High-resolution characterisation of the aging brain using simultaneous quantitative susceptibility mapping (QSM) and R2* measurements at 7T

An exploratory research report on brain mineralization in postoperative delirium and cognitive decline

Delirium is a severe postoperative complication associated with poor overall and especially neurocognitive prognosis. Altered brain mineralization is found in neurodegenerative disorders but has not been studied in postoperative delirium and postoperative cognitive decline. We hypothesized that mineralization-related hypointensity in susceptibility-weighted magnetic resonance imaging (SWI) is associated with postoperative delirium and cognitive decline. In an exploratory, hypothesis-generating study, we analysed a subsample of cognitively healthy patients ≥65 years who underwent SWI before (N = 65) and 3 months after surgery (N = 33). We measured relative SWI intensities in the basal ganglia, hippocampus and posterior basal forebrain cholinergic system (pBFCS). A post hoc analysis of two pBFCS subregions (Ch4, Ch4p) was conducted. Patients were screened for delirium until the seventh postoperative day. Cognitive testing was performed before and 3 months after surgery. Fourteen patients developed delirium. After adjustment for age, sex, preoperative cognition and region volume, only pBFCS hypointensity was associated with delirium (regression coefficient [90% CI]: B = -15.3 [-31.6; -0.8]). After adjustments for surgery duration, age, sex and region volume, perioperative change in relative SWI intensities of the pBFCS was associated with cognitive decline 3 months after surgery at a trend level (B = 6.8 [-0.9; 14.1]), which was probably driven by a stronger association in subregion Ch4p (B = 9.3 [2.3; 16.2]). Brain mineralization, particularly in the cerebral cholinergic system, could be a pathomechanism in postoperative delirium and cognitive decline. Evidence from our studies is limited because of the small sample and a SWI dataset unfit for iron quantification, and the analyses presented here should be considered exploratory.

Whole brain pattern of iron accumulation in REM sleep behavior disorder

Isolated REM sleep behavior disorder (iRBD) is an early stage of synucleinopathy with most patients progressing to Parkinson's disease (PD) or related conditions. Quantitative susceptibility mapping (QSM) in PD has identified pathological iron accumulation in the substantia nigra (SN) and variably also in basal ganglia and cortex. Analyzing whole-brain QSM across iRBD, PD, and healthy controls (HC) may help to ascertain the extent of neurodegeneration in prodromal synucleinopathy. 70 de novo PD patients, 70 iRBD patients, and 60 HCs underwent 3 T MRI. T1 and susceptibility-weighted images were acquired and processed to space standardized QSM. Voxel-based analyses of grey matter magnetic susceptibility differences comparing all groups were performed on the whole brain and upper brainstem levels with the statistical threshold set at family-wise error-corrected p-values <.05. Whole-brain analysis showed increased susceptibility in the bilateral fronto-parietal cortex of iRBD patients compared to both PD and HC. This was not associated with cortical thinning according to the cortical thickness analysis. Compared to iRBD, PD patients had increased susceptibility in the left amygdala and hippocampal region. Upper brainstem analysis revealed increased susceptibility within the bilateral SN for both PD and iRBD compared to HC; changes were located predominantly in nigrosome 1 in the former and nigrosome 2 in the latter group. In the iRBD group, abnormal dopamine transporter SPECT was associated with increased susceptibility in nigrosome 1. iRBD patients display greater fronto-parietal cortex involvement than incidental early-stage PD cohort indicating more widespread subclinical neuropathology. Dopaminergic degeneration in the substantia nigra is paralleled by susceptibility increase, mainly in nigrosome 1.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

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

Longitudinal Associations of Magnetic Susceptibility with Clinical Severity in Parkinson's Disease

BACKGROUND

Dementia is common in Parkinson's disease (PD), but there is wide variation in its timing. A critical gap in PD research is the lack of quantifiable markers of progression, and methods to identify early stages of dementia. Atrophy-based magnetic resonance imaging (MRI) has limited sensitivity in detecting or tracking changes relating to PD dementia, but quantitative susceptibility mapping (QSM), sensitive to brain tissue iron, shows potential for these purposes.

OBJECTIVE

The objective of the paper is to study, for the first time, the longitudinal relationship between cognition and QSM in PD in detail.

METHODS

We present a longitudinal study of clinical severity in PD using QSM, including 59 PD patients (without dementia at study onset), and 22 controls over 3 years.

RESULTS

In PD, increased baseline susceptibility in the right temporal cortex, nucleus basalis of Meynert, and putamen was associated with greater cognitive severity after 3 years; and increased baseline susceptibility in basal ganglia, substantia nigra, red nucleus, insular cortex, and dentate nucleus was associated with greater motor severity after 3 years. Increased follow-up susceptibility in these regions was associated with increased follow-up cognitive and motor severity, with further involvement of hippocampus relating to cognitive severity. However, there were no consistent increases in susceptibility over 3 years.

CONCLUSIONS

Our study suggests that QSM may predict changes in cognitive severity many months prior to overt cognitive involvement in PD. However, we did not find robust longitudinal changes in QSM over the course of the study. Additional tissue metrics may be required together with QSM for it to monitor progression in clinical practice and therapeutic trials. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.

MR Susceptibility Separation for Quantifying Lesion Paramagnetic and Diamagnetic Evolution in Relapsing-Remitting Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) lesion evolution may involve changes in diamagnetic myelin and paramagnetic iron. Conventional quantitative susceptibility mapping (QSM) can provide net susceptibility distribution, but not the discrete paramagnetic and diamagnetic components.

PURPOSE

To apply susceptibility separation (χ separation) to follow lesion evolution in MS with comparison to R2 */R2 ' /QSM.

STUDY TYPE

Longitudinal, prospective.

SUBJECTS

Twenty relapsing-remitting MS subjects (mean age: 42.5 ± 9.4 years, 13 females; mean years of symptoms: 4.3 ± 1.4 years).

FIELD STRENGTH/SEQUENCE

Three-dimensional multiple echo gradient echo (QSM and R2 * mapping), two-dimensional dual echo fast spin echo (R2 mapping), T2 -weighted fluid attenuated inversion recovery, and T1-weighted magnetization prepared gradient echo sequences at 3 T.

ASSESSMENT

Data were analyzed from two scans separated by a mean interval of 14.4 ± 2.0 months. White matter lesions on fluid-attenuated inversion recovery were defined by an automatic pipeline, then manually refined (by ZZ/AHW, 3/25 years' experience in MRI), and verified by a radiologist (MN, 25 years' experience in MS). Susceptibility separation yielded the paramagnetic and diamagnetic susceptibility content of each voxel. Lesions were classified into four groups based on the variation of QSM/R2 * or separated into positive/negative components from χ separation.

STATISTICAL TESTS

Two-sample paired t tests for assessment of longitudinal differences. Spearman correlation coefficients to assess associations between χ separation and R2 */R2 ' /QSM. Significant level: P < 0.005.

RESULTS

A total of 183 lesions were quantified. Categorizing lesions into groups based on χ separation demonstrated significant annual changes in QSM//R2 */R2 ' . When lesions were grouped based on changes in QSM and R2 *, both changing in unison yielded a significant dominant paramagnetic variation and both opposing yielded a dominant diamagnetic variation. Significant Spearman correlation coefficients were found between susceptibility-sensitive MRI indices and χ separation.

DATA CONCLUSION

Susceptibility separation changes in MS lesions may distinguish and quantify paramagnetic and diamagnetic evolution, potentially providing additional insight compared to R2 * and QSM alone.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

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.

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

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

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.

The relaxometry hype cycle

Relaxometry is a field with a glorious and controversial history, and no review will ever do it justice. It is full of egos and inventions, patents and lawsuits, high expectations and deep disillusionments. Rather than a paragraph dedicated to each of these, we want to give it an impressionistic overview, painted over with a coat of personal opinions and ruminations about the future of the field. For those unfamiliar with the Gartner hype cycle, here's a brief recap. The cycle starts with a technology trigger and goes through a phase of unrealistically inflated expectations. Eventually the hype dies down as implementations fail to deliver on their promise, and disillusionment sets in. Technologies that manage to live through the trough reach the slope of enlightenment, when there is a flurry of second and third generation products that make the initial promise feel feasible again. Finally, we reach the slope of productivity, where mainstream adoption takes off, and more incremental progress is made, eventually reaching steady state in terms of the technology's visibility. The entire interactive timeline can be viewed at https://qmrlab.org/relaxometry/.

BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources

INTRODUCTION

Background field removal (BFR) is a critical step required for successful quantitative susceptibility mapping (QSM). However, eliminating the background field in brains containing significant susceptibility sources, such as intracranial hemorrhages, is challenging due to the relatively large scale of the field induced by these pathological susceptibility sources.

METHOD

This study proposes a new deep learning-based method, BFRnet, to remove the background field in healthy and hemorrhagic subjects. The network is built with the dual-frequency octave convolutions on the U-net architecture, trained with synthetic field maps containing significant susceptibility sources. The BFRnet method is compared with three conventional BFR methods and one previous deep learning method using simulated and in vivo brains from 4 healthy and 2 hemorrhagic subjects. Robustness against acquisition field-of-view (FOV) orientation and brain masking are also investigated.

RESULTS

For both simulation and in vivo experiments, BFRnet led to the best visually appealing results in the local field and QSM results with the minimum contrast loss and the most accurate hemorrhage susceptibility measurements among all five methods. In addition, BFRnet produced the most consistent local field and susceptibility maps between different sizes of brain masks, while conventional methods depend drastically on precise brain extraction and further brain edge erosions. It is also observed that BFRnet performed the best among all BFR methods for acquisition FOVs oblique to the main magnetic field.

CONCLUSION

The proposed BFRnet improved the accuracy of local field reconstruction in the hemorrhagic subjects compared with conventional BFR algorithms. The BFRnet method was effective for acquisitions of tilted orientations and retained whole brains without edge erosion as often required by traditional BFR methods.

Robust quantitative susceptibility mapping via approximate message passing with parameter estimation

PURPOSE

For quantitative susceptibility mapping (QSM), the lack of ground-truth in clinical settings makes it challenging to determine suitable parameters for the dipole inversion. We propose a probabilistic Bayesian approach for QSM with built-in parameter estimation, and incorporate the nonlinear formulation of the dipole inversion to achieve a robust recovery of the susceptibility maps.

THEORY

From a Bayesian perspective, the image wavelet coefficients are approximately sparse and modeled by the Laplace distribution. The measurement noise is modeled by a Gaussian-mixture distribution with two components, where the second component is used to model the noise outliers. Through probabilistic inference, the susceptibility map and distribution parameters can be jointly recovered using approximate message passing (AMP).

METHODS

We compare our proposed AMP with built-in parameter estimation (AMP-PE) to the state-of-the-art L1-QSM, FANSI, and MEDI approaches on the simulated and in vivo datasets, and perform experiments to explore the optimal settings of AMP-PE. Reproducible code is available at: https://github.com/EmoryCN2L/QSM_AMP_PE.

RESULTS

On the simulated Sim2Snr1 dataset, AMP-PE achieved the lowest NRMSE, deviation from calcification moment and the highest SSIM, while MEDI achieved the lowest high-frequency error norm. On the in vivo datasets, AMP-PE is robust and successfully recovers the susceptibility maps using the estimated parameters, whereas L1-QSM, FANSI and MEDI typically require additional visual fine-tuning to select or double-check working parameters.

CONCLUSION

AMP-PE provides automatic and adaptive parameter estimation for QSM and avoids the subjectivity from the visual fine-tuning step, making it an excellent choice for the clinical setting.

The 3D Structural Architecture of the Human Hand Area Is Nontopographic

The functional topography of the human primary somatosensory cortex hand area is a widely studied model system to understand sensory organization and plasticity. It is so far unclear whether the underlying 3D structural architecture also shows a topographic organization. We used 7 Tesla (7T) magnetic resonance imaging (MRI) data to quantify layer-specific myelin, iron, and mineralization in relation to population receptive field maps of individual finger representations in Brodman area 3b (BA 3b) of human S1 in female and male younger adults. This 3D description allowed us to identify a characteristic profile of layer-specific myelin and iron deposition in the BA 3b hand area, but revealed an absence of structural differences, an absence of low-myelin borders, and high similarity of 3D microstructure profiles between individual fingers. However, structural differences and borders were detected between the hand and face areas. We conclude that the 3D structural architecture of the human hand area is nontopographic, unlike in some monkey species, which suggests a high degree of flexibility for functional finger organization and a new perspective on human topographic plasticity.SIGNIFICANCE STATEMENT Using ultra-high-field MRI, we provide the first comprehensive in vivo description of the 3D structural architecture of the human BA 3b hand area in relation to functional population receptive field maps. High similarity of precise finger-specific 3D profiles, together with an absence of structural differences and an absence of low-myelin borders between individual fingers, reveals the 3D structural architecture of the human hand area to be nontopographic. This suggests reduced structural limitations to cortical plasticity and reorganization and allows for shared representational features across fingers.

Perturbed iron biology in the prefrontal cortex of people with schizophrenia

Despite loss of grey matter volume and emergence of distinct cognitive deficits in young adults diagnosed with schizophrenia, current treatments for schizophrenia do not target disruptions in late maturational reshaping of the prefrontal cortex. Iron, the most abundant transition metal in the brain, is essential to brain development and function, but in excess, it can impair major neurotransmission systems and lead to lipid peroxidation, neuroinflammation and accelerated aging. However, analysis of cortical iron biology in schizophrenia has not been reported in modern literature. Using a combination of inductively coupled plasma-mass spectrometry and western blots, we quantified iron and its major-storage protein, ferritin, in post-mortem prefrontal cortex specimens obtained from three independent, well-characterised brain tissue resources. Compared to matched controls (n = 85), among schizophrenia cases (n = 86) we found elevated tissue iron, unlikely to be confounded by demographic and lifestyle variables, by duration, dose and type of antipsychotic medications used or by copper and zinc levels. We further observed a loss of physiologic age-dependent iron accumulation among people with schizophrenia, in that the iron level among cases was already high in young adulthood. Ferritin, which stores iron in a redox-inactive form, was paradoxically decreased in individuals with the disorder. Such iron-ferritin uncoupling could alter free, chemically reactive, tissue iron in key reasoning and planning areas of the young-adult schizophrenia cortex. Using a prediction model based on iron and ferritin, our data provide a pathophysiologic link between perturbed cortical iron biology and schizophrenia and indicate that achievement of optimal cortical iron homeostasis could offer a new therapeutic target.

Layer-specific vulnerability is a mechanism of topographic map aging

Topographic maps form a critical feature of cortical organization, yet are poorly described with respect to their microstructure in the living aging brain. We acquired quantitative structural and functional 7T-MRI data from younger and older adults to characterize layer-wise topographic maps of the primary motor cortex (M1). Using parcellation-inspired techniques, we show that quantitative T1 and Quantitative Susceptibility Maps values of the hand, face, and foot areas differ significantly, revealing microstructurally distinct cortical fields in M1. We show that these fields are distinct in older adults and that myelin borders between them do not degenerate. We further show that the output layer 5 of M1 shows a particular vulnerability to age-related increased iron, while layer 5 and the superficial layer show increased diamagnetic substance, likely reflecting calcifications. Taken together, we provide a novel 3D model of M1 microstructure, where body parts form distinct structural units, but layers show specific vulnerability toward increased iron and calcium in older adults. Our findings have implications for understanding sensorimotor organization and aging, in addition to topographic disease spread.

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.

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.

A probabilistic Bayesian approach to recover R2*$$ {R}_{2\ast } $$ map and phase images for quantitative susceptibility mapping

PURPOSE

Undersampling is used to reduce the scan time for high-resolution three-dimensional magnetic resonance imaging. In order to achieve better image quality and avoid manual parameter tuning, we propose a probabilistic Bayesian approach to recover R 2 ∗ $$ {R}_2^{\ast } $$ map and phase images for quantitative susceptibility mapping (QSM), while allowing automatic parameter estimation from undersampled data.

THEORY

Sparse prior on the wavelet coefficients of images is interpreted from a Bayesian perspective as sparsity-promoting distribution. A novel nonlinear approximate message passing (AMP) framework that incorporates a mono-exponential decay model is proposed. The parameters are treated as unknown variables and jointly estimated with image wavelet coefficients.

METHODS

Undersampling takes place in the y-z plane of k-space according to the Poisson-disk pattern. Retrospective undersampling is performed to evaluate the performances of different reconstruction approaches, prospective undersampling is performed to demonstrate the feasibility of undersampling in practice.

RESULTS

The proposed AMP with parameter estimation (AMP-PE) approach successfully recovers R 2 ∗ $$ {R}_2^{\ast } $$ maps and phase images for QSM across various undersampling rates. It is more computationally efficient, and performs better than the state-of-the-art l 1 $$ {l}_1 $$ -norm regularization (L1) approach in general, except a few cases where the L1 approach performs as well as AMP-PE.

CONCLUSION

AMP-PE achieves better performance by drawing information from both the sparse prior and the mono-exponential decay model. It does not require parameter tuning, and works with a clinical, prospective undersampling scheme where parameter tuning is often impossible or difficult due to the lack of ground-truth image.

Developmental trajectory of magnetic susceptibility in the healthy rhesus macaque brain

Quantitative susceptibility mapping (QSM) is used to quantify iron deposition in non-human primates in our study. Although QSM has many applications in detecting iron deposits in the human brain, including the distribution of iron deposits in specific brain regions, the change of iron deposition with aging, and the comparison of iron deposits between diseased groups and healthy controls, few studies have applied QSM to non-human primates, while most animal brain experiments focus on biochemical and anatomical results instead of non-invasive experiments. Additionally, brain imaging in children's research is difficult, but can be substituted using young rhesus monkeys, which are very similar to humans, as research animals. Therefore, understanding the relationship between iron deposition and age in rhesus macaques' brains can offer insights into both the developmental trajectory of magnetic susceptibility in the animal model and the correlated evidence in children's research. Twenty-three healthy rhesus macaque monkeys (23 ± 7.85 years, range 2-29 years) were included in this research. Seven regions of interest (ROIs-globus pallidus, substantia nigra, dentate nucleus, caudate nucleus, putamen, thalamus, red nucleus) have been analyzed in terms of QSM and R₂ * (apparent relaxation rate). Susceptibility in most ROIs correlated significantly with the growth of age, similarly to the results for R₂ *, but showed different trends in the thalamus and red nucleus, which may be caused by the different sensitivities of myelination and iron deposition in R₂ * and QSM analysis. By assessing the correlation between iron content and age in healthy rhesus macaques' brains using QSM, we provide a piece of pilot information on normality for advanced animal disease models. Meanwhile, this study also could serve as the normative basis for further clinical studies using QSM for iron content quantification. Due to the comparison of the susceptibility on the same experimental objects, this research can also provide practical support for future research on characteristics for QSM and R₂ *.

Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological-consistent iron-rich deep brain nucleus subregion identification

Iron-rich deep brain nuclei (DBN) of the human brain are involved in various motoric, emotional and cognitive brain functions. The abnormal iron alterations in the DBN are closely associated with multiple neurological and psychiatric diseases. Quantitative susceptibility mapping (QSM) provides the spatial distribution of the magnetic susceptibility of human brain tissues. Compared to traditional structural imaging, QSM provides superiority for imaging the iron-rich DBN owing to the susceptibility difference existing between brain tissues. In this study, we constructed a Montreal Neurological Institute (MNI) space unbiased QSM human brain atlas via group-wise registration from 100 healthy subjects aged 19-29 years. The atlas construction process was guided by hybrid images that were fused from multi-modal magnetic resonance images (MRI). We named it as Multi-modal-fused magnetic Susceptibility (MuSus-100) atlas. The high-quality susceptibility atlas provides extraordinary image contrast between iron-rich DBN with their surroundings. Parcellation maps of DBN and their subregions that are highly related to neurological and psychiatric pathology were then manually labeled based on the atlas set with the assistance of an image border-enhancement process. Especially, the bilateral thalamus was delineated into 64 detailed subregions referring to the Schaltenbrand-Wahren stereotactic atlas. To our best knowledge, the histological-consistent thalamic nucleus parcellation map is well defined for the first time in the MNI space. Compared with existing atlases that emphasizing DBN parcellation, the newly proposed atlas outperforms on the task of atlas-guided individual brain image DBN segmentation both in accuracy and robustness. Moreover, we applied the proposed DBN parcellation map to conduct detailed identification of the pathology-related iron content alterations in subcortical nuclei for Parkinson's Disease (PD) patients. We envision that the MuSus-100 atlas can play a crucial role in improving the accuracy of DBN segmentation for the research of neurological and psychiatric disease progress and also be helpful for target planning in deep brain stimulation surgery.

Distinct brain iron profiles associated with logopenic progressive aphasia and posterior cortical atrophy

Quantitative susceptibility mapping (QSM) can detect iron distribution in the brain by estimating local tissue magnetic susceptibility properties at every voxel. Iron deposition patterns are well studied in typical Alzheimer's disease (tAD), but little is known about these patterns in atypical clinical presentations of AD such as logopenic progressive aphasia (LPA) and posterior cortical atrophy (PCA). Seventeen PCA patients and eight LPA patients were recruited by the Neurodegenerative Research Group at Mayo Clinic, Rochester, MN, and underwent MRI that included a five-echo gradient echo sequence for calculation of QSM. Mean QSM signal was extracted from gray and white matter for regions-of-interest across the brain using the Mayo Clinic Adult Lifespan Template. Bayesian hierarchical models were fit per-region and per-hemisphere to compare PCA, LPA, 63 healthy controls, and 20 tAD patients. Strong evidence (posterior probability > 0.99) was observed for greater susceptibility in the middle occipital gyrus and amygdala in both LPA and PCA, and in the right inferior parietal, inferior temporal, and angular gyri in PCA and the caudate and substantia nigra in LPA compared to controls. Moderate evidence for greater susceptibility (posterior probability > 0.90) was also observed in the inferior occipital gyrus, precuneus, putamen and entorhinal cortex in both LPA and PCA, along with superior frontal gyrus in PCA and inferior temporal gyri, insula and basal ganglia in LPA, when compared to controls. Between phenotypic comparisons, LPA had greater susceptibility in the caudate, hippocampus, and posterior cingulate compared to PCA, while PCA showed greater susceptibility in the right superior frontal and middle temporal gyri compared to LPA. Both LPA and PCA showed moderate and strong evidence for greater susceptibility than tAD, particularly in medial and lateral parietal regions, while tAD showed greater susceptibility in the hippocampus and basal ganglia. This study proposes the possibility of unique iron profiles existing between LPA and PCA within cortical and subcortical structures. These changes match well with the disease-related changes of the clinical phenotypes, suggesting that QSM could be an informative candidate marker to study iron deposition in these patients.

Quantitative Susceptibility Mapping of Brain Iron Deposition in Patients With Recurrent Depression

OBJECTIVE

Recurrence is the most significant feature of depression and the relationship between iron and recurrent depression is still lack of direct evidence in vivo.

METHODS

Twenty-one patients with depression and twenty control subjects were included. Gradient-recalled echo, T1 and T2 images were acquired using a 3.0T MRI system. After quantitative susceptibility mapping were reconstructed and standardized, a whole-brain and the regions of interest were respectively analyzed.

RESULTS

Significant increases in susceptibility were found in multiple recurrent depression patients, which involved several brain regions (frontal lobes, temporal lobe structures, occipital lobes hippocampal regions, putamen, thalamus, cingulum, and cerebellum). Interestingly, no susceptibility changes after treatment compared to pre-treatment (all p>0.05) and no significant correlation between susceptibility and Hamilton Depression Rating Scale were found. Besides, it was close to significance that those with a higher relapse frequency or a longer mean duration of single episode had a higher susceptibility in the putamen, thalamus, and hippocampus. Further studies showed susceptibility across the putamen (ρ2=0.27, p<0.001), thalamus (ρ2=0.21, p<0.001), and hippocampus (ρ2=0.19, p<0.001) were strongly correlated with total course of disease onset.

CONCLUSION

Brain iron deposition is related to the total course of disease onset, but not the severity of depression, which suggest that brain iron deposition may be a sign of brain damage in multiple recurrent depression.

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities

Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby, QSM can reveal pathological changes of these key components in a variety of diseases. QSM requires multiple processing steps such as phase unwrapping, background field removal and field-to-source inversion. Current state-of-the-art techniques utilize iterative optimization procedures to solve the inversion and background field correction, which are computationally expensive and require a careful choice of regularization parameters. With the recent success of deep learning using convolutional neural networks for solving ill-posed reconstruction problems, the QSM community also adapted these techniques and demonstrated that the QSM processing steps can be solved by efficient feed forward multiplications not requiring either iterative optimization or the choice of regularization parameters. Here, we review the current status of deep learning-based approaches for processing QSM, highlighting limitations and potential pitfalls, and discuss the future directions the field may take to exploit the latest advances in deep learning for QSM.

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

PURPOSE

To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T 2 ∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan.

METHODS

The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T 2 ∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined.

RESULTS

High quality, co-registered T1 , T2 , and T 2 ∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T 2 ∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images.

CONCLUSION

The MR Multitasking-based 3D brain mapping of T1 , T2 , T 2 ∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.

Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI

The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.

Ironsmith: An Automated Pipeline for QSM-based Data Analyses

Quantitative susceptibility mapping (QSM) is an MRI-based, computational method for anatomically localizing and measuring concentrations of specific biomarkers in tissue such as iron. Growing research suggests QSM is a viable method for evaluating the impact of iron overload in neurological disorders and on cognitive performance in aging. Several software toolboxes are currently available to reconstruct QSM maps from 3D GRE MR Images. However, few if any software packages currently exist that offer fully automated pipelines for QSM-based data analyses: from DICOM images to region-of-interest (ROI) based QSM values. Even less QSM-based software exist that offer quality control measures for evaluating the QSM output. Here, we address these gaps in the field by introducing and demonstrating the reliability and external validity of Ironsmith; an open-source, fully automated pipeline for creating and processing QSM maps, extracting QSM values from subcortical and cortical brain regions (89 ROIs) and evaluating the quality of QSM data using SNR measures and assessment of outlier regions on phase images. Ironsmith also features automatic filtering of QSM outlier values and precise CSF-only QSM reference masks that minimize partial volume effects. Testing of Ironsmith revealed excellent intra- and inter-rater reliability. Finally, external validity of Ironsmith was demonstrated via an anatomically selective relationship between motor performance and Ironsmith-derived QSM values in motor cortex. In sum, Ironsmith provides a freely-available, reliable, turn-key pipeline for QSM-based data analyses to support research on the impact of brain iron in aging and neurodegenerative disease.

Analysis of deep grey nuclei susceptibility in early childhood: a quantitative susceptibility mapping and R2* study at 3 Tesla

Purpose

Aging is the most significant determinant for brain iron accumulation in the deep grey matter. Data on brain iron evolution during brain maturation in early childhood are limited. The purpose of this study was to investigate age-related iron deposition in the deep grey matter in children using quantitative susceptibility (QSM) and R2* mapping.

Methods

We evaluated brain MRI scans of 74 children (age 6–154 months, mean 40 months). A multi-echo gradient-echo sequence obtained at 3 Tesla was used for the QSM and R2* calculation. Susceptibility of the pallidum, head of caudate nucleus, and putamen was correlated with age and compared between sexes.

Results

Susceptibility changes in all three nuclei correlated with age (correlation coefficients for QSM/R2*: globus pallidus 0.955/0.882, caudate nucleus 0.76/0.65, and putamen 0.643/0.611). During the first 2 years, the R2* values increased more rapidly than the QSM values, indicating a combined effect of iron deposition and myelination, followed by a likely dominating effect of iron deposition. There was no significant gender difference.

Conclusion

QSM and R2* can monitor myelin maturation processes and iron accumulation in the deep grey nuclei of the brain in early life and may be a promising tool for the detection of deviations of this normal process. Susceptibility in the deep nuclei is almost similar early after birth and increases more quickly in the pallidum. The combined use of QSM and R2* analysis is beneficial.

Age-related magnetic susceptibility changes in deep grey matter and cerebral cortex of normal young and middle-aged adults depicted by whole brain analysis

Background

Iron accumulates in brain tissue in healthy subjects during aging. Our goal was to conduct a detailed analysis of iron deposition patterns in the cerebral deep grey matter and cortex using region-based and whole-brain analyses of brain magnetic susceptibility.

Methods

Brain MRI was performed in 95 healthy individuals aged between 21 and 58 years on a 3T scanner. MRI protocol included T1-weighted (T1W) magnetization-prepared rapid acquisition with gradient echo images and 3D flow-compensated multi-echo gradient-echo images for quantitative susceptibility mapping (QSM). In the region-based analysis, QSM and T1W images entered an automated multi-atlas segmentation pipeline and regional mean bulk susceptibility values were calculated. The whole-brain analysis included a non-linear transformation of QSM images to the standard MNI template. For the whole-brain analysis voxel-wise maps of linear regression slopes β and P values were calculated. Regional masks of cortical voxels with a significant association between susceptibility and age were created and further analyzed.

Results

In cortical regions, the highest increase of susceptibility values with age was found in areas involved in motor functions (precentral and postcentral areas, premotor cortex), in cognitive processing (prefrontal cortex, superior temporal gyrus, insula, precuneus), and visual processing (occipital gyri, cuneus, posterior cingulum, fusiform, calcarine and lingual gyrus). Thalamic susceptibility increased until the fourth decade and decreased thereafter with the exception of the pulvinar where susceptibility increase was observed throughout the adult lifespan. Deep grey matter structures with the highest increase of susceptibility values with age included the red nucleus, putamen, substantia nigra, dentate nucleus, external globus pallidus, caudate nucleus, and the subthalamic nucleus in decreasing order.

Conclusions

Accumulation of iron in basal ganglia follows a linear pattern whereas in the thalamus, pulvinar, precentral cortex, and precuneus, it follows a quadratic or exponential pattern. Age-related changes of iron content are different in the pulvinar and the rest of the thalamus as well as in internal and external globus pallidus. In the cortex, areas involved in motor and cognitive functions and visual processing show the highest iron increase with aging. We suggest that the departure from normal patterns of regional brain iron trajectories during aging may be helpful in the detection of subtle neurodegenerative and neuroinflammatory processes.

Combining structural and metabolic markers in a quantitative MRI study of motor neuron diseases

OBJECTIVE

To assess the performance of a combination of three quantitative MRI markers (iron deposition, basal neuronal metabolism, and regional atrophy) for differential diagnosis between amyotrophic lateral sclerosis (ALS) and primary lateral sclerosis (PLS).

METHODS

In total, 33 ALS, 12 PLS, and 28 healthy control (HC) subjects underwent a 3T MRI study including single- and multi-echo sequences for gray matter (GM) volumetry and quantitative susceptibility mapping (QSM) and a pseudo-continuous arterial spin labeling (ASL) sequence for cerebral blood flow (CBF) measurement. Mean values of QSM, CBF, and GM volumes were extracted in the motor cortex, basal ganglia, thalamus, amygdala, and hippocampus. A generalized linear model was applied to the three measures to binary discriminate between groups. The diagnostic performances were evaluated via receiver operating characteristic analyses.

RESULTS

A significant discrimination was obtained: between ALS and HCs in the left and right motor cortex, where QSM increases were respectively associated with disability scores and disease duration; between PLS and ALS in the left motor cortex, where PLS patients resulted significantly more atrophic; between ALS and HC in the right motor cortex, where GM volumes were associated with upper motor neuron scores. Significant discrimination between ALS and HC was achieved in subcortical structures only combining all three parameters.

INTERPRETATION

While increased QSM values in the motor cortex of ALS patients is a consolidated finding, combining QSM, CBF, and GM volumetry shows higher diagnostic potential for differentiating ALS patients from HC subjects and, in the motor cortex, between ALS and PLS.

MRI of healthy brain aging: A review

We present a review of the characterization of healthy brain aging using MRI with an emphasis on morphology, lesions, and quantitative MR parameters. A scope review found 6612 articles encompassing the keywords "Brain Aging" and "Magnetic Resonance"; papers involving functional MRI or not involving imaging of healthy human brain aging were discarded, leaving 2246 articles. We first consider some of the biogerontological mechanisms of aging, and the consequences of aging in terms of cognition and onset of disease. Morphological changes with aging are reviewed for the whole brain, cerebral cortex, white matter, subcortical gray matter, and other individual structures. In general, volume and cortical thickness decline with age, beginning in mid-life. Prevalent silent lesions such as white matter hyperintensities, microbleeds, and lacunar infarcts are also observed with increasing frequency. The literature regarding quantitative MR parameter changes includes T₁ , T₂ , T₂ *, magnetic susceptibility, spectroscopy, magnetization transfer, diffusion, and blood flow. We summarize the findings on how each of these parameters varies with aging. Finally, we examine how the aforementioned techniques have been used for age prediction. While relatively large in scope, we present a comprehensive review that should provide the reader with sound understanding of what MRI has been able to tell us about how the healthy brain ages.

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

PURPOSE

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

METHODS

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

RESULTS

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

Regional brain iron and gene expression provide insights into neurodegeneration in Parkinson's disease

The mechanisms responsible for the selective vulnerability of specific neuronal populations in Parkinson's disease are poorly understood. Oxidative stress secondary to brain iron accumulation is one postulated mechanism. We measured iron deposition in 180 cortical regions of 96 patients with Parkinson's disease and 35 control subjects using quantitative susceptibility mapping. We estimated the expression of 15 745 genes in the same regions using transcriptomic data from the Allen Human Brain Atlas. Using partial least squares regression, we then identified the profile of gene transcription in the healthy brain that underlies increased cortical iron in patients with Parkinson's disease relative to controls. Applying gene ontological tools, we investigated the biological processes and cell types associated with this transcriptomic profile and identified the sets of genes with spatial expression profiles in control brains that correlated significantly with the spatial pattern of cortical iron deposition in Parkinson's disease. Gene ontological analyses revealed that these genes were enriched for biological processes relating to heavy metal detoxification, synaptic function and nervous system development and were predominantly expressed in astrocytes and glutamatergic neurons. Furthermore, we demonstrated that the genes differentially expressed in Parkinson's disease are associated with the pattern of cortical expression identified in this study. Our findings provide mechanistic insights into regional selective vulnerabilities in Parkinson's disease, particularly the processes involving iron accumulation.

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

INTRODUCTION

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

METHOD

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

RESULTS

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

CONCLUSION

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

MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping

Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ₁₃, χ₂₃ and χ₃₃) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ₃₃ and phase induced by χ₁₃ and χ₂₃ terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.

R2* and quantitative susceptibility mapping in deep gray matter of 498 healthy controls from 5 to 90 years

Putative MRI markers of iron in deep gray matter have demonstrated age related changes during discrete periods of healthy childhood or adulthood, but few studies have included subjects across the lifespan. This study reports both transverse relaxation rate (R2*) and quantitative susceptibility mapping (QSM) of four primary deep gray matter regions (thalamus, putamen, caudate, and globus pallidus) in 498 healthy individuals aged 5–90 years. In the caudate, putamen, and globus pallidus, increases of QSM and R2* were steepest during childhood continuing gradually throughout adulthood, except caudate susceptibility which reached a plateau in the late 30s. The thalamus had a unique profile with steeper changes of R2* (reflecting additive effects of myelin and iron) than QSM during childhood, both reaching a plateau in the mid‐30s to early 40s and decreasing thereafter. There were no hemispheric or sex differences for any region. Notably, both R2* and QSM values showed more inter‐subject variability with increasing age from 5 to 90 years, potentially reflecting a common starting point in iron/myelination during childhood that diverges as a result of lifestyle and genetic factors that accumulate with age.

Investigation of the association between cerebral iron content and myelin content in normative aging using quantitative magnetic resonance neuroimaging

Myelin loss and iron accumulation are cardinal features of aging and various neurodegenerative diseases. Oligodendrocytes incorporate iron as a metabolic substrate for myelin synthesis and maintenance. An emerging hypothesis in Alzheimer’s disease research suggests that myelin breakdown releases substantial stores of iron that may accumulate, leading to further myelin breakdown and neurodegeneration. We assessed associations between iron content and myelin content in critical brain regions using quantitative magnetic resonance imaging (MRI) on a cohort of cognitively unimpaired adults ranging in age from 21 to 94 years. We measured whole-brain myelin water fraction (MWF), a surrogate of myelin content, using multicomponent relaxometry, and whole-brain iron content using susceptibility weighted imaging in all individuals. MWF was negatively associated with iron content in most brain regions evaluated indicating that lower myelin content corresponds to higher iron content. Moreover, iron content was significantly higher with advanced age in most structures, with men exhibiting a trend towards higher iron content as compared to women. Finally, relationship between MWF and age, in all brain regions investigated, suggests that brain myelination continues until middle age, followed by degeneration at older ages. This work establishes a foundation for further investigations of the etiology and sequelae of myelin breakdown and iron accumulation in neurodegeneration and may lead to new imaging markers for disease progression and treatment.

Ageing- and dementia-friendly design: theory and evidence from cognitive psychology, neuropsychology and environmental psychology can contribute to design guidelines that minimise spatial disorientation

Many older people, both with and without dementia, eventually move from their familiar home environments into unfamiliar surroundings, such as sheltered housing or care homes. Age-related declines in wayfinding skills can make it difficult to learn to navigate in these new, unfamiliar environments. To facilitate the transition to their new accommodation, it is therefore important to develop retirement complexes and care homes specifically designed to reduce the wayfinding difficulties of older people and those with Alzheimer’s disease (AD). Residential complexes that are designed to support spatial orientation and that compensate for impaired navigation abilities would make it easier for people with dementia to adapt to their new living environment. This would improve the independence, quality of life and well-being of residents, and reduce the caregivers’ workload. Based on these premises, this opinion paper considers how evidence from cognitive psychology, neuropsychology and environmental psychology can contribute to ageing- and dementia-friendly design with a view to minimising spatial disorientation. After an introduction of the cognitive mechanisms and processes involved in spatial navigation, and the changes that occur in typical and atypical ageing, research from the field of environmental psychology is considered, highlighting design factors likely to facilitate (or impair) indoor wayfinding in complex buildings. Finally, psychological theories and design knowledge are combined to suggest ageing- and dementia-friendly design guidelines that aim to minimise spatial disorientation by focusing on residual navigation skills.

Stable Anatomy Detection in Multimodal Imaging Through Sparse Group Regularization: A Comparative Study of Iron Accumulation in the Aging Brain

Multimodal neuroimaging provides a rich source of data for identifying brain regions associated with disease progression and aging. However, present studies still typically analyze modalities separately or aggregate voxel-wise measurements and analyses to the structural level, thus reducing statistical power. As a central example, previous works have used two quantitative MRI parameters-R2* and quantitative susceptibility (QS)-to study changes in iron associated with aging in healthy and multiple sclerosis subjects, but failed to simultaneously account for both. In this article, we propose a unified framework that combines information from multiple imaging modalities and regularizes estimates for increased interpretability, generalizability, and stability. Our work focuses on joint region detection problems where overlap between effect supports across modalities is encouraged but not strictly enforced. To achieve this, we combine L ₁ (lasso), total variation (TV), and L ₂ group lasso penalties. While the TV penalty encourages geometric regularization by controlling estimate variability and support boundary geometry, the group lasso penalty accounts for similarities in the support between imaging modalities. We address the computational difficulty in this regularization scheme with an alternating direction method of multipliers (ADMM) optimizer. In a neuroimaging application, we compare our method against independent sparse and joint sparse models using a dataset of R2* and QS maps derived from MRI scans of 113 healthy controls: our method produces clinically-interpretable regions where specific iron changes are associated with healthy aging. Together with results across multiple simulation studies, we conclude that our approach identifies regions that are more strongly associated with the variable of interest (e.g., age), more accurate, and more stable with respect to training data variability. This work makes progress toward a stable and interpretable multimodal imaging analysis framework for studying disease-related changes in brain structure and can be extended for classification and disease prediction tasks.

SEPIA-Susceptibility mapping pipeline tool for phase images

Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.

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

Introduction

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

Methods

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

Results and Discussion

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

Conclusion

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

Cortical iron disrupts functional connectivity networks supporting working memory performance in older adults

Excessive brain iron negatively affects working memory and related processes but the impact of cortical iron on task-relevant, cortical brain networks is unknown. We hypothesized that high cortical iron concentration may disrupt functional circuitry within cortical networks supporting working memory performance. Fifty-five healthy older adults completed an N-Back working memory paradigm while functional magnetic resonance imaging (fMRI) was performed. Participants also underwent quantitative susceptibility mapping (QSM) imaging for assessment of non-heme brain iron concentration. Additionally, pseudo continuous arterial spin labeling scans were obtained to control for potential contributions of cerebral blood volume and structural brain images were used to control for contributions of brain volume. Task performance was positively correlated with strength of task-based functional connectivity (tFC) between brain regions of the frontoparietal working memory network. However, higher cortical iron concentration was associated with lower tFC within this frontoparietal network and with poorer working memory performance after controlling for both cerebral blood flow and brain volume. Our results suggest that high cortical iron concentration disrupts communication within frontoparietal networks supporting working memory and is associated with reduced working memory performance in older adults.

Simultaneous QSM and metabolic imaging of the brain using SPICE: Further improvements in data acquisition and processing

PURPOSE

To achieve high-resolution mapping of brain tissue susceptibility in simultaneous QSM and metabolic imaging.

METHODS

Simultaneous QSM and metabolic imaging was first achieved using SPICE (spectroscopic imaging by exploiting spatiospectral correlation), but the QSM maps thus obtained were at relatively low-resolution (2.0 × 3.0 × 3.0 mm³ ). We overcome this limitation using an improved SPICE data acquisition method with the following novel features: 1) sampling (k, t)-space in dual densities, 2) sampling central k-space fully to achieve nominal spatial resolution of 3.0 × 3.0 × 3.0 mm³ for metabolic imaging, and 3) sampling outer k-space sparsely to achieve spatial resolution of 1.0 × 1.0 × 1.9 mm³ for QSM. To keep the scan time short, we acquired spatiospectral encodings in echo-planar spectroscopic imaging trajectories in central k-space but in CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) trajectories in outer k-space using blipped phase encodings. For data processing and image reconstruction, a union-of-subspaces model was used, effectively incorporating sensitivity encoding, spatial priors, and spectral priors of individual molecules.

RESULTS

In vivo experiments were carried out to evaluate the feasibility and potential of the proposed method. In a 6-min scan, QSM maps at 1.0 × 1.0 × 1.9 mm³ resolution and metabolic maps at 3.0 × 3.0 × 3.0 mm³ nominal resolution were obtained simultaneously. Compared with the original method, the QSM maps obtained using the new method reveal fine-scale brain structures more clearly.

CONCLUSION

We demonstrated the feasibility of achieving high-resolution QSM simultaneously with metabolic imaging using a modified SPICE acquisition method. The improved capability of SPICE may further enhance its practical utility in brain mapping.

A multi-contrast MRI approach to thalamus segmentation

Thalamic alterations occur in many neurological disorders including Alzheimer's disease, Parkinson's disease and multiple sclerosis. Routine interventions to improve symptom severity in movement disorders, for example, often consist of surgery or deep brain stimulation to diencephalic nuclei. Therefore, accurate delineation of grey matter thalamic subregions is of the upmost clinical importance. MRI is highly appropriate for structural segmentation as it provides different views of the anatomy from a single scanning session. Though with several contrasts potentially available, it is also of increasing importance to develop new image segmentation techniques that can operate multi-spectrally. We hereby propose a new segmentation method for use with multi-modality data, which we evaluated for automated segmentation of major thalamic subnuclear groups using T1 -weighted, T 2 * -weighted and quantitative susceptibility mapping (QSM) information. The proposed method consists of four steps: Highly iterative image co-registration, manual segmentation on the average training-data template, supervised learning for pattern recognition, and a final convex optimisation step imposing further spatial constraints to refine the solution. This led to solutions in greater agreement with manual segmentation than the standard Morel atlas based approach. Furthermore, we show that the multi-contrast approach boosts segmentation performances. We then investigated whether prior knowledge using the training-template contours could further improve convex segmentation accuracy and robustness, which led to highly precise multi-contrast segmentations in single subjects. This approach can be extended to most 3D imaging data types and any region of interest discernible in single scans or multi-subject templates.

Simultaneous voxel-based magnetic susceptibility and morphometry analysis using magnetization-prepared spoiled turbo multiple gradient echo

This study aimed to develop and test a simultaneous acquisition and analysis pipeline for voxel-based magnetic susceptibility and morphometry (VBMSM) on a single dataset using young volunteers, elderly healthy volunteers, and an Alzheimer's disease (AD) group. 3D T₁ -weighted and multi-echo phase images for VBM and quantitative susceptibility mapping (QSM) were simultaneously acquired using a magnetization-prepared spoiled turbo multiple gradient echo sequence with inversion pulse for QSM (MP-QSM). The magnitude image was split into gray matter (GM) and white matter (WM) and was spatially normalized. The susceptibility map was reconstructed from the phase images. The segmented image and susceptibility map were compared with those obtained from conventional multiple spoiled gradient echo (mGRE) and MP-spoiled gradient echo (MP-GRE) in healthy volunteers to validate the availability of MP-QSM by numerical measurements. To assess the feasibility of the VBMSM analysis pipeline, voxel-based comparisons of susceptibility and morphometry in MP-QSM were conducted in volunteers with a bimodal age distribution, and in elderly volunteers and the AD group, using spatially normalized GM and WM volume images and a susceptibility map. GM/WM contrasts in MP-QSM, MP-GRE, and mGRE were 0.14 ± 0.011, 0.17 ± 0.015, and 0.045 ± 0.010, respectively. Segmented GM and WM volumes in the MP-QSM closely coincided with those in the MP-GRE. Region of interest analyses indicated that the mean susceptibility values in MP-QSM were completely in agreement with those in mGRE. In an evaluation of the aging effect, a significant increase and decrease in susceptibility and volume were found by VBMSM in deep GM and WM, respectively. Between the elderly volunteers and the AD group, the characteristic susceptibility and volume changes in GM and WM were observed. The proposed MP-QSM sequence makes it possible to acquire acceptable-quality images for simultaneous analysis and determine brain atrophy and susceptibility distribution without image registration by using voxel-based analyses.

Relationship between cortical iron and tau aggregation in Alzheimer's disease

A growing body of evidence suggests that the dysregulation of neuronal iron may play a critical role in Alzheimer's disease. Recent MRI studies have established a relationship between iron accumulation and amyloid-β aggregation. The present study provides further insight demonstrating a relationship between iron and tau accumulation using magnetic resonance-based quantitative susceptibility mapping and tau-PET in n = 236 subjects with amyloid-β pathology (from the Swedish BioFINDER-2 study). Both voxel-wise and regional analyses showed a consistent association between differences in bulk magnetic susceptibility, which can be primarily ascribed to an increase in iron content, and tau-PET signal in regions known to be affected in Alzheimer's disease. Subsequent analyses revealed that quantitative susceptibility specifically mediates the relationship between tau-PET and cortical atrophy measures, thus suggesting a modulatory effect of iron burden on the disease process. We also found evidence suggesting the relationship between quantitative susceptibility and tau-PET is stronger in younger participants (age ≤ 65). Together, these results provide in vivo evidence of an association between iron deposition and both tau aggregation and neurodegeneration, which help advance our understanding of the role of iron dysregulation in the Alzheimer's disease aetiology.

Imaging biomarkers in neurodegeneration: current and future practices

There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.

Brain iron deposition is linked with cognitive severity in Parkinson's disease

BACKGROUND

Dementia is common in Parkinson's disease (PD) but measures that track cognitive change in PD are lacking. Brain tissue iron accumulates with age and co-localises with pathological proteins linked to PD dementia such as amyloid. We used quantitative susceptibility mapping (QSM) to detect changes related to cognitive change in PD.

METHODS

We assessed 100 patients with early-stage to mid-stage PD, and 37 age-matched controls using the Montreal Cognitive Assessment (MoCA), a validated clinical algorithm for risk of cognitive decline in PD, measures of visuoperceptual function and the Movement Disorders Society Unified Parkinson's Disease Rating Scale part 3 (UPDRS-III). We investigated the association between these measures and QSM, an MRI technique sensitive to brain tissue iron content.

RESULTS

We found QSM increases (consistent with higher brain tissue iron content) in PD compared with controls in prefrontal cortex and putamen (p<0.05 corrected for multiple comparisons). Whole brain regression analyses within the PD group identified QSM increases covarying: (1) with lower MoCA scores in the hippocampus and thalamus, (2) with poorer visual function and with higher dementia risk scores in parietal, frontal and medial occipital cortices, (3) with higher UPDRS-III scores in the putamen (all p<0.05 corrected for multiple comparisons). In contrast, atrophy, measured using voxel-based morphometry, showed no differences between groups, or in association with clinical measures.

CONCLUSIONS

Brain tissue iron, measured using QSM, can track cognitive involvement in PD. This may be useful to detect signs of early cognitive change to stratify groups for clinical trials and monitor disease progression.

A positive influence of basal ganglia iron concentration on implicit sequence learning

Iron homeostasis is important for maintaining normal physiological brain functioning. In two independent samples, we investigate the link between iron concentration in the basal ganglia (BG) and implicit sequence learning (ISL). In Study 1, we used quantitative susceptibility mapping and task-related fMRI to examine associations among regional iron concentration measurements, brain activation, and ISL in younger and older adults. In Study 2, we examined the link between brain iron and ISL using a metric derived from fMRI in an age-homogenous sample of older adults. Three main findings were obtained. First, BG iron concentration was positively related to ISL in both studies. Second, ISL was robust for both younger and older adults, and performance-related activation was found in fronto-striatal regions across both age groups. Third, BG iron was positively linked to task-related BOLD signal in fronto-striatal regions. This is the first study investigating the relationship among brain iron accumulation, functional brain activation, and ISL, and the results suggest that higher brain iron concentration may be linked to better neurocognitive functioning in this particular task.