MRI estimates of brain iron concentration in normal aging using quantitative susceptibility mapping

Iron depletion has different consequences on the growth and survival of Toxoplasma gondii strains

Toxoplasma gondii is an obligate intracellular parasite responsible for a pathology called toxoplasmosis, which primarily affects immunocompromised individuals and developing foetuses. The parasite can scavenge essential nutrients from its host to support its growth and survival. Among them, iron is one of the most important elements needed to sustain basic cellular functions as it is involved in a number of key metabolic processes, including oxygen transport, redox balance, and electron transport. We evaluated the effects of an iron chelator on the development of several parasite strains and found that they differed in their ability to tolerate iron depletion. The growth of parasites usually associated with a model of acute toxoplasmosis was strongly affected by iron depletion, whereas cystogenic strains were less sensitive as they were able to convert into persisting developmental forms that are associated with the chronic form of the disease. Ultrastructural and biochemical characterization of the impact of iron depletion on parasites also highlighted striking changes in both their metabolism and that of the host, with a marked accumulation of lipid droplets and perturbation of lipid homoeostasis. Overall, our study demonstrates that although acute iron depletion has an important effect on the growth of T. gondii, it has a more profound impact on actively dividing parasites, whereas less metabolically active parasite forms may be able to avoid some of the most detrimental consequences.

Comparative analysis of quantitative susceptibility mapping in preclinical dementia detection

PURPOSE

This review aims to explore the role of Quantitative Susceptibility Mapping (QSM) in the early detection of neurodegenerative diseases, particularly Alzheimer's disease (AD) and Lewy body dementia (LBD). By examining QSM's ability to map brain iron deposition, we seek to highlight its potential as a diagnostic tool for preclinical dementia.

METHODOLOGY

QSM techniques involve the advanced processing of MRI phase images to reconstruct tissue susceptibility, employing methods such as spherical mean value filtering and Tikhonov regularization for accurate background field removal. This review discusses how these methodologies enable the precise quantification of iron and other elements within the brain.

RESULTS

QSM has demonstrated effectiveness in identifying early pathological changes in key brain regions, including the hippocampus, basal ganglia, and substantia nigra. These regions are significantly impacted in the early stages of AD and LBD. Studies reviewed indicate that QSM can detect subtle neurodegenerative changes, providing valuable insights into disease progression. However, challenges remain in standardizing QSM processing algorithms to ensure consistent results across different studies.

CONCLUSION

QSM emerges as a promising tool for early dementia detection, offering precise measurements of brain iron deposition and other critical biomarkers. The review underscores the importance of refining QSM methodologies and integrating them with other imaging modalities to improve early diagnosis and management of neurodegenerative diseases. Future research should focus on standardizing QSM techniques and exploring their synergistic use with other neuroimaging methods to enhance its clinical utility.

Exploring cognitive related microstructural alterations in normal appearing white matter and deep grey matter for small vessel disease: A quantitative susceptibility mapping study

Brain microstructural alterations possibly occur in the normal-appearing white matter (NAWM) and grey matter of small vessel disease (SVD) patients, and may contribute to cognitive impairment. The aim of this study was to explore cognitive related microstructural alterations in white matter and deep grey matter nuclei in SVD patients using magnetic resonance (MR) quantitative susceptibility mapping (QSM). 170 SVD patients, including 103 vascular mild cognitive impairment (VaMCI) and 67 no cognitive impairment (NCI), and 21 healthy control (HC) subjects were included, all underwent a whole-brain QSM scanning. Using a white matter and a deep grey matter atlas, subregion-based QSM analysis was conducted to identify and characterize microstructural alterations occurring within white matter and subcortical nuclei. Significantly different susceptibility values were revealed in NAWM and in several specific white matter tracts including anterior limb of internal capsule, corticospinal tract, medial lemniscus, middle frontal blade, superior corona radiata and tapetum among VaMCI, NCI and HC groups. However, no difference was found in white matter hyperintensities between VaMCI and NCI. A trend toward higher susceptibility in the caudate nucleus and globus pallidus of VaMCI patients compared to HC, indicating elevated iron deposition in these areas. Interestingly, some of these QSM parameters were closely correlated with both global and specific cognitive function scores, controlling age, gender and education level. Our study suggested that QSM may serve as a useful imaging tool for monitoring cognitive related microstructural alterations in brain. This is especially meaningful for white matter which previously lacks of attention.

Quantitative susceptibility mapping in amyotrophic lateral sclerosis: automatic quantification of the magnetic susceptibility in the subcortical nuclei

Objective: Previous studies have suggested a link between dysregulation of cortical iron levels and neuronal loss in amyotrophic lateral sclerosis (ALS) patients. However, few studies have reported differences in quantitative susceptibility mapping (QSM) values in subcortical nuclei between patients with ALS and healthy controls (HCs). Methods: MRI was performed using a 3 Tesla Prisma scanner (64-channel head coil), including 3D T1-MPRAGE and multi-echo 3D GRE for QSM reconstruction. Automated QSM segmentation was used to measure susceptibility values in the subcortical nuclei, which were compared between the groups. Correlations with clinical scales were analyzed. Group comparisons were performed using independent t-tests, with p < 0.05 considered significant. Correlations were assessed using Pearson's correlation, with p < 0.05 considered significant. Cohen's d was reported to compare the standardized mean difference (SMD) of QSM. Results: Twelve patients with limb-onset ALS (mean age 48.7 years, 75% male) and 13 age-, sex-, and handedness-matched HCs (mean age 44.6 years, 69% male) were included. Compared to HCs, ALS patients demonstrated significantly lower susceptibility in the left caudate nucleus (CN) (SMD = -0.845), right CN (SMD = -0.851), whole CN (SMD = -1.016), and left subthalamic nucleus (STN) (SMD = -1.000). Susceptibility in the left putamen (SMD = -0.857), left thalamus (SMD = -1.081), and whole thalamus (SMD = -0.968) was significantly higher in the patients. The susceptibility of the substantia nigra (SN), CN, and pulvinar was positively correlated with disease duration. Conclusions: QSM detects abnormal iron accumulation patterns in the subcortical gray matter of ALS patients, which correlates with disease characteristics, supporting its potential as a neuroimaging biomarker.

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.

Neurotoxicology of dopamine: Victim or assailant?

Since the identification of dopamine as a neurotransmitter in the mid-20th century, investigators have examined the regulation of dopamine homeostasis at a basic biological level and in human disorders. Genetic animal models that manipulate the expression of proteins involved in dopamine homeostasis have provided key insight into the consequences of dysregulated dopamine. As a result, we have come to understand the potential of dopamine to act as an endogenous neurotoxin through the generation of reactive oxygen species and reactive metabolites that can damage cellular macromolecules. Endogenous factors, such as genetic variation and subcellular processes, and exogenous factors, such as environmental exposures, have been identified as contributors to the dysregulation of dopamine homeostasis. Given the variety of dysregulating factors that impact dopamine homeostasis and the potential for dopamine itself to contribute to further cellular dysfunction, dopamine can be viewed as both the victim and an assailant of neurotoxicity. Parkinson's disease has emerged as the exemplar case study of dopamine dysregulation due to the genetic and environmental factors known to contribute to disease risk, and due to the evidence of dysregulated dopamine as a pathologic and pathogenic feature of the disease. This review, inspired by the talk, "Dopamine in Durham: location, location, location" presented by Dr. Miller for the Jacob Hooisma Memorial Lecture at the International Neurotoxicology Association meeting in 2023, offers a primer on dopamine toxicity covering endogenous and exogenous factors that disrupt dopamine homeostasis and the actions of dopamine as an endogenous neurotoxin.

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.

A commentary on studies of brain iron accumulation during ageing

Brain iron content is widely reported to increase during "ageing", across multiple species from nematodes, rodents (mice and rats) and humans. Given the redox-active properties of iron, there has been a large research focus on iron-mediated oxidative stress as a contributor to tissue damage during natural ageing, and also as a risk factor for neurodegenerative disease. Surprisingly, however, the majority of published studies have not investigated brain iron homeostasis during the biological time period of senescence, and thus knowledge of how brain homeostasis changes during this critical stage of life largely remains unknown. This commentary examines the literature published on the topic of brain iron homeostasis during ageing, providing a critique on limitations of currently used experimental designs. The commentary also aims to highlight that although much research attention has been given to iron accumulation or iron overload as a pathological feature of ageing, there is evidence to support functional iron deficiency may exist, and this should not be overlooked in studies of ageing or neurodegenerative disease.

A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla

Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.

Iron Deposition and Distribution Across the Hippocampus Is Associated with Pattern Separation and Pattern Completion in Older Adults at Risk for Alzheimer's Disease

Elevated iron deposition in the brain has been observed in older adult humans and persons with Alzheimer's disease (AD), and has been associated with lower cognitive performance. We investigated the impact of iron deposition, and its topographical distribution across hippocampal subfields and segments (anterior, posterior) measured along its longitudinal axis, on episodic memory in a sample of cognitively unimpaired older adults at elevated familial risk for AD (N = 172, 120 females, 52 males; mean age = 68.8 ± 5.4 years). MRI-based quantitative susceptibility maps were acquired to derive estimates of hippocampal iron deposition. The Mnemonic Similarity Task was used to measure pattern separation and pattern completion, two hippocampally mediated episodic memory processes. Greater hippocampal iron load was associated with lower pattern separation and higher pattern completion scores, both indicators of poorer episodic memory. Examination of iron levels within hippocampal subfields across its long axis revealed topographic specificity. Among the subfields and segments investigated here, iron deposition in the posterior hippocampal CA1 was the most robustly and negatively associated with the fidelity memory representations. This association remained after controlling for hippocampal volume and was observed in the context of normal performance on standard neuropsychological memory measures. These findings reveal that the impact of iron load on episodic memory performance is not uniform across the hippocampus. Both iron deposition levels as well as its spatial distribution, must be taken into account when examining the relationship between hippocampal iron and episodic memory in older adults at elevated risk for AD.

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.

MR Imaging-based Biomarker Development in Hemorrhagic Stroke Patients Including Brain Iron Quantification, Diffusion Tensor Imaging, and Phenomenon of Ultra-early Erythrolysis

This review article discusses the role of MR imaging-based biomarkers in understanding and managing hemorrhagic strokes, focusing on intracerebral hemorrhage (ICH) and aneurysmal subarachnoid hemorrhage. ICH is a severe type of stroke with high mortality and morbidity rates, primarily caused by the rupture of small blood vessels in the brain, resulting in hematoma formation. MR imaging-based biomarkers, including brain iron quantification, ultra-early erythrolysis detection, and diffusion tensor imaging, offer valuable insights for hemorrhagic stroke management. These biomarkers could improve early diagnosis, risk stratification, treatment monitoring, and patient outcomes in the future, revolutionizing our approach to hemorrhagic strokes.

A predictor-corrector phase unwrapping algorithm for temporally undersampled gradient-echo MRI

PURPOSE

To develop a method for unwrapping temporally undersampled and nonlinear gradient recalled echo (GRE) phase.

THEORY AND METHODS

Temporal unwrapping is performed as a sequential one step prediction of the echo phase, followed by a correction to the nearest integer wrap-count. A spatio-temporal extension of the 1D predictor corrector unwrapping (PCU) algorithm improves the prediction accuracy, and thereby maintains spatial continuity. The proposed method is evaluated using numerical phantom, physical phantom, and in vivo brain data at both 3 T and 9.4 T. The unwrapping performance is compared with the state-of-the-art temporal and spatial unwrapping algorithms, and the spatio-temporal iterative virtual-echo based Nyquist sampled (iVENyS) algorithm.

RESULTS

Simulation results showed significant reduction in unwrapping errors at higher echoes compared with the state-of-the-art algorithms. Similar to the iVENyS algorithm, the PCU algorithm was able to generate spatially smooth phase images for in vivo data acquired at 3 T and 9.4 T, bypassing the use of additional spatial unwrapping step. A key advantage over iVENyS algorithm is the superior performance of PCU algorithm at higher echoes.

CONCLUSION

PCU algorithm serves as a robust phase unwrapping method for temporally undersampled and nonlinear GRE phase, particularly in the presence of high field gradients.

Empirically derived formulae for calculation of age- and region-related levels of iron, copper and zinc in the adult C57BL/6 mouse brain

Metal dyshomeostasis is associated with neurodegenerative disorders, cancers and vascular disease. We report the effects of age (range: 3 to 18 months) on regional copper, iron and zinc levels in the brain of the C57BL/6 mouse, a widely used inbred strain with a permissive background allowing maximal expression of mutations in models that recapitulate these disorders. We present formulae that can be used to determine regional brain metal concentrations in the C57BL/6 mouse at any age in the range of three to eighteen months of life. Copper levels in the C57BL/6 mouse adult brain were highest in the striatum and cerebellum and increased with age, excepting the cortex and hippocampus. Regional iron levels increased linearly with age in all brain regions, while regional zinc concentrations became more homogeneous with age. Knockdown of the copper transporter Ctr1 reduced brain copper, but not iron or zinc, concentrations in a regionally-dependent manner. These findings demonstrate biometals in the brain change with age in a regionally-dependent manner. These data and associated formulae have implications for improving design and interpretation of a wide variety of studies in the C57BL/6 mouse.

Comparison of three magnetic resonance imaging measures of brain iron in healthy and cocaine use disorder participants

Several magnetic resonance imaging (MRI) measures for quantifying endogenous nonheme brain iron have been proposed. These correspond to distinct physical properties with varying sensitivities and specificities to iron. Moreover, they may depend not only on tissue iron concentration, but also on the intravoxel spatial pattern of iron deposition, which is complex in many brain regions. Here, the three MRI brain iron measures of R 2 * , magnetic field correlation (MFC), and magnetic susceptibility are compared in several deep gray matter regions for both healthy participants (HPs) and individuals with cocaine use disorder (CUD). Their concordance is assessed from their correlations with each other and their relative dependencies on age. In addition, associations between the iron measures and microstructure in adjacent white matter regions are investigated by calculating their correlations with diffusion MRI measures from the internal capsule, and associations with cognition are determined by using results from a battery of standardized tests relevant to CUD. It is found that all three iron measures are strongly correlated with each other for the considered gray matter regions, but with correlation coefficients substantially less than one indicating important differences. The age dependencies of all three measures are qualitatively similar in most regions, except for the red nucleus, where the susceptibility has a significantly stronger correlation with age than R 2 * . Weak to moderate correlations are seen for the iron measures with several of the diffusion and cognitive measures, with the strongest correlations being obtained for R 2 * . The iron measures differ little between the HP and CUD groups, although susceptibility is significantly lower in the red nucleus for the CUD group. For the comparisons made, the iron measures behave similarly in most respects, but with notable quantitative differences. It is suggested that these differences may be, in part, attributable to a higher sensitivity to the spatial pattern of iron deposition for R 2 * and MFC than for susceptibility. This is supported most strongly by a sharp contrast between the values of the iron measures in the globus pallidus relative to those in the red nucleus. The observed correlations of the iron measures with diffusion and cognitive scores point to possible connections between gray matter iron, white matter microstructure, and cognition.

Harmonic field extension for QSM with reduced spatial coverage using physics-informed generative adversarial network

Quantitative susceptibility mapping (QSM) is frequently employed in investigating brain iron related to brain development and diseases within deep gray matter (DGM). Nonetheless, the acquisition of whole-brain QSM data is time-intensive. An alternative approach, focusing the QSM specifically on areas of interest such as the DGM by reducing the field-of-view (FOV), can significantly decrease scan times. However, severe susceptibility value underestimations have been reported during QSM reconstruction with a limited FOV, largely attributable to artifacts from incorrect background field removal in the boundary region. This presents a considerable barrier to the clinical use of QSM with small spatial coverages using conventional methods alone. To mitigate the propagation of these errors, we proposed a harmonic field extension method based on a physics-informed generative adversarial network. Both quantitative and qualitative results demonstrate that our method outperforms conventional methods and delivers results comparable to those obtained with full FOV. Furthermore, we demonstrate the versatility of our method by applying it to data acquired prospectively with limited FOV and to data from patients with Parkinson's disease. The method has shown significant improvements in local field results, with QSM outcomes. In a clear illustration of its feasibility and effectiveness in real clinical environments, our proposed method addresses the prevalent issue of susceptibility underestimation in QSM with small spatial coverage.

Quantitative susceptibility mapping from basal ganglia and related structures: correlation with disease severity in progressive supranuclear palsy

OBJECTIVE

We examined whether mean magnetic susceptibility values from deep gray matter structures in patients with progressive supranuclear palsy (PSP) differed from those in patients with Parkinson's disease (PD) and healthy volunteers, and correlated with the PSP rating scale.

METHODS

Head of caudate nucleus, putamen, globus pallidus, substantia nigra and red nucleus were the regions of interest. Mean susceptibility values from these regions in PSP patients were estimated using quantitative susceptibility mapping. Correlations with clinical severity of disease as measured by the PSP rating scale were examined. The mean susceptibility values were also compared with those from healthy volunteers and age- and disease duration-matched patients with PD.

RESULTS

Data from 26 healthy volunteers, 26 patients with PD and 27 patients with PSP, were analysed. Patients with PSP had higher mean susceptibility values from all regions of interest when compared to both the other groups. The PSP rating scale scores correlated strongly with mean susceptibility values from the red nucleus and moderately with those from the putamen and substantia nigra. The scores did not correlate with mean susceptibility values from the caudate nucleus or globus pallidus. In patients with PD, the motor deficits correlated moderately with mean susceptibility values from substantia nigra.

CONCLUSIONS

In patients with PSP, mean susceptibility values indicating the severity of mineralization of basal ganglia and related structures correlate with disease severity, the correlation of red nucleus being the strongest. Further studies are warranted to explore whether mean susceptibility values could serve as biomarkers for PSP.

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.

Altered Iron and Microstructure in Huntington's Disease Subcortical Nuclei: Insight From 7T MRI

BACKGROUND

Pathophysiological changes of Huntington's disease (HD) can precede symptom onset by decades. Robust imaging biomarkers are needed to monitor HD progression, especially before the clinical onset.

PURPOSE

To investigate iron dysregulation and microstructure alterations in subcortical regions as HD imaging biomarkers, and to associate such alterations with motor and cognitive impairments.

STUDY TYPE

Prospective.

POPULATION

Fourteen individuals with premanifest HD (38.0 ± 11.0 years, 9 females; far-from-onset N = 6, near-onset N = 8), 21 manifest HD patients (49.1 ± 12.1 years, 11 females), and 33 age-matched healthy controls (43.9 ± 12.2 years, 17 females).

FIELD STRENGTH/SEQUENCE

7 T, T1 -weighted imaging, quantitative susceptibility mapping, and diffusion tensor imaging.

ASSESSMENT

Volume, susceptibility, fractional anisotropy (FA), and mean diffusivity (MD) within subcortical brain structures were compared across groups, used to establish HD classification models, and correlated to clinical measures and cognitive assessments.

STATISTICAL TESTS

Generalized linear model, multivariate logistic regression, receiver operating characteristics with the area under the curve (AUC), and likelihood ratio test comparing a volumetric model to one that also includes susceptibility and diffusion metrics, Wilcoxon paired signed-rank test, and Pearson's correlation. A P-value <0.05 after Benjamini-Hochberg correction was considered statistically significant.

RESULTS

Significantly higher striatal susceptibility and FA were found in premanifest and manifest HD preceding atrophy, even in far-from-onset premanifest HD compared to controls (putamen susceptibility: 0.027 ± 0.022 vs. 0.018 ± 0.013 ppm; FA: 0.358 ± 0.048 vs. 0.313 ± 0.039). The model with additional susceptibility, FA, and MD features showed higher AUC compared to volume features alone when differentiating premanifest HD from HC (0.83 vs. 0.66), and manifest from premanifest HD (0.94 vs. 0.83). Higher striatal susceptibility significantly correlated with cognitive deterioration in HD (executive function: r = -0.600; socioemotional function: r = -0.486).

DATA CONCLUSION

7 T MRI revealed iron dysregulation and microstructure alterations with HD progression, which could precede volume loss, provide added value to HD differentiation, and might be associated with cognitive changes.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Ferroptosis is Involved in the Pharmacological Effect of Ginsenoside

Ginsenoside is the principal active ingredient in ginseng. Several investigations have found that ginsenosides have anti-inflammatory, antioxidant, anti-apoptotic, anti-cancer, and antiallergic activities. Ferroptosis is an iron-dependent, non-apoptotic form of cell-regulated death caused by lipid peroxidation. Iron, lipid, and amino acid metabolism orchestrate the complex ferroptosis response through direct or indirect regulation of iron accumulation or lipid peroxidation. More and more research has demonstrated that ginsenoside impacts illnesses via ferroptosis, implying that ferroptosis might be employed as a novel target of ginsenoside for disease therapy. This article examines the molecular mechanism of ferroptosis as well as the current advancement of ginsenoside in influencing disorders via ferroptosis.

Iron content affects age group differences in associative learning-related fMRI activity

Brain regions accumulate different amounts of iron with age, with older adults having higher iron in the basal ganglia (globus pallidus, putamen, caudate) relative to the hippocampus. This has important implications for functional magnetic resonance imaging (fMRI) studies in aging as the presence of iron may influence both neuronal functioning as well as the measured fMRI (BOLD) signal, and these effects will vary across age groups and brain regions. To test this hypothesis, the current study examined the effect of iron on age group differences in task-related activity within each basal nuclei and the hippocampus. Twenty-eight younger and 22 older adults completed an associative learning task during fMRI acquisition. Iron content (QSM, R2*) was estimated from a multi-echo gradient echo sequence. As previously reported, older adults learned significantly less than younger adults and age group differences in iron content were largest in the basal ganglia (putamen, caudate). In the hippocampus (early task stage) and globus pallidus (late task stage), older adults had significantly higher learning-related activity than younger adults both before and after controlling for iron. In the putamen (late task stage), however, younger adults had significantly higher learning-related activity than older adults that was only seen after controlling for iron. These findings support the notion that age-related differences in iron influence both neuronal functioning and the measured fMRI signal in select basal nuclei. Moreover, previous fMRI studies in aging populations may have under-reported age group differences in task-related activity by not accounting for iron within these regions.

Quantitative susceptibility mapping in rats with minimal hepatic encephalopathy: Does iron overload aggravate cognitive impairment by promoting neuroinflammation?

BACKGROUND AND AIMS

Minimal hepatic encephalopathy (MHE) is a mild form of hepatic encephalopathy that lacks observable signs and symptoms. Nevertheless, MHE can cause neurocognitive dysfunction, although the neurobiological mechanisms are not fully understood. Here, the effects of hippocampal iron deposition on cognitive function and its role in MHE were investigated.

MATERIALS AND METHODS

Eighteen rats were assigned to experimental and control groups. MHE was induced by thioacetamide. Spatial memory and exploratory behavior were assessed by the Morris water and elevated plus mazes. Hippocampal susceptibility was measured by quantitative susceptibility mapping, iron deposition in the hippocampus and liver by Prussian blue staining, and inflammatory cytokine and ferritin levels in the hippocampus were measured by ELISA.

RESULTS

MHE rats showed impaired spatial memory and exploratory behavior (P < 0.05 for all parameters). The bilateral hippocampal susceptibility values were significantly raised in MHE rats, together with evidence of neuroinflammation (increased pro-inflammatory and reduced anti-inflammatory cytokine levels (all P < 0.05). Further analysis indicated good correlations between hippocampal susceptibility values with latency time and inflammatory cytokine levels in MHE but not in control rats.

CONCLUSION

MHE induced by thioacetamide was associated with hippocampal iron deposition and inflammation, suggesting that iron overload may be an important driver of neuroinflammatory responses.

Quantitative susceptibility mapping shows lower brain iron content in children with childhood epilepsy with centrotemporal spikes

PURPOSE

The dysregulation of brain iron homeostasis is closely relevant to a multitude of chronic neurological disorders. This study employed quantitative susceptibility mapping (QSM) to detect and compare whole-brain iron content between childhood epilepsy with centrotemporal spikes (CECTS) children and typically developing children.

MATERIALS AND METHODS

32 children with CECTS and 25 age- and gender-matched healthy children were enrolled. All participants were imaged with 3.0-T MRI to acquire the structural and susceptibility-weighted data. The susceptibility-weighted data were processed using STISuite toolbox to obtain QSM. The magnetic susceptibility difference between the two groups was compared using voxel-wise and region of interest methods. Multivariable linear regression, controlling for age, were employed to investigate the associations between the brain magnetic susceptibility and age at onset.

RESULTS

Lower magnetic susceptibility was mainly observed in sensory- and motor-related brain regions in children with CECTS, including bilateral middle frontal gyrus, supplementary motor area, midcingulate cortex, paracentral lobule and precentral gyrus, the magnetic susceptibility of right paracentral lobule, right precuneus and left supplementary motor area were found to have positive correlation with the age at onset.

CONCLUSIONS

This study suggests that the potential iron deficiency in certain brain regions is associated with CECTS, which might be helpful for further illumination of potential pathogenesis mechanism of CECTS.

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.

Quantitative Susceptibility Mapping Changes Relate to Gait Issues in Parkinson's Disease

BACKGROUND

Quantitative susceptibility mapping (QSM) demonstrates elevated iron content in Parkinson's disease (PD) patients within the basal ganglia, though it has infrequently been studied in relation to gait difficulties including freezing of gait (FOG). Our purpose was to relate QSM of basal ganglia and extra-basal ganglia structures with qualitative and quantitative gait measures in PD.

METHODS

This case-control study included PD and cognitively unimpaired (CU) participants from the Comprehensive Assessment of Neurodegeneration and Dementia study. Whole brain QSM was acquired at 3T. Region of interests (ROIs) were drawn blinded manually in the caudate nucleus, putamen, globus pallidus, pulvinar nucleus of the thalamus, red nucleus, substantia nigra, and dentate nucleus. Susceptibilities of ROIs were compared between PD and CU. Items from the FOG questionnaire and quantitative gait measures from PD participants were compared to susceptibilities.

RESULTS

Twenty-nine participants with PD and 27 CU participants were included. There was no difference in susceptibility values in any ROI when comparing CU versus PD (p > 0.05 for all). PD participants with gait impairment (n = 23) had significantly higher susceptibility in the putamen (p = 0.008), red nucleus (p = 0.01), and caudate nucleus (p = 0.03) compared to those without gait impairment (n = 6). PD participants with FOG (n = 12) had significantly higher susceptibility in the globus pallidus (p = 0.03) compared to those without FOG (n = 17). Among quantitative gait measures, only stride time variability was significantly different between those with and without FOG (p = 0.04).

CONCLUSION

Susceptibilities in basal ganglia and extra-basal ganglia structures are related to qualitative measures of gait impairment and FOG in PD.

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.

Brain iron deposition is positively correlated with cognitive impairment in patients with chronic cerebral hypoperfusion: a MRI susceptibility mapping study

AIM

To investigate the relationship of brain iron deposition with cognitive impairment in patients with chronic cerebral hypoperfusion (CHP).

MATERIALS AND METHODS

Brain iron deposition was detected using quantitative susceptibility mapping (QSM), and cognitive function by neuropsychological tests including the Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADLs), and verbal fluency tests in a total of 40 participants, 23 with CHP and 17 age- and sex-matched healthy participants without CHP (controls).

RESULTS

The neuropsychological tests revealed that cognitive impairment (p<0.05) and susceptibility values (p<0.05) of the bilateral hippocampus (HP) and substantia nigra (SN) in CHP patients were significantly higher than those of the controls. The susceptibility values of bilateral HP and left putamen correlated closely with the scores of neuropsychological tests in the CHP patients (p<0.05, r2>0.1). The susceptibility values in the left putamen and bilateral HP were significantly higher in CHP patients with mild cognitive impairment (MCI; n=8) than those of CHP patients without MCI (n=15; p<0.05).

CONCLUSIONS

The present findings indicated that brain iron deposition in specific areas may be responsible for the cognitive impairment in CHP patients, and that QSM is a useful tool to determine brain iron, predicting cognitive impairment in CHP patients.

Effect of corticosubcortical iron deposition on dysfunction in CADASIL is mediated by white matter microstructural damage

Iron dysregulation may attenuate cognitive performance in patients with CADASIL. However, the underlying pathophysiological mechanisms remain incompletely understood. Whether white matter microstructural changes mediate these processes is largely unclear. In the present study, 30 cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) patients were confirmed via genetic analysis and 30 sex- and age-matched healthy controls underwent multimodal MRI examinations and neuropsychological assessments. Quantitative susceptibility mapping and peak width of skeletonized mean diffusivity (PSMD) were analyzed. Mediation effect analysis was performed to explore the interrelationship between iron deposition, white matter microstructural changes and cognitive deficits in CADASIL. Cognitive deterioration was most affected in memory and executive function, followed by attention and working memory in CADASIL. Excessive iron in the temporal-precuneus pathway and deep gray matter specific to CADASIL were identified. Mediation analysis further revealed that PSMD mediated the relationship between iron concentration and cognitive profile in CADASIL. The present findings provide a new perspective on iron deposition in the corticosubcortical circuit and its contribution to disease-related selective cognitive decline, in which iron concentration may affect cognition by white matter microstructural changes in CADASIL.

Technical note: Improved differentiation of calcification from hemosiderin using paramagnetic- and diamagnetic-specific magnetic resonance susceptibility weighted imaging (p-SWI, d-SWI)

INTRODUCTION

Differentiation of calcification and calcium-containing tissue from blood products remains challenging using magnetic resonance imaging (MRI). We developed a novel post-processing algorithm which creates both paramagnetic- and diamagnetic-specific SWI images generated from T2* weighted images using distinct "positive" and "negative" phase masks.

METHODS

10 patients who had undergone clinical MRI scanning of the brain with a rapid echo planar based T2*-weighted EPI-GRE pulse sequence with evidence for either hemosiderin and/or calcifications were retrospectively identified. Complex raw k-space data from individual imaging coils were then extracted, reconstructed, and appropriately combined to produce magnitude and phase images using a phase preserving method. The final reconstructed images included the T2* EPI-GRE magnitude images, p-SWI and d-SWI images. Filtered phase images were also available for review. Correlation with CT scans and MR imaging appearance over time corroborated the composition of the voxels.

RESULTS

Differential "blooming" of diamagnetic and paramagnetic foci was readily identified on the corresponding p-SWI and d-SWI images and provided fast and reliable visual differentiation of diamagnetic from paramagnetic susceptibility effects by ascertaining which of the two images depicted the greatest "blooming" effect. Correlation with the available filtered phase maps was not necessary for differentiation of paramagnetic from diamagnetic image components.

CONCLUSION

Clinical interpretation of SWI images can be further enhanced by creating specific p-SWI and d-SWI image pairs which contain greater visual information than the combination of standard p-SWI images and phase image.

Quantitative susceptibility mapping using multi-channel convolutional neural networks with dipole-adaptive multi-frequency inputs

Quantitative susceptibility mapping (QSM) quantifies the distribution of magnetic susceptibility and shows great potential in assessing tissue contents such as iron, myelin, and calcium in numerous brain diseases. The accuracy of QSM reconstruction was challenged by an ill-posed field-to-susceptibility inversion problem, which is related to the impaired information near the zero-frequency response of the dipole kernel. Recently, deep learning methods demonstrated great capability in improving the accuracy and efficiency of QSM reconstruction. However, the construction of neural networks in most deep learning-based QSM methods did not take the intrinsic nature of the dipole kernel into account. In this study, we propose a dipole kernel-adaptive multi-channel convolutional neural network (DIAM-CNN) method for the dipole inversion problem in QSM. DIAM-CNN first divided the original tissue field into high-fidelity and low-fidelity components by thresholding the dipole kernel in the frequency domain, and it then inputs the two components as additional channels into a multichannel 3D Unet. QSM maps from the calculation of susceptibility through multiple orientation sampling (COSMOS) were used as training labels and evaluation reference. DIAM-CNN was compared with two conventional model-based methods [morphology enabled dipole inversion (MEDI) and improved sparse linear equation and least squares (iLSQR) and one deep learning method (QSMnet)]. High-frequency error norm (HFEN), peak signal-to-noise-ratio (PSNR), normalized root mean squared error (NRMSE), and the structural similarity index (SSIM) were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the DIAM-CNN results had superior image quality to those of the MEDI, iLSQR, or QSMnet results. Experiments on data with simulated hemorrhagic lesions demonstrated that DIAM-CNN produced fewer shadow artifacts around the bleeding lesion than the compared methods. This study demonstrates that the incorporation of dipole-related knowledge into the network construction has a potential to improve deep learning-based QSM reconstruction.

Multimodal comparisons of QSM and PET in neurodegeneration and aging

Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.

APART-QSM: an improved sub-voxel quantitative susceptibility mapping for susceptibility source separation using an iterative data fitting method

The brain tissue phase contrast in MRI sequences reflects the spatial distributions of multiple substances, such as iron, myelin, calcium, and proteins. These substances with paramagnetic and diamagnetic susceptibilities often colocalize in one voxel in brain regions. Both opposing susceptibilities play vital roles in brain development and neurodegenerative diseases. Conventional QSM methods only provide voxel-averaged susceptibility value and cannot disentangle intravoxel susceptibilities with opposite signs. Advanced susceptibility imaging methods have been recently developed to distinguish the contributions of opposing susceptibility sources for QSM. The basic concept of separating paramagnetic and diamagnetic susceptibility proportions is to include the relaxation rate R₂^* with R₂^' in QSM. The magnitude decay kernel, describing the proportionality coefficient between R₂^' and susceptibility, is an essential reconstruction coefficient for QSM separation methods. In this study, we proposed a more comprehensive complex signal model that describes the relationship between 3D GRE signal and the contributions of paramagnetic and diamagnetic susceptibility to the frequency shift and R₂^* relaxation. The algorithm is implemented as a constrained minimization problem in which the voxel-wise magnitude decay kernel and sub-voxel susceptibilities are determined alternately in each iteration until convergence. The calculated voxel-wise magnitude decay kernel could realistically model the relationship between the R₂^' relaxation and the volume susceptibility. Thus, the proposed method effectively prevents the errors of the magnitude decay kernel from propagating to the final susceptibility separation reconstruction. Phantom studies, ex vivo macaque brain experiments, and in vivo human brain imaging studies were conducted to evaluate the ability of the proposed method to distinguish paramagnetic and diamagnetic susceptibility sources. The results demonstrate that the proposed method provides state-of-the-art performances for quantifying brain iron and myelin compared to previous QSM separation methods. Our results show that the proposed method has the potential to simultaneously quantify whole brain iron and myelin during brain development and aging. The proposed model was also deployed with multiple-orientation complex GRE data input measurements, resulting in high-quality QSM separation maps with more faithful tissue delineation between brain structures compared to those reconstructed by single-orientation QSM separation methods.

Age-related differences of cerebellar cortex and nuclei: MRI findings in healthy controls and its application to spinocerebellar ataxia (SCA6) patients

Understanding cerebellar alterations due to healthy aging provides a reference point against which pathological findings in late-onset disease, for example spinocerebellar ataxia type 6 (SCA6), can be contrasted. In the present study, we investigated the impact of aging on the cerebellar nuclei and cerebellar cortex in 109 healthy controls (age range: 16 - 78 years) using 3 Tesla magnetic resonance imaging (MRI). Findings were compared with 25 SCA6 patients (age range: 38 - 78 years). A subset of 16 SCA6 (included: 14) patients and 50 controls (included: 45) received an additional MRI scan at 7 Tesla and were re-scanned after one year. MRI included T1-weighted, T2-weighted FLAIR, and multi-echo T2*-weighted imaging. The T2*-weighted phase images were converted to quantitative susceptibility maps (QSM). Since the cerebellar nuclei are characterized by elevated iron content with respect to their surroundings, two independent raters manually outlined them on the susceptibility maps. T1-weighted images acquired at 3T were utilized to automatically identify the cerebellar gray matter (GM) volume. Linear correlations revealed significant atrophy of the cerebellum due to tissue loss of cerebellar cortical GM in healthy controls with increasing age. Reduction of the cerebellar GM was substantially stronger in SCA6 patients. The volume of the dentate nuclei did not exhibit a significant relationship with age, at least in the age range between 18 and 78 years, whereas mean susceptibilities of the dentate nuclei increased with age. As previously shown, the dentate nuclei volumes were smaller and magnetic susceptibilities were lower in SCA6 patients compared to age- and sex-matched controls. The significant dentate volume loss in SCA6 patients could also be confirmed with 7T MRI. Linear mixed effects models and individual paired t-tests accounting for multiple comparisons revealed no statistical significant change in volume and susceptibility of the dentate nuclei after one year in neither patients nor controls. Importantly, dentate volumes were more sensitive to differentiate between SCA6 (Cohen's d = 3.02) and matched controls than the cerebellar cortex volume (d = 2.04). In addition to age-related decline of the cerebellar cortex and atrophy in SCA6 patients, age-related increase of susceptibility of the dentate nuclei was found in controls, whereas dentate volume and susceptibility was significantly decreased in SCA6 patients. Because no significant changes of any of these parameters was found at follow-up, these measures do not allow to monitor disease progression at short intervals.

Increased iron deposition in nucleus accumbens associated with disease progression and chronicity in migraine

BACKGROUND

Migraine is one of the world's most prevalent and disabling diseases. Despite huge advances in neuroimaging research, more valuable neuroimaging markers are still urgently needed to provide important insights into the brain mechanisms that underlie migraine symptoms. We therefore aim to investigate the regional iron deposition in subcortical nuclei of migraineurs as compared to controls and its association with migraine-related pathophysiological assessments.

METHODS

A total of 200 migraineurs (56 chronic migraine [CM], 144 episodic migraine [EM]) and 41 matched controls were recruited. All subjects underwent MRI and clinical variables including frequency/duration of migraine, intensity of migraine, 6-item Headache Impact Test (HIT-6), Migraine Disability Assessment (MIDAS), and Pittsburgh Sleep Quality Index (PSQI) were recorded. Quantitative susceptibility mapping was employed to quantify the regional iron content in subcortical regions. Associations between clinical variables and regional iron deposition were studied as well.

RESULTS

Increased iron deposition in the putamen, caudate, and nucleus accumbens (NAC) was observed in migraineurs more than controls. Meanwhile, patients with CM had a significantly higher volume of iron deposits compared to EM in multiple subcortical nuclei, especially in NAC. Volume of iron in NAC can be used to distinguish patients with CM from EM with a sensitivity of 85.45% and specificity of 71.53%. As the most valuable neuroimaging markers in all of the subcortical nuclei, higher iron deposition in NAC was significantly associated with disease progression, and higher HIT-6, MIDAS, and PSQI.

CONCLUSIONS

These findings provide evidence that iron deposition in NAC may be a biomarker for migraine chronicity and migraine-related dysfunctions, thus may help to understand the underlying vascular and neural mechanisms of migraine.

TRIAL REGISTRATION

ClinicalTrials.gov, number NCT04939922.

Age-dependent changes in brain iron deposition and volume in deep gray matter nuclei using quantitative susceptibility mapping

BACKGROUND

Microstructural changes in deep gray matter (DGM) nuclei are related to physiological behavior, cognition, and memory. Therefore, it is critical to study age-dependent trajectories of biomarkers in DGM nuclei for understanding brain development and aging, as well as predicting cognitive or neurodegenerative diseases.

OBJECTIVES

We aimed to (1) characterize age-dependent trajectories of mean susceptibility, adjusted volume, and total iron content simultaneously in DGM nuclei using quantitative susceptibility mapping (QSM); (2) examine potential contributions of sex related effects to the different age-dependence trajectories of volume and iron deposition; and (3) evaluate the ability of brain age prediction by combining mean magnetic susceptibility and volume of DGM nuclei.

METHODS

Magnetic susceptibilities and volumetric values of DGM nuclei were obtained from 220 healthy participants (aged 10-70 years) scanned on a 3T MRI system. Regions of interest (ROIs) were drawn manually on the QSM images. Univariate regression analysis between age and each of the MRI measurements in a single ROI was performed. Pearson correlation coefficients were calculated between magnetic susceptibility and adjusted volume in a single ROI. The statistical significance of sex differences in age-dependent trajectories of magnetic susceptibilities and adjusted volumes were determined using one-way ANCOVA. Multiple regression analysis was used to evaluate the ability to estimate brain age using a combination of the mean susceptibilities and adjusted volumes in multiple DGM nuclei.

RESULTS

Mean susceptibility and total iron content increased linearly, quadratically, or exponentially with age in all six DGM nuclei. Negative linear correlation was observed between adjusted volume and age in the head of the caudate nucleus (CN; R² = 0.196, p < 0.001). Quadratic relationships were found between adjusted volume and age in the putamen (PUT; R² = 0.335, p < 0.001), globus pallidus (GP; R² = 0.062, p = 0.001), and dentate nucleus (DN; R² = 0.077, p < 0.001). Males had higher mean magnetic susceptibility than females in the PUT (p = 0.001), red nucleus (RN; p = 0.002), and substantia nigra (SN; p < 0.001). Adjusted volumes of the CN (p < 0.001), PUT (p = 0.030), GP (p = 0.007), SN (p = 0.021), and DN (p < 0.001) were higher in females than those in males throughout the entire age range (10-70 years old). The total iron content of females was higher than that of males in the CN (p < 0.001), but lower than that of males in the PUT (p = 0.014) and RN (p = 0.043) throughout the entire age range (10-70 years old). Multiple regression analyses revealed that the combination of the mean susceptibility value of the PUT, and the volumes of the CN and PUT had the strongest associations with brain age (R² = 0.586).

CONCLUSIONS

QSM can be used to simultaneously investigate age- and sex- dependent changes in magnetic susceptibility and volume of DGM nuclei, thus enabling a comprehensive understanding of the developmental trajectories of iron accumulation and volume in DGM nuclei during brain development and aging.

Autolysis Affects the Iron Cargo of Ferritins in Neurons and Glial Cells at Different Rates in the Human Brain

Iron is known to accumulate in neurological disorders, so a careful balance of the iron concentration is essential for healthy brain functioning. An imbalance in iron homeostasis could arise due to the dysfunction of proteins involved in iron homeostasis. Here, we focus on ferritin-the primary iron storage protein of the brain. In this study, we aimed to improve a method to measure ferritin-bound iron in the human post-mortem brain, and to discern its distribution in particular cell types and brain regions. Though it is known that glial cells and neurons differ in their ferritin concentration, the change in the number and distribution of iron-filled ferritin cores between different cell types during autolysis has not been revealed yet. Here, we show the cellular and region-wide distribution of ferritin in the human brain using state-of-the-art analytical electron microscopy. We validated the concentration of iron-filled ferritin cores to the absolute iron concentration measured by quantitative MRI and inductively coupled plasma mass spectrometry. We show that ferritins lose iron from their cores with the progression of autolysis whereas the overall iron concentrations were unaffected. Although the highest concentration of ferritin was found in glial cells, as the total ferritin concentration increased in a patient, ferritin accumulated more in neurons than in glial cells. Summed up, our findings point out the unique behaviour of neurons in storing iron during autolysis and explain the differences between the absolute iron concentrations and iron-filled ferritin in a cell-type-dependent manner in the human brain. The rate of loss of the iron-filled ferritin cores during autolysis is higher in neurons than in glial cells.

Utility of quantitative MRI metrics in brain ageing research

The advent of new, advanced quantitative MRI metrics allows for in vivo evaluation of multiple biological processes highly relevant for ageing. The presented study combines several MRI parameters hypothesised to detect distinct biological characteristics as myelin density, cellularity, cellular membrane integrity and iron concentration. 116 healthy volunteers, continuously distributed over the whole adult age span, underwent a multi-modal MRI protocol acquisition. Scatterplots of individual MRI metrics revealed that certain MRI protocols offer much higher sensitivity to early adulthood changes while plateauing in higher age (e.g., global functional connectivity in cerebral cortex or orientation dispersion index in white matter), while other MRI metrics provided reverse ability—stable levels in young adulthood with sharp changes with rising age (e.g., T1ρ and T2ρ). Nonetheless, despite the previously published validations of specificity towards microstructural biology based on cytoarchitectonic maps in healthy population or alterations in certain pathologies, several metrics previously hypothesised to be selective to common measures failed to show similar scatterplot distributions, pointing to further confounding factors directly related to age. Furthermore, other metrics, previously shown to detect different biological characteristics, exhibited substantial intercorrelations, be it due to the nature of the MRI protocol itself or co-dependence of relevant biological microstructural processes. All in all, the presented study provides a unique basis for the design and choice of relevant MRI parameters depending on the age group of interest. Furthermore, it calls for caution in simplistic biological inferences in ageing based on one simple MRI metric, even though previously validated under other conditions. Complex multi-modal approaches combining several metrics to extract the shared subcomponent will be necessary to achieve the desired goal of histological MRI.

What Do Randomized Controlled Trials Inform Us About Potential Disease-Modifying Strategies for Parkinson's Disease?

Research advances have shed new insight into cellular pathways contributing to PD pathogenesis and offer increasingly compelling therapeutic targets. In this review, we made a broad survey of the published literature that report possible disease-modifying effects on PD. While there are many studies that demonstrate benefits for various therapies for PD in animal and human studies, we confined our search to human "randomised controlled trials" and with the key words "neuroprotection" or "disease-modifying". It is hoped that through studying the results of these trials, we might clarify possible mechanisms that underlie idiopathic PD. This contrasts with studying the effect of pathophysiology of familial PD, which could be carried out by gene knockouts and animal models. Randomised controlled trials indicate promising effects of MAO-B inhibitors, dopamine agonists, NMDA receptor antagonists, metabotropic glutamate receptor antagonists, therapies related to improving glucose utilization and energy production, therapies related to reduction of excitotoxicity and oxidative stress, statin use, therapies related to iron chelation, therapies related to the use of phytochemicals, and therapies related to physical exercise and brain reward pathway on slowing PD progression. Cumulatively, these approaches fall into two categories: direct enhancement of dopaminergic signalling, and reduction of neurodegeneration. Overlaps between the two categories result in challenges in distinguishing between symptomatic versus disease-modifying effects with current clinical trial designs. Nevertheless, a broad-based approach allows us to consider all possible therapeutic avenues which may be neuroprotective. While the traditional standard of care focuses on symptomatic management with dopaminergic drugs, more recent approaches suggest ways to preserve dopaminergic neurons by attenuating excitotoxicity and oxidative stress.

Cell-Specific Dysregulation of Iron and Oxygen Homeostasis as a Novel Pathophysiology in PSP

OBJECTIVE

Progressive supranuclear palsy (PSP) is a 4R-tauopathy showing heterogeneous tau cytopathology commencing in the globus pallidus (GP) and the substantia nigra (SN), regions also associated with age-related iron accumulation. Abnormal iron levels have been extensively associated with tau pathology in neurodegenerative brains, however, its role in PSP pathogenesis remains yet unknown. We perform the first cell type-specific evaluation of PSP iron homeostasis and the closely related oxygen homeostasis, in relation to tau pathology in human postmortem PSP brains.

METHODS

In brain regions vulnerable to PSP pathology (GP, SN, and putamen), we visualized iron deposition in tau-affected and unaffected neurons, astroglia, oligodendrocytes, and microglia, using a combination of iron staining with immunolabelling. To further explore molecular pathways underlying our observations, we examined the expression of key iron and oxygen homeostasis mRNA transcripts and proteins.

RESULTS

We found astrocytes as the major cell type accumulating iron in the early affected regions of PSP, highly associated with cellular tau pathology. The same regions are affected by dysregulated expression of alpha and beta hemoglobin and neuroglobin showing contrasting patterns. We discovered changes in iron and oxygen homeostasis-related gene expression associated with aging of the brain, and identified dysregulated expression of rare neurodegeneration with brain iron accumulation (NBIA) genes associated with tau pathology to distinguish PSP from the healthy aging brain.

INTERPRETATION

We present novel aspects of PSP pathophysiology highlighting an overlap with NBIA pathways. Our findings reveal potential novel targets for therapy development and have implications beyond PSP for other iron-associated neurodegenerative diseases. ANN NEUROL 2023;93:431-445.

Visualizing the deep cerebellar nuclei using quantitative susceptibility mapping: An application in healthy controls, Parkinson's disease patients and essential tremor patients

The visualization and identification of the deep cerebellar nuclei (DCN) (dentate [DN], interposed [IN] and fastigial nuclei [FN]) are particularly challenging. We aimed to visualize the DCN using quantitative susceptibility mapping (QSM), predict the contrast differences between QSM and T2* weighted imaging, and compare the DCN volume and susceptibility in movement disorder populations and healthy controls (HCs). Seventy-one Parkinson's disease (PD) patients, 39 essential tremor patients, and 80 HCs were enrolled. The PD patients were subdivided into tremor dominant (TD) and postural instability/gait difficulty (PIGD) groups. A 3D strategically acquired gradient echo MR imaging protocol was used for each subject to obtain the QSM data. Regions of interest were drawn manually on the QSM data to calculate the volume and susceptibility. Correlation analysis between the susceptibility and either age or volume was performed and the intergroup differences of the volume and magnetic susceptibility in all the DCN structures were evaluated. For the most part, all the DCN structures were clearly visualized on the QSM data. The susceptibility increased as a function of volume for both the HC group and disease groups in the DN and IN (p < .001) but not the FN (p = .74). Only the volume of the FN in the TD-PD group was higher than that in the HCs (p = .012), otherwise, the volume and susceptibility among these four groups did not differ significantly. In conclusion, QSM provides clear visualization of the DCN structures. The results for the volume and susceptibility of the DCN can be used as baseline references in future studies of movement disorders.

Peripheral and Central Iron Measures in Alcohol Use Disorder and Aging: A Quantitative Susceptibility Mapping Pilot Study

Chronic excessive alcohol use has neurotoxic effects, which may contribute to cognitive decline and the risk of early-onset dementia. Elevated peripheral iron levels have been reported in individuals with alcohol use disorder (AUD), but its association with brain iron loading has not been explored. We evaluated whether (1) serum and brain iron loading are higher in individuals with AUD than non-dependent healthy controls and (2) serum and brain iron loading increase with age. A fasting serum iron panel was obtained and a magnetic resonance imaging scan with quantitative susceptibility mapping (QSM) was used to quantify brain iron concentrations. Although serum ferritin levels were higher in the AUD group than in controls, whole-brain iron susceptibility did not differ between groups. Voxel-wise QSM analyses revealed higher susceptibility in a cluster in the left globus pallidus in individuals with AUD than controls. Whole-brain iron increased with age and voxel-wise QSM indicated higher susceptibility with age in various brain areas including the basal ganglia. This is the first study to analyze both serum and brain iron loading in individuals with AUD. Larger studies are needed to examine the effects of alcohol use on iron loading and its associations with alcohol use severity, structural and functional brain changes, and alcohol-induced cognitive impairments.

Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach

BACKGROUND AND PURPOSE

Early diagnosis of Parkinson's disease (PD) is still a clinical challenge. Most previous studies using manual or semi-automated methods for segmenting the substantia nigra (SN) are time-consuming and, despite raters being well-trained, individual variation can be significant. In this study, we used a template-based, automatic, SN subregion segmentation pipeline to detect the neuromelanin (NM) and iron features in the SN and SN pars compacta (SNpc) derived from a single 3D magnetization transfer contrast (MTC) gradient echo (GRE) sequence in an attempt to develop a comprehensive imaging biomarker that could be used to diagnose PD.

MATERIALS AND METHODS

A total of 100 PD patients and 100 age- and sex-matched healthy controls (HCs) were imaged on a 3T scanner. NM-based SN (SN_NM) boundaries and iron-based SN (SN_QSM) boundaries and their overlap region (representing the SNpc) were delineated automatically using a template-based SN subregion segmentation approach based on quantitative susceptibility mapping (QSM) and NM images derived from the same MTC-GRE sequence. All PD and HC subjects were evaluated for the nigrosome-1 (N1) sign by two raters independently. Receiver Operating Characteristic (ROC) analyses were performed to evaluate the utility of SN_NM volume, SN_QSM volume, SNpc volume and iron content with a variety of thresholds as well as the N1 sign in diagnosing PD. Correlation analyses were performed to study the relationship between these imaging measures and the clinical scales in PD.

RESULTS

In this study, we verified the value of the fully automatic template based midbrain deep gray matter mapping approach in differentiating PD patients from HCs. The automatic segmentation of the SN in PD patients led to satisfactory DICE similarity coefficients and volume ratio (VR) values of 0.81 and 1.17 for the SN_NM, and 0.87 and 1.05 for the SN_QSM, respectively. For the HC group, the average DICE similarity coefficients and VR values were 0.85 and 0.94 for the SN_NM, and 0.87 and 0.96 for the SN_QSM, respectively. The SN_QSM volume tended to decrease with age for both the PD and HC groups but was more severe for the PD group. For diagnosing PD, the N1 sign performed reasonably well by itself (Area Under the Curve (AUC) = 0.783). However, combining the N1 sign with the other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an improved diagnosis of PD with an AUC as high as 0.947 (using an SN threshold of 50ppb and an NM threshold of 0.15). Finally, the SN_QSM volume showed a negative correlation with the MDS-UPDRS III (R² = 0.1, p = 0.036) and the Hoehn and Yahr scale (R² = 0.04, p = 0.013) in PD patients.

CONCLUSION

In summary, this fully automatic template based deep gray matter mapping approach performs well in the segmentation of the SN and its subregions for not only HCs but also PD patients with SN degeneration. The combination of the N1 sign with other quantitative measures (SN_NM volume, SN_QSM volume, SNpc volume and iron content) resulted in an AUC of 0.947 and provided a comprehensive set of imaging biomarkers that, potentially, could be used to diagnose PD clinically.

Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine

OBJECTIVES

The objective of this longitudinal study was to determine whether brain iron accumulation, measured using magnetic resonance imaging magnetic transverse relaxation rates (T2*), is associated with response to erenumab for the treatment of migraine.

METHODS

Participants (n = 28) with migraine, diagnosed using international classification of headache disorders 3rd edition criteria, were eligible if they had six to 25 migraine days during a four-week headache diary run-in phase. Participants received two treatments with 140 mg erenumab, one immediately following the pre-treatment run-in phase and a second treatment four weeks later. T2* data were collected immediately following the pre-treatment phase, and at two weeks and eight weeks following the first erenumab treatment. Patients were classified as erenumab responders if their migraine-day frequency at five-to-eight weeks post-initial treatment was reduced by at least 50% compared to the pre-treatment run-in phase. A longitudinal Sandwich estimator approach was used to compare longitudinal group differences (responders vs non-responders) in T2* values, associated with iron accumulation. Group visit effects were calculated with a significance threshold of p = 0.005 and cluster forming threshold of 250 voxels. T2* values of 19 healthy controls were used for a reference. The average of each significant region was compared between groups and visits with Bonferroni corrections for multiple comparisons with significance defined as p < 0.05.

RESULTS

Pre- and post-treatment longitudinal imaging data were available from 28 participants with migraine for a total of 79 quantitative T2* images. Average subject age was 42 ± 13 years (25 female, three male). Of the 28 subjects studied, 53.6% were erenumab responders. Comparing longitudinal T2* between erenumab responders vs non-responders yielded two comparisons which survived the significance threshold of p < 0.05 after correction for multiple comparisons: the difference at eight weeks between the erenumab-responders and non-responders in the periaqueductal gray (mean ± standard error; responders 43 ± 1 ms vs non-responders 32.5 ± 1 ms, p = 0.002) and the anterior cingulate cortex (mean ± standard error; responders 50 ± 1 ms vs non-responders 40 ± 1 ms, p = 0.01).

CONCLUSIONS

Erenumab response is associated with higher T2* in the periaqueductal gray and anterior cingulate cortex, regions that participate in pain processing and modulation. T2* differences between erenumab responders vs non-responders, a measure of brain iron accumulation, are seen at eight weeks post-treatment. Less iron accumulation in the periaqueductal gray and anterior cingulate cortex might play a role in the therapeutic mechanisms of migraine reduction associated with erenumab.

The Roles of Iron and Ferroptosis in Human Chronic Diseases

Ferroptosis, an iron-dependent novel type of cell death, has been characterized as an excessive accumulation of lipid peroxides and reactive oxygen species. A growing number of studies demonstrate that ferroptosis not only plays an important role in the pathogenesis and progression of chronic diseases, but also functions differently in different diseases. As a double-edged sword, activation of ferroptosis could potently inhibit tumor growth and increase sensitivity to chemotherapy and immunotherapy in various cancer settings. Therefore, the development of more efficacious ferroptosis agonists or inhibitors remains the mainstay of ferroptosis-targeting strategy for cancer therapeutics or cardiovascular and cerebrovascular diseases and neurodegenerative diseases therapeutics.

A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex

Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.

Comparison of quantitative susceptibility mapping methods for iron-sensitive susceptibility imaging at 7T: An evaluation in healthy subjects and patients with Huntington's disease

Quantitative susceptibility mapping (QSM) is a promising tool for investigating iron dysregulation in neurodegenerative diseases, including Huntington's disease (HD). Many diverse methods have been proposed to generate accurate and robust QSM images. In this study, we evaluated the performance of different dipole inversion algorithms for iron-sensitive susceptibility imaging at 7T on healthy subjects of a large age range and patients with HD. We compared an iterative least-squares-based method (iLSQR), iterative methods that use regularization, single-step approaches, and deep learning-based techniques. Their performance was evaluated by comparing: (1) deviations from a multiple-orientation QSM reference; (2) visual appearance of QSM maps and the presence of artifacts; (3) susceptibility in subcortical brain regions with age; (4) regional brain susceptibility with published postmortem brain iron quantification; and (5) susceptibility in HD-affected basal ganglia regions between HD subjects and healthy controls. We found that single-step QSM methods with either total variation or total generalized variation constraints (SSTV/SSTGV) and the single-step deep learning method iQSM generally provided the best performance in terms of correlation with iron deposition and were better at differentiating between healthy controls and premanifest HD individuals, while deep learning QSM methods trained with multiple-orientation susceptibility data created QSM maps that were most similar to the multiple orientation reference and with the best visual scores.

Constructing a prognostic risk model for Alzheimer's disease based on ferroptosis

Introduction

The aim of this study is to establish a prognostic risk model based on ferroptosis to prognosticate the severity of Alzheimer's disease (AD) through gene expression changes.

Methods

The GSE138260 dataset was initially downloaded from the Gene expression Omnibus database. The ssGSEA algorithm was used to evaluate the immune infiltration of 28 kinds of immune cells in 36 samples. The up-regulated immune cells were divided into Cluster 1 group and Cluster 2 group, and the differences were analyzed. The LASSO regression analysis was used to establish the optimal scoring model. Cell Counting Kit-8 and Real Time Quantitative PCR were used to verify the effect of different concentrations of Aβ_1-42 on the expression profile of representative genes in vitro.

Results

Based on the differential expression analysis, there were 14 up-regulated genes and 18 down-regulated genes between the control group and Cluster 1 group. Cluster 1 and Cluster 2 groups were differentially analyzed, and 50 up-regulated genes and 101 down-regulated genes were obtained. Finally, nine common differential genes were selected to establish the optimal scoring model. In vitro, CCK-8 experiments showed that the survival rate of cells decreased significantly with the increase of Aβ_1-42 concentration compared with the control group. Moreover, RT-qPCR showed that with the increase of Aβ_1-42 concentration, the expression of POR decreased first and then increased; RUFY3 was firstly increased and then decreased.

Discussion

The establishment of this research model can help clinicians make decisions on the severity of AD, thus providing better guidance for the clinical treatment of Alzheimer's disease.

Incomplete spectrum QSM using support information

Introduction

Reconstructing a bounded object from incomplete k-space data is a well posed problem, and it was recently shown that this incomplete spectrum approach can be used to reconstruct undersampled MRI images with similar quality to compressed sensing approaches. Here, we apply this incomplete spectrum approach to the field-to-source inverse problem encountered in quantitative magnetic susceptibility mapping (QSM). The field-to-source problem is an ill-posed problem because of conical regions in frequency space where the dipole kernel is zero or very small, which leads to the kernel's inverse being ill-defined. These "ill-posed" regions typically lead to streaking artifacts in QSM reconstructions. In contrast to compressed sensing, our approach relies on knowledge of the image-space support, more commonly referred to as the mask, of our object as well as the region in k-space with ill-defined values. In the QSM case, this mask is usually available, as it is required for most QSM background field removal and reconstruction methods.

Methods

We tuned the incomplete spectrum method (mask and band-limit) for QSM on a simulated dataset from the most recent QSM challenge and validated the QSM reconstruction results on brain images acquired in five healthy volunteers, comparing incomplete spectrum QSM to current state-of-the art-methods: FANSI, nonlinear dipole inversion, and conventional thresholded k-space division.

Results

Without additional regularization, incomplete spectrum QSM performs slightly better than direct QSM reconstruction methods such as thresholded k-space division (PSNR of 39.9 vs. 39.4 of TKD on a simulated dataset) and provides susceptibility values in key iron-rich regions similar or slightly lower than state-of-the-art algorithms, but did not improve the PSNR in comparison to FANSI or nonlinear dipole inversion. With added (ℓ1-wavelet based) regularization the new approach produces results similar to compressed sensing based reconstructions (at sufficiently high levels of regularization).

Discussion

Incomplete spectrum QSM provides a new approach to handle the "ill-posed" regions in the frequency-space data input to QSM.