Quantitative susceptibility mapping shows lower brain iron content in children with autism

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Brain iron concentration in childhood ADHD: A systematic review of neuroimaging studies

Iron deficiency may play a role in the pathophysiology of Attention Deficit/Hyperactivity Disorder (ADHD). Due to its preponderant function in monoamine catecholamine and myelin synthesis, brain iron concentration may be of primary interest in the investigation of iron dysregulation in ADHD. This study reviewed current evidence of brain iron abnormalities in children and adolescents with ADHD using magnetic resonance imaging methods, such as relaxometry and quantitative susceptibility mapping, to assess brain iron estimates. The study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A literature search was performed for studies published between January 1, 2008 and July 7, 2023 in Medline, Scopus and Proquest. Regions of interest, brain iron index values and phenotypical information were extracted from the relevant studies. Risk of bias was assessed using a modified version of the National Heart, Lung, and Blood Institute quality assessment tool. Seven cross-sectional studies comparing brain iron estimates in children with ADHD with neurotypical children were included. Significantly reduced brain iron content in medication-naïve children with ADHD was a consistent finding. Two studies found psychostimulant use may increase and normalize brain iron concentration in children with ADHD. The findings were consistent across the studies despite differing methodologies and may lay the early foundation for the recognition of a potential biomarker in ADHD, although longitudinal prospective neuroimaging studies using larger sample sizes are required. Lastly, the effects of iron supplementation on brain iron concentration in children with ADHD need to be elucidated.

Restless sleep disorder in a sample of children and adolescents with autism spectrum disorder: preliminary results from a case series

STUDY OBJECTIVES

Sleep disorders are a frequent comorbidity among children with autism spectrum disorder (ASD). Among sleep-related issues of ASD, restless sleep is a common complaint. In recent years, restless sleep disorder (RSD) has been proposed as a new clinical entity, characterized by agitated sleep as its predominant manifestation. Despite the high prevalence of sleep disorders and data reporting restless sleep among ASD patients, to date no study has yet characterized RSD within patients with ASD. Therefore, the aim of our study was to assess the occurrence of RSD in a sample of children and adolescents with ASD through clinical and polysomnographic assessment.

METHODS

Children and adolescents with ASD ages 6-18 years were recruited for the study. Through parental interviews, patients with a suspected RSD were selected and offered diagnostic investigation by video-polysomnography and blood tests to assess martial balance.

RESULTS

Among the 129 participants included, 16 patients (12.4%) were found to have a suspected RSD. Only 6 (4.7%) underwent video-polysomnography due to lack of compliance or family refusal. In 6/6 participants examined, the disorder was confirmed by video-polysomnography movement analysis (total movement index ≥ 5 events/h) and ferritin values were found in the normal range.

CONCLUSIONS

RSD does not appear to be particularly frequent among patients with ASD and that of iron metabolism may not be the main factor implicated in the pathogenesis of RSD within this population. Additional evaluation is needed to confirm the result and further investigate the etiological mechanisms underlying the disorder.

CITATION

Voci A, Mazzone L, De Stefano D, Valeriani M, Bruni O, Moavero R. Restless sleep disorder in a sample of children and adolescents with autism spectrum disorder: preliminary results from a case series. J Clin Sleep Med. 2024;20(3):427-432.

Altered brain iron deposition in patients with minimal hepatic encephalopathy: an MRI quantitative susceptibility mapping study

AIM

To explore the use of quantitative susceptibility mapping (QSM) in assessing changes in brain iron deposits and their association with cognitive function in patients with minimal hepatic encephalopathy (MHE).

MATERIALS AND METHODS

The study cohort comprised 27 cases with hepatitis B-associated cirrhosis with MHE (MHE group), 25 with hepatitis B-associated cirrhosis without MHE (NMHE group), and 25 healthy controls (HC group). Iron deposits in the bilateral frontal white matter, caudate nucleus (CN), putamen, globus pallidus, thalamus, red nucleus, substantia nigra (SN), hippocampus, and dentate nucleus were measured by QSM. The associations between iron deposition with the time taken to complete number connection tests A (NCT-A) and the score on digital-symbol test (DST) were analysed.

RESULTS

Susceptibility values differed significantly in the bilateral CN, left thalamus, right SN, and left hippocampus in the MHE group compared with the other groups and were positively associated with the times taken to complete the NCT-A in the bilateral CN, left thalamus, and right SN and negatively associated with DST scores in the bilateral CN, left TH, and left HP.

CONCLUSION

Reduced cognitive function in MHE patients was significantly associated with abnormally increased iron deposition in certain brain areas. The quantification of brain iron deposition by QSM may thus be an objective and accurate means of evaluating MHE.

Improving quantitative susceptibility mapping for the identification of traumatic brain injury neurodegeneration at the individual level

BACKGROUND

Emerging evidence suggests that traumatic brain injury (TBI) is a major risk factor for developing neurodegenerative disease later in life. Quantitative susceptibility mapping (QSM) has been used by an increasing number of studies in investigations of pathophysiological changes in TBI. However, generating artefact-free quantitative susceptibility maps in brains with large focal lesions, as in the case of moderate-to-severe TBI (ms-TBI), is particularly challenging. To address this issue, we utilized a novel two-pass masking technique and reconstruction procedure (two-pass QSM) to generate quantitative susceptibility maps (QSMxT; Stewart et al., 2022, Magn Reson Med.) in combination with the recently developed virtual brain grafting (VBG) procedure for brain repair (Radwan et al., 2021, NeuroImage) to improve automated delineation of brain areas. We used QSMxT and VBG to generate personalised QSM profiles of individual patients with reference to a sample of healthy controls.

METHODS

Chronic ms-TBI patients (N = 8) and healthy controls (N = 12) underwent (multi-echo) GRE, and anatomical MRI (MPRAGE) on a 3T Siemens PRISMA scanner. We reconstructed the magnetic susceptibility maps using two-pass QSM from QSMxT. We then extracted values of magnetic susceptibility in grey matter (GM) regions (following brain repair via VBG) across the whole brain and determined if they deviate from a reference healthy control group [Z-score < -3.43 or > 3.43, relative to the control mean], with the aim of obtaining personalised QSM profiles.

RESULTS

Using two-pass QSM, we achieved susceptibility maps with a substantial increase in quality and reduction in artefacts irrespective of the presence of large focal lesions, compared to single-pass QSM. In addition, VBG minimised the loss of GM regions and exclusion of patients due to failures in the region delineation step. Our findings revealed deviations in magnetic susceptibility measures from the HC group that differed across individual TBI patients. These changes included both increases and decreases in magnetic susceptibility values in multiple GM regions across the brain.

CONCLUSIONS

We illustrate how to obtain magnetic susceptibility values at the individual level and to build personalised QSM profiles in ms-TBI patients. Our approach opens the door for QSM investigations in more severely injured patients. Such profiles are also critical to overcome the inherent heterogeneity of clinical populations, such as ms-TBI, and to characterize the underlying mechanisms of neurodegeneration at the individual level more precisely. Moreover, this new personalised QSM profiling could in the future assist clinicians in assessing recovery and formulating a neuroscience-guided integrative rehabilitation program tailored to individual TBI patients.

Identification of Immune Infiltration and Iron Metabolism-Related Subgroups in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with a broad spectrum of symptoms and prognoses. Effective therapy requires understanding this variability. ASD children's cognitive and immunological development may depend on iron homoeostasis. This study employs a machine learning model that focuses on iron metabolism hub genes to identify ASD subgroups and describe immune infiltration patterns. A total of 97 control and 148 ASD samples were obtained from the GEO database. Differentially expressed genes (DEGs) and an iron metabolism gene collection achieved the intersection of 25 genes. Unsupervised cluster analysis determined molecular subgroups in individuals with ASD based on 25 genes related to iron metabolism. We assessed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, gene set variation analysis (GSVA), and immune infiltration analysis to compare iron metabolism subtype effects. We employed machine learning to identify subtype-predicting hub genes and utilized both training and validation sets to assess gene subtype prediction accuracy. ASD can be classified into two iron-metabolizing molecular clusters. Metabolic enrichment pathways differed between clusters. Immune infiltration showed that clusters differed immunologically. Cluster 2 had better immunological scores and more immune cells, indicating a stronger immune response. Machine learning screening identified SELENBP1 and CAND1 as important genes in ASD's iron metabolism signaling pathway. These genes express in the brain and have AUC values over 0.8, implying significant predictive power. The present study introduces iron metabolism signaling pathway indicators to predict ASD subtypes. ASD is linked to immune cell infiltration and iron metabolism disorders.

Developmental coupling of brain iron and intrinsic activity in infants during the first 150 days

Brain iron is vital for core neurodevelopmental processes including myelination and neurotransmitter synthesis and, accordingly, iron accumulates in the brain with age. However, little is known about the association between brain iron and neural functioning and how they evolve with age in early infancy. This study investigated brain iron in 48 healthy infants (22 females) aged 64.00 ± 33.28 days by estimating R2 * relaxometry from multi-echo functional MRI (fMRI). Linked independent component analysis was performed to examine the association between iron deposition and spontaneous neural activity, as measured by the amplitude of low frequency fluctuations (ALFF) by interrogating shared component loadings across modalities. Further, findings were validated in an independent dataset (n = 45, 24 females, 77.93 ± 26.18 days). The analysis revealed developmental coupling between the global R2 * and ALFF within the default mode network (DMN). Furthermore, we observed that this coupling effect significantly increased with age (r = 0.78, p = 9.2e-11). Our results highlight the importance of iron-neural coupling during early development and suggest that the neural maturation of the DMN may correspond to growth in distributed brain iron.

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.

Brain Iron Homeostasis and Mental Disorders

Iron plays an essential role in various physiological processes. A disruption in iron homeostasis can lead to severe consequences, including impaired neurodevelopment, neurodegenerative disorders, stroke, and cancer. Interestingly, the link between mental health disorders and iron homeostasis has not received significant attention. Therefore, our understanding of iron metabolism in the context of psychological diseases is incomplete. In this review, we aim to discuss the pathologies and potential mechanisms that relate to iron homeostasis in associated mental disorders. We propose the hypothesis that maintaining brain iron homeostasis can support neuronal physiological functions by impacting key enzymatic activities during neurotransmission, redox balance, and myelination. In conclusion, our review highlights the importance of investigating the relationship between trace element nutrition and the pathological process of mental disorders, focusing on iron. This nutritional perspective can offer valuable insights for the clinical treatment of mental disorders.

Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications

Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ^©RSNA, 2022.

Brain Iron and Mental Health Symptoms in Youth with and without Prenatal Alcohol Exposure

Prenatal alcohol exposure (PAE) negatively affects brain development and increases the risk of poor mental health. We investigated if brain volumes or magnetic susceptibility, an indirect measure of brain iron, were associated with internalizing or externalizing symptoms in youth with and without PAE. T1-weighted and quantitative susceptibility mapping (QSM) MRI scans were collected for 19 PAE and 40 unexposed participants aged 7.5–15 years. Magnetic susceptibility and volume of basal ganglia and limbic structures were extracted using FreeSurfer. Internalizing and Externalizing Problems were assessed using the Behavioural Assessment System for Children (BASC-2-PRS). Susceptibility in the nucleus accumbens was negatively associated with Internalizing Problems, while amygdala susceptibility was positively associated with Internalizing Problems across groups. PAE moderated the relationship between thalamus susceptibility and internalizing symptoms as well as the relationship between putamen susceptibility and externalizing symptoms. Brain volume was not related to internalizing or externalizing symptoms. These findings highlight that brain iron is related to internalizing and externalizing symptoms differently in some brain regions for youth with and without PAE. Atypical iron levels (high or low) may indicate mental health issues across individuals, and iron in the thalamus may be particularly important for behavior in individuals with PAE.

Application of Quantitative Magnetic Resonance Imaging in the Diagnosis of Autism in Children

Objective

To explore the application of quantitative magnetic resonance imaging in the diagnosis of autism in children.

Methods

Sixty autistic children aged 2–3 years and 60 age- and sex-matched healthy children participated in the study. All the children were scanned using head MRI conventional sequences, 3D-T1, diffusion kurtosis imaging (DKI), enhanced T2*- weighted magnetic resonance angiography (ESWAN) and 3D-pseudo continuous Arterial Spin-Labeled (3D-pcASL) sequences. The quantitative susceptibility mapping (QSM), cerebral blood flow (CBF), and brain microstructure of each brain area were compared between the groups, and correlations were analyzed.

Results

The iron content and cerebral blood flow in the frontal lobe, temporal lobe, hippocampus, caudate nucleus, substantia nigra, and red nucleus of the study group were lower than those in the corresponding brain areas of the control group (P < 0.05). The mean kurtosis (MK), radial kurtosis (RK), and axial kurtosis (AK) values of the frontal lobe, temporal lobe, putamen, hippocampus, caudate nucleus, substantia nigra, and red nucleus in the study group were lower than those of the corresponding brain areas in the control group (P < 0.05). The mean diffusivity (MD) and fractional anisotropy of kurtosis (FAK) values of the frontal lobe, temporal lobe and hippocampus in the control group were lower than those in the corresponding brain areas in the study group (P < 0.05). The values of CBF, QSM, and DKI in frontal lobe, temporal lobe and hippocampus could distinguish ASD children (AUC > 0.5, P < 0.05), among which multimodal technology (QSM, CBF, DKI) had the highest AUC (0.917) and DKI had the lowest AUC (0.642).

Conclusion

Quantitative magnetic resonance imaging (including QSM, 3D-pcASL, and DKI) can detect abnormalities in the iron content, cerebral blood flow and brain microstructure in young autistic children, multimodal technology (QSM, CBF, DKI) could be considered as the first choice of imaging diagnostic technology.

Clinical Trial Registration

[http://www.chictr.org.cn/searchprojen.aspx], identifier [ChiCTR2000029699].

Are Essential Trace Elements Effective in Modulation of Mental Disorders? Update and Perspectives

The emergence of mental disorders is associated with several risk factors including genetic and environmental susceptibility. A group of nutrients serves an especially important role in a number of essential neurodevelopmental processes through brain areas promoting the high degree of brain metabolism during early life, although almost all nutrients are needed. These include macronutrients and micronutrients (e.g., iron, magnesium, zinc, copper, selenium). Numerous nutritional psychiatry trials have been performed to examine the correlation of many individual nutrients with mental health, such as essential trace elements. The increased accumulation or lack of such components will facilitate an alternative metabolic pathway that can lead to many diseases and conditions of neurodevelopment. Mental functions have biochemical bases, so the impairment of such neurochemical mechanisms due to lack of trace elements can have mental effects. In psychological conditions such as depression, anxiety, schizophrenia, and autism, scientific studies demonstrate the putative role of trace element deficiency. Therefore, given the critical roles played by essential trace elements in the neurodevelopment and mental health, the effect of these elements' intake on the modulation of psychological functioning is reviewed.

Quantitative susceptibility mapping shows lower brain iron content in children with attention-deficit hyperactivity disorder

To investigate the feasibility of quantitative susceptibility mapping in children with attention‐deficit hyperactivity disorder (ADHD), 53 children with ADHD aged 5–16 years were prospectively selected as the study group and 49 healthy children matched with age and gender were selected as the control group. All children underwent magnetic resonance imaging conventional sequence, 3D‐T1, and enhanced T2*‐weighted magnetic resonance angiography (ESWAN) sequence scanning. The iron content of brain regions was obtained through software postprocessing, and the iron content of brain regions of children with ADHD and healthy children was compared and analyzed to find out the characteristics of the iron content of brain regions of children with ADHD. The iron content in frontal lobe, globus pallidus, caudate nucleus, substantia nigra, putamen, and hippocampus of children with ADHD was lower than that of healthy children (p < .05). There was no significant difference in the content of iron in the left and right brain regions of children with ADHD (p > .05). The volume of frontal lobe and hippocampus of children with ADHD was lower than that of healthy children (p < .05). Iron content in brain areas such as globus pallidus, caudate nucleus, hippocampus, and putamen could distinguish children with ADHD (Area under curve [AUC] > 0.5, p < .05). Quantitative susceptibility mapping showed decreased iron content in some brain regions of children with ADHD.

Diagnosis of children with attention-deficit/hyperactivity disorder (ADHD) comorbid autistic traits (ATs) by applying quantitative magnetic resonance imaging techniques

OBJECTIVE

To explore the feasibility of applying quantitative magnetic resonance imaging techniques for the diagnosis of children with attention-deficit/hyperactivity disorder (ADHD) comorbid autistic traits (ATs).

METHODS

A prospective study was performed by selecting 56 children aged 4-5 years with ADHD-ATs as the study group and 53 sex- and age-matched children with ADHD without ATs as the control group. All children underwent magnetic resonance scans with enhanced T2^*- weighted magnetic resonance angiography (ESWAN), 3D-PCASL, and 3D-T1 sequences. Iron content and cerebral blood flow parameters were obtained via subsequent software processing, and the parameter values in particular brain regions in both groups were compared and analyzed to determine the characteristics of these parameters in children with ADHD-ATs.

RESULTS

Iron content and cerebral blood flow in the frontal lobe, temporal lobe, hippocampus, and caudate nucleus of children with ADHD-ATs were lower than those of children with ADHD without ATs (p < 0.05). Iron content and CBF values in the frontal lobe, temporal lobe and caudate nucleus could distinguish children with ADHD-ATs from those without ATs (AUC > 0.5, p < 0.05).

CONCLUSIONS

Quantitative magnetic resonance techniques could distinguish children with ADHD-ATs.

TRIAL REGISTRATION

This study protocol was registered at the Chinese clinical trial registry (ChiCTR2100046616).

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.

Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms

OBJECTIVE

To develop and validate deep learning (DL) methods for diagnosing autism spectrum disorder (ASD) based on conventional MRI (cMRI) and apparent diffusion coefficient (ADC) images.

METHODS

A total of 151 ASD children and 151 age-matched typically developing (TD) controls were included in this study. The data from these subjects were assigned to training and validation datasets. An additional 20 ASD children and 25 TD controls were acquired, whose data were utilized in an independent test set. All subjects underwent cMRI and diffusion-weighted imaging examination of the brain. We developed a series of DL models to separate ASD from TD based on the cMRI and ADC data. The seven models used include five single-sequence models (SSMs), one dominant-sequence model (DSM), and one all-sequence model (ASM). To enhance the feature detection of the models, we embed an attention mechanism module.

RESULTS

The highest AUC (0.824 ~ 0.850) was achieved when applying the SSM based on either FLAIR or ADC to the validation and independent test sets. A DSM using the combination of FLAIR and ADC showed an improved AUC in the validation (0.873) and independent test sets (0.876). The ASM also showed better diagnostic value in the validation (AUC = 0.838) and independent test sets (AUC = 0.836) compared to the SSMs. Among the models with attention mechanism, the DSM achieved the highest diagnostic performance with an AUC, accuracy, sensitivity, and specificity of 0.898, 84.4%, 85.0%, and 84.0% respectively.

CONCLUSIONS

This study established the potential of DL models to distinguish ASD cases from TD controls based on cMRI and ADC images.

KEY POINTS

• Deep learning models based on conventional MRI and ADC can be used to diagnose ASD. • The model (DSM) based on the FLAIR and ADC sequence achieved the best diagnostic performance with an AUC of 0.836 in the independent test sets. • The attention mechanism further improved the diagnostic performance of the models.

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.