterior cingulate cortices were found in patients with schizophrenia, most of whom were on medication and at the chronic stage of illness. Infratentorial structures were found to be abnormally perfused in patients with bipolar or major depressive disorders. Brain perfusion abnormalities were helpful in diagnosing most neurocognitive disorders. Abnormalities reported in VCI and the remaining mental disorders were heterogeneous and not generalisable.

Quantitative susceptibility mapping for detection of kidney stones, hemorrhage differentiation, and cyst classification in ADPKD

BACKGROUND AND PURPOSE

The objective is to demonstrate feasibility of quantitative susceptibility mapping (QSM) in autosomal dominant polycystic kidney disease (ADPKD) patients and to compare imaging findings with traditional T1/T2w magnetic resonance imaging (MRI).

METHODS

Thirty-three consecutive patients (11 male, 22 female) diagnosed with ADPKD were initially selected. QSM images were reconstructed from the multiecho gradient echo data and compared to co-registered T2w, T1w, and CT images. Complex cysts were identified and classified into distinct subclasses based on their imaging features. Prevalence of each subclass was estimated.

RESULTS

QSM visualized two renal calcifications measuring 9 and 10 mm and three pelvic phleboliths measuring 2 mm but missed 24 calcifications measuring 1 mm or less and 1 larger calcification at the edge of the field of view. A total of 121 complex T1 hyperintense/T2 hypointense renal cysts were detected. 52 (43%) Cysts appeared hyperintense on QSM consistent with hemorrhage; 60 (49%) cysts were isointense with respect to simple cysts and normal kidney parenchyma, while the remaining 9 (7%) were hypointense. The presentation of the latter two complex cyst subtypes is likely indicative of proteinaceous composition without hemorrhage.

CONCLUSION

Our results indicate that QSM of ADPKD kidneys is possible and uniquely suited to detect large renal calculi without ionizing radiation and able to identify properties of complex cysts unattainable with traditional approaches.

Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping

OBJECTIVE

Quantitative susceptibility mapping (QSM) provides an estimate of the magnetic susceptibility of tissue using magnetic resonance (MR) phase measurements. The tissue magnetic susceptibility (source) from the measured magnetic field distribution/local tissue field (effect) inherent in the MR phase images is estimated by numerically solving the inverse source-effect problem. This study aims to develop an effective model-based deep-learning framework to solve the inverse problem of QSM.

MATERIALS AND METHODS

This work proposes a Schatten p -norm-driven model-based deep learning framework for QSM with a learnable norm parameter p to adapt to the data. In contrast to other model-based architectures that enforce the l2 -norm or l1 -norm for the denoiser, the proposed approach can enforce any p -norm ( 0 < p ≤ 2 ) on a trainable regulariser.

RESULTS

The proposed method was compared with deep learning-based approaches, such as QSMnet, and model-based deep learning approaches, such as learned proximal convolutional neural network (LPCNN). Reconstructions performed using 77 imaging volumes with different acquisition protocols and clinical conditions, such as hemorrhage and multiple sclerosis, showed that the proposed approach outperformed existing state-of-the-art methods by a significant margin in terms of quantitative merits.

CONCLUSION

The proposed SpiNet-QSM showed a consistent improvement of at least 5% in terms of the high-frequency error norm (HFEN) and normalized root mean squared error (NRMSE) over other QSM reconstruction methods with limited training data.

A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation

Quantitative susceptibility mapping (QSM) is an MRI-based technique that estimates the underlying tissue magnetic susceptibility based on phase signal. Deep learning (DL)-based methods have shown promise in handling the challenging ill-posed inverse problem for QSM reconstruction. However, they require extensive paired training data that are typically unavailable and suffer from generalization problems. Recent model-incorporated DL approaches also overlook the non-local effect of the tissue phase in applying the source-to-field forward model due to patch-based training constraint, resulting in a discrepancy between the prediction and measurement and subsequently suboptimal QSM reconstruction. This study proposes an unsupervised and subject-specific DL method for QSM reconstruction based on implicit neural representation (INR), referred to as INR-QSM. INR has emerged as a powerful framework for learning a high-quality continuous representation of the signal (image) by exploiting its internal information without training labels. In INR-QSM, the desired susceptibility map is represented as a continuous function of the spatial coordinates, parameterized by a fully-connected neural network. The weights are learned by minimizing a loss function that includes a data fidelity term incorporated by the physical model and regularization terms. Additionally, a novel phase compensation strategy is proposed for the first time to account for the non-local effect of tissue phase in data consistency calculation to make the physical model more accurate. Our experiments show that INR-QSM outperforms traditional established QSM reconstruction methods and the compared unsupervised DL method both qualitatively and quantitatively, and is competitive against supervised DL methods under data perturbations.

Chaos and COSMOS-Considerations on QSM methods with multiple and single orientations and effects from local anisotropy

PURPOSE

Field-to-susceptibility inversion in quantitative susceptibility mapping (QSM) is ill-posed and needs numerical stabilization through either regularization or oversampling by acquiring data at three or more object orientations. Calculation Of Susceptibility through Multiple Orientations Sampling (COSMOS) is an established oversampling approach and regarded as QSM gold standard. It achieves a well-conditioned inverse problem, requiring rotations by 0°, 60° and 120° in the yz-plane. However, this is impractical in vivo, where head rotations are typically restricted to a range of ±25°. Non-ideal sampling degrades the conditioning with residual streaking artifacts whose mitigation needs further regularization. Moreover, susceptibility anisotropy in white matter is not considered in the COSMOS model, which may introduce additional bias. The current work presents a thorough investigation of these effects in primate brain.

METHODS

Gradient-recalled echo (GRE) data of an entire fixed chimpanzee brain were acquired at 7 T (350 μm resolution, 10 orientations) including ideal COSMOS sampling and realistic rotations in vivo. Comparisons of the results included ideal COSMOS, in-vivo feasible acquisitions with 3-8 orientations and single-orientation iLSQR QSM.

RESULTS

In-vivo feasible and optimal COSMOS yielded high-quality susceptibility maps with increased SNR resulting from averaging multiple acquisitions. COSMOS reconstructions from non-ideal rotations about a single axis required additional L2-regularization to mitigate residual streaking artifacts.

CONCLUSION

In view of unconsidered anisotropy effects, added complexity of the reconstruction, and the general challenge of multi-orientation acquisitions, advantages of sub-optimal COSMOS schemes over regularized single-orientation QSM appear limited in in-vivo settings.

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.

Quantitative susceptibility mapping in the brain reflects spatial expression of genes involved in iron homeostasis and myelination

Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p < .05, corrected) between expression of ferritin and the QSM signal in deep grey nuclei regions. We repeated the analysis for other genes that encode proteins thought to be involved in the transport and storage of iron in the brain, as well as myelination. In addition to ferritin, our findings demonstrate a positive correlation (p < .05, corrected) between the expression of ferroportin, transferrin, divalent metal transporter 1, several gene markers of myelinating oligodendrocytes, and the QSM signal in deep grey nuclei regions. Our results suggest that the QSM signal reflects both the storage and active transport of iron in the deep grey nuclei regions of the brain.

Assessing brain integrity in patients with long-term and well-functioning metal-based hip implants

Production of metal debris from implant wear and corrosion processes is now a well understood occurrence following hip arthroplasty. Evidence has shown that metal ions can enter the bloodstream and travel to distant organs including the brain, and in extreme cases, can induce sensorial and neurological diseases. Our objective was tosimultaneously analyze brain anatomy and physiology in patients with long-term and well-functioning implants. Included were subjects who had received total hip or hip resurfacing arthroplastywith an implantation time of a minimum of 7 years (n = 28) and age- and sex-matched controls (n = 32). Blood samples were obtained to measure ion concentrations of cobalt and chromium, and the Montreal Cognitive Assessment was performed. 3T MRI brain scans were completed with an MPRAGE sequence for ROI segmentation and multiecho gradient echo sequences to generate QSM and R2* maps. Mean QSM and R2* values were recorded for five deep brain and four middle and cortical brain structures on both hemispheres: pallidum, putamen, caudate, amygdala, hippocampus, anterior cingulate, inferior temporal, and cerebellum. No differences in QSM or R2* or cognition scores were found between both groups (p > 0.6654). No correlation was found between susceptibility and blood ion levels for cobalt or chromium in any region of the brain. No correlation was found between blood ion levels and cognition scores. Clinical significance: Results suggest that metal ions released by long-term and well-functioning implants do not affect brain integrity.

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a simulated-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms. The PnP OA-LFE module's versatility was further demonstrated by its successful application to xQSM, a distinct DL-QSM network for dipole inversion. In conclusion, this work introduces a new DL paradigm, allowing researchers to develop innovative QSM methods without requiring a complete overhaul of their existing architectures.

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.

Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features

A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.

Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice.

OBJECTIVE

We performed a systematic review and meta-analysis on the use of QSM in MS.

METHODS

Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively.

RESULTS

After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions.

CONCLUSIONS

We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.

Iron quantification in basal ganglia: quantitative susceptibility mapping as a potential biomarker for Alzheimer's disease - a systematic review and meta-analysis

Introduction

Alzheimer's disease (AD), characterized by distinctive pathologies such as amyloid-β plaques and tau tangles, also involves deregulation of iron homeostasis, which may accelerate neurodegeneration. This meta-analysis evaluated the use of quantitative susceptibility mapping (QSM) to detect iron accumulation in the deep gray matter (DGM) of the basal ganglia in AD, contributing to a better understanding of AD progression, and potentially leading to new diagnostic and therapeutic approaches.

Methods

Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the PubMed, Scopus, Web of Sciences, and Google Scholar databases up to October 2023 for studies employing QSM in AD research. Eligibility criteria were based on the PECO framework, and we included studies assessing alterations in magnetic susceptibility indicative of iron accumulation in the DGM of patients with AD. After initial screening and quality assessment using the Newcastle-Ottawa Scale, a meta-analysis was conducted to compare iron levels between patients with AD and healthy controls (HCs) using a random-effects model.

Results

The meta-analysis included nine studies comprising 267 patients with AD and 272 HCs. There were significantly higher QSM values, indicating greater iron deposition, in the putamen (standardized mean difference (SMD) = 1.23; 95% CI: 0.62 to 1.84; p = 0.00), globus pallidus (SMD = 0.79; 95% CI: 0.07 to 1.52; p = 0.03), and caudate nucleus (SMD = 0.72; 95% CI: 0.39 to 1.06; p = 0.00) of AD patients compared to HCs. However, no significant differences were found in the thalamus (SMD = 1.00; 95% CI: -0.42 to 2.43; p = 0.17). The sensitivity analysis indicated that no single study impacted the overall results. Age was identified as a major contributor to heterogeneity across all basal ganglia nuclei in subgroup analysis. Older age (>69 years) and lower male percentage (≤30%) were associated with greater putamen iron increase in patients with AD.

Conclusion

The study suggests that excessive iron deposition is linked to the basal ganglia in AD, especially the putamen. The study underscores the complex nature of AD pathology and the accumulation of iron, influenced by age, sex, and regional differences, necessitating further research for a comprehensive understanding.

Iron-based biomarkers for personalizing pharmacological ascorbate therapy in glioblastoma: insights from a phase 2 clinical trial

BACKGROUND

Pharmacological ascorbate (intravenous delivery reaching plasma concentrations ≈ 20 mM; P-AscH-) has emerged as a promising therapeutic strategy for glioblastoma. Recently, a single-arm phase 2 clinical trial demonstrated a significant increase in overall survival when P-AscH- was combined with temozolomide and radiotherapy. As P-AscH- relies on iron-dependent mechanisms, this study aimed to assess the predictive potential of both molecular and imaging-based iron-related markers to enhance the personalization of P-AscH- therapy in glioblastoma participants.

METHODS

Participants (n = 55) with newly diagnosed glioblastoma were enrolled in a phase 2 clinical trial conducted at the University of Iowa (NCT02344355). Tumor samples obtained during surgical resection were processed and stained for transferrin receptor and ferritin heavy chain expression. A blinded pathologist performed pathological assessment. Quantitative susceptibility mapping (QSM) measures were obtained from pre-radiotherapy MRI scans following maximal safe surgical resection. Circulating blood iron panels were evaluated prior to therapy through the University of Iowa Diagnostic Laboratory.

RESULTS

Through univariate analysis, a significant inverse association was observed between tumor transferrin receptor expression and overall and progression-free survival. QSM measures exhibited a significant, positive association with progression-free survival. Subjects were actively followed until disease progression and then were followed through chart review or clinical visits for overall survival.

CONCLUSIONS

This study analyzes iron-related biomarkers in the context of P-AscH- therapy for glioblastoma. Integrating molecular, systemic, and imaging-based markers offers a multifaceted approach to tailoring treatment strategies, thereby contributing to improved patient outcomes and advancing the field of glioblastoma therapy.

mcTFI QSM MRI ABC/2 intracranial hemorrhage to noncontrast head CT volume measurement equivalence

BACKGROUND/OBJECTIVES

Intracranial hemorrhage (ICH) volume assessment is an important part of patient management and is routinely obtained by non-contrast head CT (NCHCT) using the validated ABC/2 measurement method. Because conventional MRI imaging sequences demonstrate variability in ICH appearance, volumetric analyses for MRI bleed volume in a standardized manner using ABC/2 is not possible. The recently introduced multiecho-complex total field inversion quantitative susceptibility mapping (mcTFI QSM) MRI technique, which maps brain tissue susceptibility to both depict brain tissue structures and quantify tissue susceptibility, may provide a viable alternative. In this study we evaluated mcTFI QSM ABC/2 ICH volume assessment relative to NCHCT.

METHODS

Patients with ICH who had undergone NCHCT and MRI brain scans within 48 h were recruited for this retrospective study. The ABC/2 method was applied to estimate the bleed volume for both NCHCT and MRI by a CAQ-certified neuroradiologist with 10 years of experience and a trained laboratory assistant. Results were analyzed via Bland-Altman (B-A) and linear regression.

RESULTS

54 patients (27 females) who had undergone NCHCT and MRI within 48 h (<24 h., n = 31, 24-48 h, n = 10) were enrolled. mcTFI QSM ICH volume measurement method showed a positive correlation (99.5%) compared to NCHCT. B-A plot comparing ABC/2 ICH volume on NCHCT and mcTFI MRI done for patients within 24 h demonstrates a bias of -0.09%.

CONCLUSIONS

ICH volume calculation using ABC/2 on mcTFI QSM showed a high correlation with NCHCT measurement. These results suggest mcTFI QSM is a promising MRI method for ABC/2 for bleed volume measurement.

Multivariate and regional age-related change in basal ganglia iron in neonates

In the perinatal period, reward and cognitive systems begin trajectories, influencing later psychiatric risk. The basal ganglia is important for reward and cognitive processing but early development has not been fully characterized. To assess age-related development, we used a measure of basal ganglia physiology, specifically brain tissue iron, obtained from nT2* signal in resting-state functional magnetic resonance imaging (rsfMRI), associated with dopaminergic processing. We used data from the Developing Human Connectome Project (n = 464) to assess how moving from the prenatal to the postnatal environment affects rsfMRI nT2*, modeling gestational and postnatal age separately for basal ganglia subregions in linear models. We did not find associations with tissue iron and gestational age [range: 24.29-42.29] but found positive associations with postnatal age [range:0-17.14] in the pallidum and putamen, but not the caudate. We tested if there was an interaction between preterm birth and postnatal age, finding early preterm infants (GA < 35 wk) had higher iron levels and changed less over time. To assess multivariate change, we used support vector regression to predict age from voxel-wise-nT2* maps. We could predict postnatal but not gestational age when maps were residualized for the other age term. This provides evidence subregions differentially change with postnatal experience and preterm birth may disrupt trajectories.

Sub-voxel quantitative susceptibility mapping for assessing whole-brain magnetic susceptibility from ages 4 to 80

The evolution of magnetic susceptibility of the brain is mainly determined by myelin in white matter (WM) and iron deposition in deep gray matter (DGM). However, existing imaging techniques have limited abilities to simultaneously quantify the myelination and iron deposition within a voxel throughout brain development and aging. For instance, the temporal trajectories of iron in the brain WM and myelination in DGM have not been investigated during the aging process. This study aimed to map the age-related iron and myelin changes in the whole brain, encompassing myelin in DGM and iron deposition in WM, using a novel sub-voxel quantitative susceptibility mapping (QSM) method. To achieve this, a cohort of 494 healthy adults (18-80 years old) was studied. The sub-voxel QSM method was employed to obtain the paramagnetic and diamagnetic susceptibility based on the approximatedR 2 ' map from acquiredR 2 * map. The linear relationship betweenR 2 * andR 2 ' maps was established from the regression coefficients on a small cohort data acquired with both 3D gradient recalled echo data andR 2 mapping. Large cohort sub-voxel susceptibility maps were used to create longitudinal and age-specific atlases via group-wise registration. To explore the differential developmental trajectories in the DGM and WM, we employed nonlinear models including exponential and Poisson functions, along with generalized additive models. The constructed atlases reveal the iron accumulation in the posterior part of the putamen and the gradual myelination process in the globus pallidus with aging. Interestingly, the developmental trajectories show that the rate of myelination differs among various DGM regions. Furthermore, the process of myelin synthesis is paralleled by an associated pattern of iron accumulation in the primary WM fiber bundles. In summary, our study offers significant insights into the distinctive developmental trajectories of iron in the brain's WM and myelination/demyelination in the DGM in vivo. These findings highlight the potential of using sub-voxel QSM to uncover new perspectives in neuroscience and improve our understanding of whole-brain myelination and iron deposit processes across the lifespan.

Thin slab quantitative susceptibility mapping

PURPOSE

Susceptibility maps reconstructed from thin slabs may suffer underestimation due to background-field removal imperfections near slab boundaries and the increased difficulty of solving a 3D-inversion problem with reduced support, particularly in the direction of the main magnetic field. Reliable QSM reconstruction from thin slabs would enable focal acquisitions in a much-reduced scan time.

METHODS

This work proposes using additional rapid low-resolution data of extended spatial coverage to improve background-field estimation and regularize the inversion-to-susceptibility process for high resolution, thin slab data. The new method was tested using simulated and in-vivo brain data of high resolution (0.33 × 0.33 × 0.33 mm3 and 0.54 × 0.54 × 0.65 mm3 , respectively) at 3T, and compared to the standard large volume approach.

RESULTS

Using the proposed method, in-vivo high-resolution QSM at 3T was obtained from slabs of width as small as 10.4 mm, aided by a lower-resolution dataset of 24 times coarser voxels. Simulations showed that the proposed method produced more consistent measurements from slabs of at least eight slices. Reducing the mean ROI error to 5% required the low-resolution data to cover ˜60 mm in the direction of the main field, have at least 2-mm isotropic resolution that is not coarser than the high-resolution data by more than four-fold in any direction.

CONCLUSION

Applying the proposed method enabled focal QSM acquisitions at sub-millimeter resolution within reasonable acquisition time.

Quantitative susceptibility mapping of brain iron in healthy aging and cognition

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.

Straightforward Magnetic Resonance Temperature Measurements Combined with High Frame Rate and Magnetic Susceptibility Correction

Proton resonance frequency shift (PRFS) is an MRI-based simple temperature mapping method that exhibits higher spatial and temporal resolution than temperature mapping methods based on T1 relaxation time and diffusion. PRFS temperature measurements are validated against fiber-optic thermal sensors (FOSs). However, the use of FOSs may introduce temperature errors, leading to both underestimation and overestimation of PRFS measurements, primarily due to material susceptibility changes caused by the thermal sensors. In this study, we demonstrated susceptibility-corrected PRFS (scPRFS) with a high frame rate and accuracy for suitably distributed temperatures. A single-echo-based background removal technique was employed for phase variation correction, primarily owing to magnetic susceptibility, which enabled fast temperature mapping. The scPRFS was used to validate the temperature fidelity by comparing the temperatures of fiber-optic sensors and conventional PRFS through phantom-mimicked human and ex vivo experiments. This study demonstrates that scPRFS measurements in agar-gel are in good agreement with the thermal sensor readings, with a root mean square error (RMSE) of 0.33-0.36 °C in the phantom model and 0.12-0.16 °C in the ex vivo experiment. These results highlight the potential of scPRFS for precise thermal monitoring and ablation in both low- and high-temperature non-invasive therapies.

The diamagnetic component map from quantitative susceptibility mapping (QSM) source separation reveals pathological alteration in Alzheimer's disease-driven neurodegeneration

A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.

SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform

Multimodal neuroimaging data of various brain disorders provides valuable information to understand brain function in health and disease. Various neuroimaging-based databases have been developed that mainly consist of volumetric magnetic resonance imaging (MRI) data. We present the comprehensive web-based neuroimaging platform "SWADESH" for hosting multi-disease, multimodal neuroimaging, and neuropsychological data along with analytical pipelines. This novel initiative includes neurochemical and magnetic susceptibility data for healthy and diseased conditions, acquired using MR spectroscopy (MRS) and quantitative susceptibility mapping (QSM) respectively. The SWADESH architecture also provides a neuroimaging database which includes MRI, MRS, functional MRI (fMRI), diffusion weighted imaging (DWI), QSM, neuropsychological data and associated data analysis pipelines. Our final objective is to provide a master database of major brain disease states (neurodegenerative, neuropsychiatric, neurodevelopmental, and others) and to identify characteristic features and biomarkers associated with such disorders.

Quantitative Susceptibility Mapping MRI in Deep-Brain Nuclei in First-Episode Psychosis

BACKGROUND

Psychosis is related to neurochemical changes in deep-brain nuclei, particularly suggesting dopamine dysfunctions. We used an magnetic resonance imaging-based technique called quantitative susceptibility mapping (QSM) to study these regions in psychosis. QSM quantifies magnetic susceptibility in the brain, which is associated with iron concentrations. Since iron is a cofactor in dopamine pathways and co-localizes with inhibitory neurons, differences in QSM could reflect changes in these processes.

METHODS

We scanned 83 patients with first-episode psychosis and 64 healthy subjects. We reassessed 22 patients and 21 control subjects after 3 months. Mean susceptibility was measured in 6 deep-brain nuclei. Using linear mixed models, we analyzed the effect of case-control differences, region, age, gender, volume, framewise displacement (FD), treatment duration, dose, laterality, session, and psychotic symptoms on QSM.

RESULTS

Patients showed a significant susceptibility reduction in the putamen and globus pallidus externa (GPe). Patients also showed a significant R2* reduction in GPe. Age, gender, FD, session, group, and region are significant predictor variables for QSM. Dose, treatment duration, and volume were not predictor variables of QSM.

CONCLUSIONS

Reduction in QSM and R2* suggests a decreased iron concentration in the GPe of patients. Susceptibility reduction in putamen cannot be associated with iron changes. Since changes observed in putamen and GPe were not associated with symptoms, dose, and treatment duration, we hypothesize that susceptibility may be a trait marker rather than a state marker, but this must be verified with long-term studies.

Change of iron content in brain regions after intravenous iron therapy in restless legs syndrome: quantitative susceptibility mapping study

STUDY OBJECTIVES

The pathomechanism of restless legs syndrome (RLS) is related to brain iron deficiency and iron therapy is effective for RLS; however, the effect of iron therapy on human brain iron state has never been studied with magnetic resonance imaging. This study aimed to investigate the change of brain iron concentrations in patients with RLS after intravenous iron therapy using quantitative susceptibility mapping (QSM).

METHODS

We enrolled 31 RLS patients and 20 healthy controls. All participants underwent initial baseline (t0) assessment using brain magnetic resonance imaging, serum iron status, and sleep questionnaires including international RLS Study Group rating scale (IRLS). RLS patients underwent follow-up tests at 6 and 24 weeks (t1 and t2) after receiving 1000 mg ferric carboxymaltose. Iron content of region-of-interest on QSM images was measured for 13 neural substrates using the fixed-shaped method.

RESULTS

RLS symptoms evaluated using IRLS were significantly improved after iron treatment (t0: 29.7 ± 6.5, t1: 19.5 ± 8.5, t2: 21.3 ± 10.1; p < .001). There was no significant difference in susceptibility values between the controls and RLS patients at t0. In the caudate nucleus, putamen, and pulvinar thalamus of RLS patients, the QSM values differed significantly for three timepoints (p = .035, .048, and .032, respectively). The post-hoc analysis revealed that the QSM values increased at t1 in the caudate nucleus (66.8 ± 18.0 vs 76.4 ± 16.6, p = .037) and decreased from t1 to t2 in the putamen (69.4 ± 16.3 vs 62.5 ± 13.6, p = .025). Changes in the QSM values for the pulvinar and caudate nuclei at t1 were positively and negatively correlated with symptomatic improvement, respectively (r = 0.361 and -0.466, respectively).

CONCLUSIONS

Intravenous iron treatment results in changes in brain iron content which correlate to reductions in RLS severity. This suggests a connection between symptom improvement and the associated specific brain regions constituting the sensorimotor network.

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.

MRI findings in movement disorders and associated sleep disturbances

BACKGROUND

One of the most useful tools for identifying sleep disturbances is neuroimaging, especially magnetic resonance imaging (MRI). This review research was to look at the role of MRI findings in movement disorders and sleep disturbances.

METHODS

This review collects all MRI data on movement disorders and sleep disruptions. Between 2000 and 2022, PubMed and Google Scholar were utilized to find original English publications and reviews. According to the inclusion and exclusion criteria, around 100 publications were included. We only looked at research that explored MRI modality together with movement problems, sleep disorders, and brain area involvement. Most of the information focuses on movement irregularities and sleep interruptions.

RESULTS

Movement disorders such as Parkinson's disease (PD), Huntington's disease (HD), neuromuscular diseases, rapid eye movement (REM) sleep behavior movement disorder (RBD), cerebellar movement disorders, and brainstem movement disorders are assessed using MRI-based neuroimaging techniques. Some of the brain areas were associated with disorders in movement abnormalities and related sleep disturbances. This review found that many people with mobility disorders also have sleep problems. Some brain areas' malfunctions may cause motor and sleep issues.

CONCLUSION

Neuroimaging helps us understand the sleep difficulties associated with movement disorders by examining the structural and functional implications of movement disorders and sleep disturbances.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.