Determination of axonal and dendritic orientation distributions within the developing cerebral cortex by diffusion tensor imaging

Brain tissue microstructure in a prospective, longitudinal, population-based cohort of preterm and term-born young adults

BACKGROUND

Fifteen million infants annually are born prematurely, placing them at high risk for life-long adverse neurodevelopmental outcomes. Whether brain tissue abnormalities that accompany preterm birth persist into young adulthood and are associated with long-term cognitive or psychiatric outcomes is not known.

METHODS

From infancy into young adulthood, we followed a population-based sample of consecutively identified preterm infants and their matched term controls. The preterm group was born at an average gestational age of 31.5 ± 2.6 weeks. We obtained Diffusion Tensor Imaging scans and assessed cognitive and psychiatric outcomes in young adulthood, at a mean age of 19 (range 17.6-20.8) years. Usable data were acquired from 180 participants (89 preterm, 91 term).

RESULTS

Preterm birth was associated with lower fractional anisotropy (FA) and higher average diffusion coefficient (ADC) values in deep white matter tracts of the internal capsule, cerebral peduncles, inferior frontal-occipital fasciculus, sagittal stratum and splenium of the corpus callosum, as well as in grey matter of the caudate, putamen and thalamus. A younger gestational age at birth accentuated these tissue abnormalities. Perinatal characteristics, including lower 5-min APGAR score, history of bronchopulmonary dysplasia, more days of oxygen supplementation and multiple births all increased ADC values in deep white matter tracts and grey matter throughout the brain. Preterm individuals had significantly lower full-scale IQ and more frequent lifetime psychiatric disorders. Those with psychiatric illnesses had significantly higher ADC and lower FA values throughout the deep posterior white matter.

CONCLUSIONS

Abnormalities in brain tissue microstructure associated with preterm birth persist into young adulthood and likely represent disordered myelination and accompanying axonal pathology. These disturbances are associated with a higher likelihood of developing a psychiatric disorder by young adulthood. Brain tissue disturbances were accentuated in those born at younger gestational ages and in those with a history of perinatal complications associated with infection and inflammation.

Multi-tensor fixel-based metrics in tractometry: application to multiple sclerosis

Traditional Diffusion Tensor Imaging (DTI) metrics are affected by crossing fibers and lesions. Most of the previous tractometry works use the single diffusion tensor, which leads to limited sensitivity and challenging interpretation of the results in crossing fiber regions. In this work, we propose a tractometry pipeline that combines white matter tractography with multi-tensor fixel-based metrics. These multi-tensors are estimated using the stable, accurate and robust to noise Multi-Resolution Discrete Search method (MRDS). The spatial coherence of the multi-tensor field estimated with MRDS, which includes up to three anisotropic and one isotropic tensors, is tractography-regularized using the Track Orientation Density Imaging method. Our end-to-end tractometry pipeline goes from raw data to track-specific multi-tensor-metrics tract profiles that are robust to noise and crossing fibers. A comprehensive evaluation conducted in a phantom simulating healthy and damaged tissue with the standard model, as well as in a healthy cohort of 20 individuals scanned along 5 time points, demonstrates the advantages of using multi-tensor metrics over traditional single-tensor metrics in tractometry. Qualitative assessment in a cohort of patients with relapsing-remitting multiple sclerosis reveals that the pipeline effectively detects white matter anomalies in the presence of crossing fibers and lesions.

Microstructural asymmetries of the planum temporale predict functional lateralization of auditory-language processing

Structural hemispheric asymmetry has long been assumed to guide functional lateralization of the human brain, but empirical evidence for this compelling hypothesis remains scarce. Recently, it has been suggested that microstructural asymmetries may be more relevant to functional lateralization than macrostructural asymmetries. To investigate the link between microstructure and function, we analyzed multimodal MRI data in 907 right-handed participants. We quantified structural asymmetry and functional lateralization of the planum temporale (PT), a cortical area crucial for auditory-language processing. We found associations between PT functional lateralization and several structural asymmetries, such as surface area, intracortical myelin content, neurite density, and neurite orientation dispersion. The PT structure also showed hemispheric-specific coupling with its functional activity. All these functional-structural associations are highly specific to within-PT functional activity during auditory-language processing. These results suggest that structural asymmetry underlies functional lateralization of the same brain area and highlights a critical role of microstructural PT asymmetries in auditory-language processing.

Early Infant Prefrontal Cortical Microstructure Predicts Present and Future Emotionality

BACKGROUND

High levels of infant negative emotionality (NE) and low positive emotionality (PE) predict future emotional and behavioral problems. The prefrontal cortex (PFC) supports emotional regulation, with each PFC subregion specializing in specific emotional processes. Neurite orientation dispersion and density imaging estimates microstructural integrity and myelination via the neurite density index (NDI) and dispersion via the orientation dispersion index (ODI), with potential to more accurately evaluate microstructural alterations in the developing brain. Yet, no study has used these indices to examine associations between PFC microstructure and concurrent or developing infant emotionality.

METHODS

We modeled PFC subregional NDI and ODI at 3 months with caregiver-reported infant NE and PE at 3 months (n = 61) and at 9 months (n = 50), using multivariable and subsequent bivariate regression models.

RESULTS

The most robust statistically significant findings were positive associations among 3-month rostral anterior cingulate cortex (ACC) ODI and caudal ACC NDI and concurrent NE, a positive association between 3-month lateral orbitofrontal cortex ODI and prospective NE, and a negative association between 3-month dorsolateral PFC ODI and concurrent PE. Multivariate models also revealed that other PFC subregional microstructure measures, as well as infant and caregiver sociodemographic and clinical factors, predicted infant 3- and 9-month NE and PE.

CONCLUSIONS

Greater NDI and ODI, reflecting greater microstructural complexity, in PFC regions supporting salience perception (rostral ACC), decision making (lateral orbitofrontal cortex), action selection (caudal ACC), and attentional processes (dorsolateral PFC) might result in greater integration of these subregions with other neural networks and greater attention to salient negative external cues, thus higher NE and/or lower PE. These findings provide potential infant cortical markers of future psychopathology risk.

Cortical microstructure and hemispheric specialization-A diffusion-imaging analysis in younger and older adults

Characterizing cortical plasticity becomes increasingly important for identifying compensatory mechanisms and structural reserve in the ageing population. While cortical thickness (CT) largely contributed to systems neuroscience, it incompletely informs about the underlying neuroplastic pathophysiology. In turn, microstructural characteristics may correspond to atrophy mechanisms in a more sensitive way. Fractional anisotropy, a diffusion tensor imaging (DTI) measure, is inversely related to cortical histologic complexity. Axial diffusivity and radial diffusivity are assumed to be linked to the density of structures oriented perpendicular and parallel to the cortical surface, respectively. We hypothesized (1) that cortical DTI will reveal microstructural correlates for hemispheric specialization, particularly in the language and motor systems, and (2) that lateralization of cortical DTI parameters will show an age effect, paralleling age-related changes in activation, especially in the prefrontal cortex. We analysed data from healthy younger and older adult participants (N = 91). DTI and CT data were extracted from regions of the Destrieux atlas. Diffusion measures showed lateralization in specialized motor, language, visual, auditory and inferior parietal cortices. Age-dependent increased lateralization for DTI measures was observed in the prefrontal, angular, superior temporal and lateral occipital cortex. CT did not show any age-dependent alterations in lateralization. Our observations argue that cortical DTI can capture microstructural properties associated with functional specialization, resembling findings from histology. Age effects on diffusion measures in the integrative prefrontal and parietal areas may shed novel light on the atrophy-related plasticity in healthy ageing.

Comparative utility of MRI and EEG for early detection of cortical dysmaturation after postnatal systemic inflammation in the neonatal rat

BACKGROUND

Exposure to postnatal systemic inflammation is associated with increased risk of brain injury in preterm infants, leading to impaired maturation of the cerebral cortex and adverse neurodevelopmental outcomes. However, the optimal method for identifying cortical dysmaturation is unclear. Herein, we compared the utility of electroencephalography (EEG), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) at different recovery times after systemic inflammation in newborn rats.

METHODS

Sprague Dawley rat pups of both sexes received single-daily lipopolysaccharide (LPS; 0.3 mg/kg i.p.; n = 51) or saline (n = 55) injections on postnatal days (P)1, 2, and 3. A subset of these animals were implanted with EEG electrodes. Cortical EEG was recorded for 30 min from unanesthetized, unrestrained pups at P7, P14, and P21, and in separate groups, brain tissues were collected at these ages for ex-vivo MRI analysis (9.4 T) and Golgi-Cox staining (to assess neuronal morphology) in the motor cortex.

RESULTS

Postnatal inflammation was associated with reduced cortical pyramidal neuron arborization from P7, P14, and P21. These changes were associated with dysmature EEG features (e.g., persistence of delta waveforms, higher EEG amplitude, reduced spectral edge frequency) at P7 and P14, and higher EEG power in the theta and alpha ranges at P21. By contrast, there were no changes in cortical DTI or NODDI in LPS rats at P7 or P14, while there was an increase in cortical fractional anisotropy (FA) and decrease in orientation dispersion index (ODI) at P21.

CONCLUSIONS

EEG may be useful for identifying the early evolution of impaired cortical development after early life postnatal systemic inflammation, while DTI and NODDI seem to be more suited to assessing established cortical changes.

Assessing the cortical microstructure in contralesional sensorimotor areas after stroke

Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. Animal data obtained in rats and monkeys have evidenced that contralesional motor areas undergo degenerative alterations in their microstructure which are accompanied by compensatory changes as well. We hypothesized that cortical diffusion imaging can detect similar changes in human stroke survivors. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from two independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy, axial diffusivity, radial diffusivity and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy, axial diffusivity, radial diffusivity and cortical thickness and clinical scores. Against our hypothesis, we did not find any significant alterations in contralesional cortical microstructure after stroke. Likewise, we did not detect any correlations between cortical microstructure and behavioural scores. Future analyses are warranted to investigate whether such alterations might occur in different populations, e.g. in later stages of recovery, in more severely impaired patients, or only in the ipsilesional hemisphere in patients with specific lesion patterns.

Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI

Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-diffusion tensor imaging [DTI] and neurite orientation dispersion and density imaging [NODDI] multicompartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased, and fwe-DTI metrics decreased with age. By applying nonlinear growth models in a vertex-wise analysis, we observed a general posterior-to-anterior pattern of maturation, where the fwe-DTI measures mean diffusivity and radial diffusivity reached peak maturation earlier than the NODDI metrics neurite density index. Using non-negative matrix factorization, we found occipito-parietal cortical regions that correspond to lower order sensory domains mature earlier than fronto-temporal higher order association domains. Our findings corroborate previous histological and neuroimaging studies that show spatially varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically determined regional patterns of change.

White matter microstructural disruption in minimal hepatic encephalopathy: a neurite orientation dispersion and density imaging (NODDI) study

PURPOSE

To evaluate the ability of neurite orientation dispersion and density imaging (NODDI) for detecting white matter (WM) microstructural abnormalities in minimal hepatic encephalopathy (MHE).

METHODS

Diffusion-weighted images, enabling the estimation of NODDI and diffusion tensor imaging (DTI) parameters, were acquired from 20 healthy controls (HC), 22 cirrhotic patients without MHE (NHE), and 15 cirrhotic patients with MHE. Tract-based spatial statistics were used to determine differences in DTI (including fractional anisotropy [FA] and mean/axial/radial diffusivity [MD/AD/RD]) and NODDI parameters (including neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISO]). Voxel-wise analyses of correlations between diffusion parameters and neurocognitive performance determined by Psychometric Hepatic Encephalopathy Score (PHES) were completed.

RESULTS

MHE patients had extensive NDI reduction and rare ODI reduction, primarily involving the genu and body of corpus callosum and the bilateral frontal lobe, corona radiata, external capsule, anterior limb of internal capsule, temporal lobe, posterior thalamic radiation, and brainstem. The extent of NDI and ODI reduction expanded from NHE to MHE. In both MHE and NHE groups, the extent of NDI change was quite larger than that of FA change. No significant intergroup difference in ISO/MD/AD/RD was observed. Tissue specificity afforded by NODDI revealed the underpinning of FA reduction in MHE. The NDI in left frontal lobe was significantly correlated with PHES.

CONCLUSION

MHE is characterized by diffuse WM microstructural impairment (especially neurite density reduction). NODDI can improve the detection of WM microstructural impairments in MHE and provides more precise information about MHE-related pathology than DTI.

Mapping the individual human cortex using multidimensional MRI and unsupervised learning

Human evolution has seen the development of higher-order cognitive and social capabilities in conjunction with the unique laminar cytoarchitecture of the human cortex. Moreover, early-life cortical maldevelopment has been associated with various neurodevelopmental diseases. Despite these connections, there is currently no noninvasive technique available for imaging the detailed cortical laminar structure. This study aims to address this scientific and clinical gap by introducing an approach for imaging human cortical lamina. This method combines diffusion-relaxation multidimensional MRI with a tailored unsupervised machine learning approach that introduces enhanced microstructural sensitivity. This new imaging method simultaneously encodes the microstructure, the local chemical composition and importantly their correlation within complex and heterogenous tissue. To validate our approach, we compared the intra-cortical layers obtained using our ex vivo MRI-based method with those derived from Nissl staining of postmortem human brain specimens. The integration of unsupervised learning with diffusion-relaxation correlation MRI generated maps that demonstrate sensitivity to areal differences in cytoarchitectonic features observed in histology. Significantly, our observations revealed layer-specific diffusion-relaxation signatures, showing reductions in both relaxation times and diffusivities at the deeper cortical levels. These findings suggest a radial decrease in myelin content and changes in cell size and anisotropy, reflecting variations in both cytoarchitecture and myeloarchitecture. Additionally, we demonstrated that 1D relaxation and high-order diffusion MRI scalar indices, even when aggregated and used jointly in a multimodal fashion, cannot disentangle the cortical layers. Looking ahead, our technique holds the potential to open new avenues of research in human neurodevelopment and the vast array of disorders caused by disruptions in neurodevelopment.

Evaluating Fiber Orientation Dispersion Measures Computed From Single-Shell Diffusion MRI

Fiber orientation dispersion is one of the fundamental features that can be estimated from diffusion magnetic resonance imaging (dMRI) of the brain. Several approaches have been proposed to estimate dispersion from single- and multi-shell dMRI acquisitions. Here, we derive solutions to bring these proposed methods to a standard orientation dispersion index (ODI) with the goal of making them comparable across different dMRI acquisitions. To illustrate the utility of the measures in studying brain aging, we further examined the age-dependent trajectory of the different single- and multi-shell ODI estimates in the white matter across the lifespan.Clinical Relevance- This work computes metrics of brain microstructure that can be adapted for large neuroimaging initiatives that aim to study the brain's development and aging, and to identify deviations that may serve as biomarkers of brain disease.

Altered microstructure of the contralesional ventral premotor cortex and motor output after stroke

Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas, and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy and cortical thickness and clinical scores. Compared with controls, stroke patients exhibited a reduction in fractional anisotropy in the contralesional ventral premotor cortex (P = 0.005). Fractional anisotropy of the other regions and cortical thickness did not show a comparable group difference. Higher fractional anisotropy of the ventral premotor cortex, but not cortical thickness, was positively associated with residual grip force in the stroke patients. These data provide novel evidence that the contralesional ventral premotor cortex might constitute a key sensorimotor area particularly susceptible to stroke-related alterations in cortical microstructure as measured by diffusion MRI and they suggest a link between these changes and residual motor output after stroke.

Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI

Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-DTI and NODDI multi-compartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased and fwe-DTI metrics decreased with age. Using non-negative matrix factorization, we found cortical regions that correspond to lower-order sensory regions mature earlier than higher-order association regions. Our findings corroborate previous histological and neuroimaging studies that show spatially-varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically-determined regional patterns of change.

Individual electric field predicts functional connectivity changes after anodal transcranial direct-current stimulation in chronic stroke

The neuromodulation effect of anodal tDCS is not thoroughly studied, and the heterogeneous profile of stroke individuals with brain lesions would further complicate the stimulation outcomes. This study aimed to investigate the functional changes in sensorimotor areas induced by anodal tDCS and whether individual electric field could predict the functional outcomes. Twenty-five chronic stroke survivors were recruited and divided into tDCS group (n = 12) and sham group (n = 13). Increased functional connectivity (FC) within the surrounding areas of ipsilesional primary motor cortex (M1) was only observed after anodal tDCS. Averaged FC among the ipsilesional sensorimotor regions was observed to be increased after anodal tDCS (t(11) = 2.57, p = 0.026), but not after sham tDCS (t(12) = 0.69, p = 0.50). Partial least square analysis identified positive correlations between electric field (EF) strength normal to the ipsilesional M1 surface and individual FC changes in tDCS group (r = 0.84, p < 0.001) but not in sham group (r = 0.21, p = 0.5). Our results indicated anodal tDCS facilitates the FC within the ipsilesional sensorimotor network in chronic stroke subjects, and individual electric field predicts the functional outcomes.

Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children

The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.

Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology

Preterm brains commonly exhibit elevated signal intensity in the white matter on T2-weighted MRI at term-equivalent age. This signal, known as diffuse excessive high signal intensity (DEHSI) or diffuse white matter abnormality (DWMA) when quantitatively assessed, is associated with abnormal microstructure on diffusion tensor imaging. However, postmortem data are largely lacking and difficult to obtain, and the pathological significance of DEHSI remains in question. In a cohort of 202 infants born preterm at ≤32 weeks gestational age, we leveraged two newer diffusion MRI models - Constrained Spherical Deconvolution (CSD) and neurite orientation dispersion and density index (NODDI) - to better characterize the macro and microstructural properties of DWMA and inform the ongoing debate around the clinical significance of DWMA. With increasing DWMA volume, fiber density broadly decreased throughout the white matter and fiber cross-section decreased in the major sensorimotor tracts. Neurite orientation dispersion decreased in the centrum semiovale, corona radiata, and temporal lobe. These findings provide insight into DWMA's biological underpinnings and demonstrate that it is a serious pathology.

Diffusion MRI anisotropy in the cerebral cortex is determined by unmyelinated tissue features

Diffusion magnetic resonance imaging (dMRI) is commonly used to assess the tissue and cellular substructure of the human brain. In the white matter, myelinated axons are the principal neural elements that shape dMRI through the restriction of water diffusion; however, in the gray matter the relative contributions of myelinated axons and other tissue features to dMRI are poorly understood. Here we investigate the determinants of diffusion in the cerebral cortex. Specifically, we ask whether myelinated axons significantly shape dMRI fractional anisotropy (dMRI-FA), a measure commonly used to characterize tissue properties in humans. We compared ultra-high resolution ex vivo dMRI data from the brain of a marmoset monkey with both myelin- and Nissl-stained histological sections obtained from the same brain after scanning. We found that the dMRI-FA did not match the spatial distribution of myelin in the gray matter. Instead dMRI-FA was more closely related to the anisotropy of stained tissue features, most prominently those revealed by Nissl staining and to a lesser extent those revealed by myelin staining. Our results suggest that unmyelinated neurites such as large caliber apical dendrites are the primary features shaping dMRI measures in the cerebral cortex.

Associations of Human Milk Oligosaccharides with Infant Brain Tissue Organization and Regional Blood Flow at 1 Month of Age

Animal studies have shown that human milk oligosaccharides (HMOs) are important in early brain development, yet their roles have not been assessed in humans. The purpose of this study was to determine the associations of HMOs with MRI indices of tissue microstructure and regional cerebral blood flow (rCBF) in infants. Mother–infant pairs (N = 20) were recruited at 1 month postpartum. Milk was assayed for the concentrations of the HMOs 2′-fucosyllactose (2′FL), 3-fucosyllactose (3FL), 3′-sialyllactose (3′SL), and 6′-sialyllactose (6′SL). Diffusion and arterial spin labeling measures were acquired using a 3.0-Tesla MRI scanner. Multiple linear regression was used to assess the voxel-wise associations of HMOs with fractional anisotropy (FA), mean diffusivity (MD), and rCBF values across the brain. After adjusting for pre-pregnancy BMI, sex, birthweight, and postmenstrual age at time of scan, a higher 2′FL concentration was associated with reduced FA, increased MD, and reduced rCBF in similar locations within the cortical mantle. Higher 3FL and 3′SL concentrations were associated with increased FA, reduced MD, and increased rCBF in similar regions within the developing white matter. The concentration of 6′SL was not associated with MRI indices. Our data reveal that fucosylated and sialylated HMOs differentially associate with indices of tissue microstructure and rCBF, suggesting specific roles for 2′FL, 3FL, and 3′SL in early brain maturation.

Investigating the contribution of cytoarchitecture to diffusion MRI measures in gray matter using histology

Postmortem studies are currently considered a gold standard for investigating brain structure at the cellular level. To investigate cellular changes in the context of human development, aging, or disease treatment, non-invasive in-vivo imaging methods such as diffusion MRI (dMRI) are needed. However, dMRI measures are only indirect measures and require validation in gray matter (GM) in the context of their sensitivity to the underlying cytoarchitecture, which has been lacking. Therefore, in this study we conducted direct comparisons between in-vivo dMRI measures and histology acquired from the same four rhesus monkeys. Average and heterogeneity of fractional anisotropy and trace from diffusion tensor imaging and mean squared displacement (MSD) and return-to-origin-probability from biexponential model were calculated in nine cytoarchitectonically different GM regions using dMRI data. DMRI measures were compared with corresponding histology measures of regional average and heterogeneity in cell area density. Results show that both average and heterogeneity in trace and MSD measures are sensitive to the underlying cytoarchitecture (cell area density) and capture different aspects of cell composition and organization. Trace and MSD thus would prove valuable as non-invasive imaging biomarkers in future studies investigating GM cytoarchitectural changes related to development and aging as well as abnormal cellular pathologies in clinical studies.

Using tissue microstructure and multimodal MRI to parse the phenotypic heterogeneity and cellular basis of autism spectrum disorder

BACKGROUND

Identifying the brain bases for phenotypic heterogeneity in Autism Spectrum Disorder (ASD) will advance understanding of its pathogenesis and improve its clinical management.

METHODS

We compared Diffusion Tensor Imaging (DTI) indices and connectome measures between 77 ASD and 88 Typically Developing (TD) control participants. We also assessed voxel-wise associations of DTI indices with measures of regional cerebral blood flow (rCBF) and N-acetylaspartate (NAA) to understand how tissue microstructure associates with cellular metabolism and neuronal density, respectively.

RESULTS

Autism Spectrum Disorder participants had significantly lower fractional anisotropy (FA) and higher diffusivity values in deep white matter tracts, likely representing ether reduced myelination by oligodendrocytes or a reduced density of myelinated axons. Greater abnormalities in these measures and regions were associated with higher ASD symptom scores. Participant age, sex and IQ significantly moderated these group differences. Path analyses showed that reduced NAA levels accounted significantly for higher diffusivity and higher rCBF values in ASD compared with TD participants.

CONCLUSIONS

Reduced neuronal density (reduced NAA) likely underlies abnormalities in DTI indices of white matter microstructure in ASD, which in turn are major determinants of elevated blood flow. Together, these findings suggest the presence of reduced axonal density and axonal pathology in ASD white matter. Greater pathology in turn accounts for more severe symptoms, lower intellectual ability, and reduced global efficiency for measures of white matter connectivity in ASD.

Neurite dispersion and density mediates the relationship between cardiorespiratory fitness and cognition in healthy younger adults

Growing evidence suggests physical activity and cardiorespiratory fitness are associated with better cognition across the lifespan. However, the neurobiological underpinnings relating fitness and cognition remain unclear, particularly in healthy younger adults. Using a well-established and popular multi-compartment diffusion modeling approach, called Neurite Orientation and Dispersion and Density Imaging (NODDI), we investigated the relationship between physical fitness (measured via a 2-min walk test), cognition (fluid and crystallized), and gray and white matter microstructure, in a large sample (n = 816) of healthy younger adults (ages 22-35 years) from the human connectome project (HCP). Concurrent with previous literature, we found that fitness was positively associated with both fluid and crystallized cognition. Furthermore, we found that physical fitness was negatively associated with white matter orientation dispersion index (ODIWM) around the cerebellar peduncle and was negatively associated with widespread cortical and subcortical gray matter neurite density index (NDIGM). Lower ODIWM of the cerebral peduncle was associated with better fluid cognitive performance, while lower NDIGM was associated with better crystallized cognition. Finally, we found that while ODIWM partially mediated the relationship between fitness and fluid cognition, NDIGM partially mediated the relationship between fitness and crystallized cognition. This study is the first to explore the relationship between physical fitness and white and gray matter microstructure measures using NODDI. Our findings suggest that in addition to improved cognitive performance, higher physical fitness may be associated with lower white matter tract dispersion and lower neurite density in the cortical and subcortical gray matter of healthy younger adults.

Multimodal Neuroimaging in Rett Syndrome With MECP2 Mutation

Rett syndrome (RTT) is a rare neurodevelopmental disorder characterized by severe cognitive, social, and physical impairments resulting from de novo mutations in the X-chromosomal methyl-CpG binding protein gene 2 (MECP2). While there is still no cure for RTT, exploring up-to date neurofunctional diagnostic markers, discovering new potential therapeutic targets, and searching for novel drug efficacy evaluation indicators are fundamental. Multiple neuroimaging studies on brain structure and function have been carried out in RTT-linked gene mutation carriers to unravel disease-specific imaging features and explore genotype-phenotype associations. Here, we reviewed the neuroimaging literature on this disorder. MRI morphologic studies have shown global atrophy of gray matter (GM) and white matter (WM) and regional variations in brain maturation. Diffusion tensor imaging (DTI) studies have demonstrated reduced fractional anisotropy (FA) in left peripheral WM areas, left major WM tracts, and cingulum bilaterally, and WM microstructural/network topology changes have been further found to be correlated with behavioral abnormalities in RTT. Cerebral blood perfusion imaging studies using single-photon emission CT (SPECT) or PET have evidenced a decreased global cerebral blood flow (CBF), particularly in prefrontal and temporoparietal areas, while magnetic resonance spectroscopy (MRS) and PET studies have contributed to unraveling metabolic alterations in patients with RTT. The results obtained from the available reports confirm that multimodal neuroimaging can provide new insights into a complex interplay between genes, neurotransmitter pathway abnormalities, disease-related behaviors, and clinical severity. However, common limitations related to the available studies include small sample sizes and hypothesis-based and region-specific approaches. We, therefore, conclude that this field is still in its early development phase and that multimodal/multisequence studies with improved post-processing technologies as well as combined PET–MRI approaches are urgently needed to further explore RTT brain alterations.

Diffusion MRI signal cumulants and hepatocyte microstructure at fixed diffusion time: Insights from simulations, 9.4T imaging, and histology

Purpose

Relationships between diffusion‐weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange?

Methods

Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity L/D0, and clinical protocols (single diffusion encoding; maximum b‐value: {1000, 1500, 2000} s/mm²; 5 unique gradient duration/separation pairs; SNR = {∞, 100, 80, 40, 20}), accounting for heterogeneity in (D0,L) and perfusion contamination. Diffusion (D) and kurtosis (K) coefficients were calculated, and relationships between (D0,L) and (D,K) were visualized. Functions mapping (D,K) to (D0,L) were computed to predict unseen (D0,L) values, tested for their ability to classify discrete cell‐size contrasts, and deployed on 9.4T ex vivo MRI‐histology data of fixed mouse livers

Results

Relationships between (D,K) and (D0,L) are complex and depend on the diffusion encoding. Functions mapping D,K to (D0,L) captures salient characteristics of D0(D,K) and L(D,K) dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three‐class cell‐size classification task (for SNR = 20, bmax = 1500 s/mm², δ = 20 ms, and Δ = 75 ms). MRI detects cell‐size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes.

Conclusion

Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.

Single-shell NODDI using dictionary-learner-estimated isotropic volume fraction

Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular, and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize brain tissue microstructure. Single-shell reconstruction for NODDI parameters has been discouraged in previous studies caused by failure when fitting, especially for the neurite density index (NDI). Here, we investigated the possibility of creating robust NODDI parameter maps with single-shell data, using the isotropic volume fraction (f_ISO ) as a prior. Prior estimation was made independent of the NODDI model constraint using a dictionary learning approach. First, we used a stochastic sparse dictionary-based network (DictNet), which is trained with data obtained from in vivo and simulated diffusion MRI data, to predict f_ISO . In single-shell cases, the mean diffusivity and raw T₂ signal with no diffusion weighting (S₀ ) was incorporated in the dictionary for the f_ISO estimation. Then, the NODDI framework was used with the known f_ISO to estimate the NDI and orientation dispersion index (ODI). The f_ISO estimated using our model was compared with other f_ISO estimators in the simulation. Further, using both synthetic data simulation and human data collected on a 3 T scanner (both high-quality HCP and clinical dataset), we compared the performance of our dictionary-based learning prior NODDI (DLpN) with the original NODDI for both single-shell and multi-shell data. Our results suggest that DLpN-derived NDI and ODI parameters for single-shell protocols are comparable with original multi-shell NODDI, and the protocol with b = 2000 s/mm² performs the best (error ~ 5% in white and gray matter). This may allow NODDI evaluation of studies on single-shell data by multi-shell scanning of two subjects for DictNet f_ISO training.

Neurite density imaging in amygdala nuclei reveals interindividual differences in neuroticism

Neuroticism is known to have significant health implications. While previous research revealed that interindividual differences in the amygdala function are associated with interindividual differences in neuroticism, the impact of the amygdala’s structure and especially microstructure on variations in neuroticism remains unclear. Here, we present the first study using NODDI to examine the association between the in vivo microstructural architecture of the amygdala and neuroticism at the level of neurites. We, therefore, acquired brain images from 221 healthy participants using advanced multi‐shell diffusion‐weighted imaging. Because the amygdala comprises several nuclei, we, moreover, used a high‐resolution T1 image to automatically segment the amygdala into eight different nuclei. Neuroticism and its facets have been assessed using the NEO‐PI‐R. Finally, we associated neuroticism and its facets with the volume and microstructure of the amygdala nuclei. Statistical analysis revealed that lower neurite density in the lateral amygdala nucleus (La) was significantly associated with higher scores in depression, one of the six neuroticism facets. The La is the sensory relay of the amygdala, filtering incoming information based on previous experiences. Reduced neurite density and related changes in the dendritic structure of the La could impair its filtering function. This again might cause harmless sensory information to be misevaluated as threatening and lead to the altered amygdala responsivity as reported in previous studies investigating the functional correlates of neuroticism and neuroticism‐related disorders like depression.

High fidelity fiber orientation density functions from fiber ball imaging

The fiber orientation density function (fODF) in white matter is a primary physical quantity that can be estimated with diffusion MRI. It has often been employed for fiber tracking and microstructural modeling. Requirements for the construction of high fidelity fODFs, in the sense of having good angular resolution, adequate data to avoid sampling errors, and minimal noise artifacts, are described for fODFs calculated with fiber ball imaging. A criterion is formulated for the number of diffusion encoding directions needed to achieve a given angular resolution. The advantages of using large b-values (≥6000 s/mm² ) are also discussed. For the direct comparison of different fODFs, a method is developed for defining a local frame of reference tied to each voxel's individual axonal structure. The Matusita anisotropy axonal is proposed as a scalar fODF measure for quantifying angular variability. Experimental results, obtained at 3 T from human volunteers, are used as illustrations.

Microstructural Tissue Changes in a Rat Model of Mild Traumatic Brain Injury

Our study investigates the potential of diffusion MRI (dMRI), including diffusion tensor imaging (DTI), fixel-based analysis (FBA) and neurite orientation dispersion and density imaging (NODDI), to detect microstructural tissue abnormalities in rats after mild traumatic brain injury (mTBI). The brains of sham-operated and mTBI rats 35 days after lateral fluid percussion injury were imaged ex vivo in a 11.7-T scanner. Voxel-based analyses of DTI-, fixel- and NODDI-based metrics detected extensive tissue changes in directly affected brain areas close to the primary injury, and more importantly, also in distal areas connected to primary injury and indirectly affected by the secondary injury mechanisms. Histology revealed ongoing axonal abnormalities and inflammation, 35 days after the injury, in the brain areas highlighted in the group analyses. Fractional anisotropy (FA), fiber density (FD) and fiber density and fiber bundle cross-section (FDC) showed similar pattern of significant areas throughout the brain; however, FA showed more significant voxels in gray matter areas, while FD and FDC in white matter areas, and orientation dispersion index (ODI) in areas most damage based on histology. Region-of-interest (ROI)-based analyses on dMRI maps and histology in selected brain regions revealed that the changes in MRI parameters could be attributed to both alterations in myelinated fiber bundles and increased cellularity. This study demonstrates that the combination of dMRI methods can provide a more complete insight into the microstructural alterations in white and gray matter after mTBI, which may aid diagnosis and prognosis following a mild brain injury.

A model of tension-induced fiber growth predicts white matter organization during brain folding

The past decade has experienced renewed interest in the physical processes that fold the developing cerebral cortex. Biomechanical models and experiments suggest that growth of the cortex, outpacing growth of underlying subcortical tissue (prospective white matter), is sufficient to induce folding. However, current models do not explain the well-established links between white matter organization and fold morphology, nor do they consider subcortical remodeling that occurs during the period of folding. Here we propose a framework by which cortical folding may induce subcortical fiber growth and organization. Simulations incorporating stress-induced fiber elongation indicate that subcortical stresses resulting from folding are sufficient to induce stereotyped fiber organization beneath gyri and sulci. Model predictions are supported by high-resolution ex vivo diffusion tensor imaging of the developing rhesus macaque brain. Together, results provide support for the theory of cortical growth-induced folding and indicate that mechanical feedback plays a significant role in brain connectivity.

Cortical Thickness Differences Are Associated With Chemical Synaptic Transmission Upregulated Genes in Degeneration of Mild Cognitive Impairment

Mild cognitive impairment (MCI) is a transition between normal cognition (NC) and Alzheimer’s disease (AD). Differences in cortical thickness (ΔCT) have been reported in cases that degenerate from MCI to AD. The aspects of genetic and transcriptional variation related to ΔCT are vague. In this study, using an 8-year longitudinal follow-up outcome, we investigated the genetic correlates of ΔCT in MCI subjects with degeneration from MCI to AD (MCI_AD). We employed partial least squares regression (PLSR) on brain T1-weighted magnetic resonance imaging (MRI) images of 180 participants [143 stable MCI (MCI_S) participants and 37 MCI_AD participants] and brain gene expression data from the Allen Institute for Brain Science (AIBS) database to investigate genes associated with ΔCT. We found that upregulated PLS component 1 ΔCT-related genes were enriched in chemical synaptic transmission. To verify the robustness and specificity of the results, we conducted PLSR analysis invalidation and specificity datasets and performed weighted gene co-expression network analysis instead of PLSR for the above three datasets. We also used gene expression data in the brain prefrontal cortex from the Gene Expression Omnibus (GEO) database to indirectly validate the robustness and specificity of our results. We conclude that transcriptionally upregulated genes involved in chemical synaptic transmission are strongly related to global ΔCT in MCI patients who experience degeneration from MCI to AD.

Synchrotron X-ray micro-CT as a validation dataset for diffusion MRI in whole mouse brain

PURPOSE

To introduce synchrotron X-ray microcomputed tomography (microCT) and demonstrate its use as a natively isotropic, nondestructive, 3D validation modality for diffusion MRI in whole, fixed mouse brain.

METHODS

Postmortem diffusion MRI and microCT data were acquired of the same whole mouse brain. Diffusion data were processed using constrained spherical deconvolution. Synchrotron data were acquired at an isotropic voxel size of 1.17 μm. Structure tensor analysis was used to calculate fiber orientation distribution functions from the microCT data. A pipeline was developed to spatially register the 2 datasets in order to perform qualitative comparisons of fiber geometries represented by fiber orientation distribution functions. Fiber orientations from both modalities were used to perform whole-brain deterministic tractography to demonstrate validation of long-range white matter pathways.

RESULTS

Fiber orientation distribution functions were able to be extracted throughout the entire microCT dataset, with spatial registration to diffusion MRI simplified due to the whole brain extent of the microCT data. Fiber orientations and tract pathways showed good agreement between modalities.

CONCLUSION

Synchrotron microCT is a potentially valuable new tool for future multi-scale diffusion MRI validation studies, providing comparable value to optical histology validation methods while addressing some key limitations in data acquisition and ease of processing.

Comparison of Neurite Orientation Dispersion and Density Imaging and Two-Compartment Spherical Mean Technique Parameter Maps in Multiple Sclerosis

Background: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT parameters due to multiple sclerosis (MS) pathology in clinical settings.

Purpose: To compare group-wise differences between healthy controls and MS patients in NODDI and SMT metrics, investigating associations with disability and correlations with diffusion tensor imaging (DTI) metrics.

Methods: Sixty three relapsing-remitting MS patients were compared to 28 healthy controls. NODDI and SMT metrics corresponding to intracellular volume fraction (v_in), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (v_iso) (NODDI only) were calculated from diffusion MRI data, alongside DTI metrics (fractional anisotropy, FA; axial/mean/radial diffusivity, AD/MD/RD). Correlations between all pairs of MRI metrics were calculated in normal-appearing white matter (NAWM). Associations with expanded disability status scale (EDSS), controlling for age and gender, were evaluated. Patient-control differences were assessed voxel-by-voxel in MNI space controlling for age and gender at the 5% significance level, correcting for multiple comparisons. Spatial overlap of areas showing significant differences were compared using Dice coefficients.

Results: NODDI and SMT show significant associations with EDSS (standardised beta coefficient −0.34 in NAWM and −0.37 in lesions for NODDI v_in; 0.38 and −0.31 for SMT ODE and v_in in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI v_in and SMT v_in strongly correlated (r = 0.72, p < 0.05), likewise NODDI ODI and SMT ODE (r = −0.80, p < 0.05). All DTI, NODDI and SMT metrics detect widespread differences between patients and controls in NAWM (12.57% and 11.90% of MNI brain mask for SMT and NODDI v_in, Dice overlap of 0.42).

Data Conclusion: SMT and NODDI detect significant differences in white matter microstructure between MS patients and controls, concurring on the direction of these changes, providing consistent descriptors of tissue microstructure that correlate with disability and show alterations beyond focal damage. Our study suggests that NODDI and SMT may play a role in monitoring MS in clinical trials and practice.

Cytosolic diffusivity and microscopic anisotropy of N-acetyl aspartate in human white matter with diffusion-weighted MRS at 7 T

Metabolite diffusion measurable in humans in vivo with diffusion-weighted spectroscopy (DW-MRS) provides a window into the intracellular morphology and state of specific cell types. Anisotropic diffusion in white matter is governed by the microscopic properties of the individual cell types and their structural units (axons, soma, dendrites). However, anisotropy is also markedly affected by the macroscopic orientational distribution over the imaging voxel, particularly in DW-MRS, where the dimensions of the volume of interest (VOI) are much larger than those typically used in diffusion-weighted imaging. One way to address the confound of macroscopic structural features is to average the measurements acquired with uniformly distributed gradient directions to mimic a situation where fibers present in the VOI are orientationally uniformly distributed. This situation allows the extraction of relevant microstructural features such as transverse and longitudinal diffusivities within axons and the related microscopic fractional anisotropy. We present human DW-MRS data acquired at 7 T in two different white matter regions, processed and analyzed as described above, and find that intra-axonal diffusion of the neuronal metabolite N-acetyl aspartate is in good correspondence to simple model interpretations, such as multi-Gaussian diffusion from disperse fibers where the transverse diffusivity can be neglected. We also discuss the implications of our approach for current and future applications of DW-MRS for cell-specific measurements.

Neurite Orientation Dispersion and Density Imaging of Rat Brain Microstructural Changes due to Middle Cerebral Artery Occlusion at a 3T MRI

The purpose of this work was to demonstrate the feasibility of neurite orientation dispersion and density imaging (NODDI) in characterizing the brain tissue microstructural changes of middle cerebral artery occlusion (MCAO) in rats at 3T MRI, and to validate NODDI metrics with histology. A multi-shell diffusion MRI protocol was performed on 11 MCAO rats and 10 control rats at different post-operation time points of 0.5, 2, 6, 12, 24 and 72 h. NODDI orientation dispersion index (ODI) and intracellular volume fraction (V_ic) metrics were compared between MCAO group and control group. The evolution of NODDI metrics was characterized and validated by histology. Infarction was consistent with significantly increased ODI and V_ic in comparison to control tissues at all time points (P<0.001). Lesion ODI increased gradually from 0.5 to 72 h, while its V_ic showed a more complicated and fluctuated evolution. ODI and V_ic were significantly different between hyperacute and acute stroke periods (P<0.001). The NODDI metrics were found to be consistent with the histological findings. In conclusion, NODDI can reflect microstructural changes of brain tissues in MCAO rats at 3T MRI and the metrics are consistent with histology. This study helps to prepare NODDI for the diagnosis and management of ischemic stroke in translational research and clinical practice.

Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging

BACKGROUND

The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease.

NEW METHOD

This is the second review on the topic of g-ratio mapping using MRI.

RESULTS

This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches.

COMPARISON WITH EXISTING METHODS

Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology.

CONCLUSIONS

We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.

Diffusion kurtosis imaging of gray matter in young adults with autism spectrum disorder

Prior ex vivo histological postmortem studies of autism spectrum disorder (ASD) have shown gray matter microstructural abnormalities, however, in vivo examination of gray matter microstructure in ASD has remained scarce due to the relative lack of non-invasive methods to assess it. The aim of this work was to evaluate the feasibility of employing diffusional kurtosis imaging (DKI) to describe gray matter abnormalities in ASD in vivo. DKI data were examined for 16 male participants with a diagnosis of ASD and IQ>80 and 17 age- and IQ-matched male typically developing (TD) young adults 18-25 years old. Mean (MK), axial (AK), radial (RK) kurtosis and mean diffusivity (MD) metrics were calculated for lobar and sub-lobar regions of interest. Significantly decreased MK, RK, and MD were found in ASD compared to TD participants in the frontal and temporal lobes and several sub-lobar regions previously associated with ASD pathology. In ASD participants, decreased kurtosis in gray matter ROIs correlated with increased repetitive and restricted behaviors and poor social interaction symptoms. Decreased kurtosis in ASD may reflect a pathology associated with a less restrictive microstructural environment such as decreased neuronal density and size, atypically sized cortical columns, or limited dendritic arborizations.

Maternal cortisol is associated with neonatal amygdala microstructure and connectivity in a sexually dimorphic manner

The mechanisms linking maternal stress in pregnancy with infant neurodevelopment in a sexually dimorphic manner are poorly understood. We tested the hypothesis that maternal hypothalamic-pituitary-adrenal axis activity, measured by hair cortisol concentration (HCC), is associated with microstructure, structural connectivity, and volume of the infant amygdala. In 78 mother-infant dyads, maternal hair was sampled postnatally, and infants underwent magnetic resonance imaging at term-equivalent age. We found a relationship between maternal HCC and amygdala development that differed according to infant sex. Higher HCC was associated with higher left amygdala fractional anisotropy (β = 0.677, p=0.010), lower left amygdala orientation dispersion index (β = −0.597, p=0.034), and higher fractional anisotropy in connections between the right amygdala and putamen (β = 0.475, p=0.007) in girls compared to boys. Furthermore, altered amygdala microstructure was only observed in boys, with connectivity changes restricted to girls. Maternal cortisol during pregnancy is related to newborn amygdala architecture and connectivity in a sexually dimorphic manner. Given the fundamental role of the amygdala in the emergence of emotion regulation, these findings offer new insights into mechanisms linking maternal health with neuropsychiatric outcomes of children.

Stress during pregnancy, for example because of mental or physical disorders, can have long-term effects on child development. Epidemiological studies have shown that individuals exposed to stress in the womb are at higher risk of developmental and mood conditions, such as ADHD and depression. This effect is different between the sexes, and the biological mechanisms that underpin these observations are poorly understood.

One possibility is that a baby’s developing amygdala, the part of the brain that processes emotions, is affected by a signal known as cortisol. This hormone is best known for its role in coordinating the stress response, but it also directs the growth of a fetus. Tracking fetal amygdala changes as well as cortisol levels in the pregnant individual could explain how stress during pregnancy affects development.

To investigate, Stoye et al. recruited nearly 80 volunteers and their newborn children. MRI scans were used to examine the structure of the amygdala, and how it is connected to other parts of the brain. In parallel, the amount of cortisol was measured in hair samples collected from the volunteers around the time of birth, which reflects stress levels during the final three months of pregnancy.

Linking the brain imaging results to the volunteers’ cortisol levels showed that being exposed to higher cortisol levels in the womb affected babies in different ways based on their sex: boys showed alterations in the fine structure of their amygdala, while girls displayed changes in the way that brain region connected to other neural networks.

The work by Stoye et al. potentially reveals a biological mechanism by which early exposure to stress could affect brain development differently between the sexes, potentially informing real-world interventions.

Assessment of the structural complexity of diffusion MRI voxels using 3D electron microscopy in the rat brain

Validation and interpretation of diffusion magnetic resonance imaging (dMRI) requires detailed understanding of the actual microstructure restricting the diffusion of water molecules. In this study, we used serial block-face scanning electron microscopy (SBEM), a three-dimensional electron microscopy (3D-EM) technique, to image seven white and grey matter volumes in the rat brain. SBEM shows excellent contrast of cellular membranes, which are the major components restricting the diffusion of water in tissue. Additionally, we performed 3D structure tensor (3D-ST) analysis on the SBEM volumes and parameterised the resulting orientation distributions using Watson and angular central Gaussian (ACG) probability distributions as well as spherical harmonic (SH) decomposition. We analysed how these parameterisations described the underlying orientation distributions and compared their orientation and dispersion with corresponding parameters from two dMRI methods, neurite orientation dispersion and density imaging (NODDI) and constrained spherical deconvolution (CSD). Watson and ACG parameterisations and SH decomposition captured well the 3D-ST orientation distributions, but ACG and SH better represented the distributions due to its ability to model asymmetric dispersion. The dMRI parameters corresponded well with the 3D-ST parameters in the white matter volumes, but the correspondence was less evident in the more complex grey matter. SBEM imaging and 3D-ST analysis also revealed that the orientation distributions were often not axially symmetric, a property neatly captured by the ACG distribution. Overall, the ability of SBEM to image diffusion barriers in intricate detail, combined with 3D-ST analysis and parameterisation, provides a step forward toward interpreting and validating the dMRI signals in complex brain tissue microstructure.

Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity

Diffusion tensor imaging (DTI) has fundamentally transformed how we interrogate diseases and disorders of the brain in neuropsychiatric illness. DTI and recently developed multicompartment diffusion-weighted imaging (MC-DWI) techniques, such as NODDI (neurite orientation dispersion and density imaging), measure diffusion anisotropy presuming a static neuroglial environment; however, microglial morphology and density are highly dynamic in psychiatric illness, and how alterations in microglial density might influence intracellular measures of diffusion anisotropy in DTI and MC-DWI brain microstructure is unknown. To address this question, DTI and MC-DWI studies of murine brains depleted of microglia were performed, revealing significant alterations in axonal integrity and fiber tractography in DTI and in commonly used MC-DWI models. With accumulating evidence of the role of microglia in neuropsychiatric illness, our findings uncover the unexpected contribution of microglia to measures of axonal integrity and structural connectivity and provide unanticipated insights into the potential influence of microglia in diffusion imaging studies of neuropsychiatric disease.

Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates

Purpose

Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics.

Methods

Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32⁺¹ weeks (24⁺²–36⁺⁴) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35⁺² weeks (25⁺³–43⁺¹). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development.

Results

PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.).

Conclusion

We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone.

Supplementary Information

The online version of this article (10.1007/s00234-020-02584-9) contains supplementary material, which is available to authorized users.

Challenges for biophysical modeling of microstructure

The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years. In this review, we dwell on the various challenges along the journey of bringing a biophysical model from initial design to clinical implementation, identifying both hurdles that have been already overcome and outstanding issues. First, we describe the critical initial task of selecting which features of tissue microstructure can be estimated using a model and which acquisition protocol needs to be implemented to make the estimation possible. The model performance should necessarily be tested in realistic numerical simulations and in experimental data - adapting the fitting strategy accordingly, and parameter estimates should be validated against complementary techniques, when/if available. Secondly, the model performance and validity should be explored in pathological conditions, and, if appropriate, dedicated models for pathology should be developed. We build on examples from tumors, ischemia and demyelinating diseases. We then discuss the challenges associated with clinical translation and added value. Finally, we single out four major unresolved challenges that are related to: the availability of a microstructural ground truth, the validation of model parameters which cannot be accessed with complementary techniques, the development of a generalized standard model for any brain region and pathology, and the seamless communication between different parties involved in the development and application of biophysical models of diffusion.

SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI

This work introduces a compartment-based model for apparent cell body (namely soma) and neurite density imaging (SANDI) using non-invasive diffusion-weighted MRI (DW-MRI). The existing conjecture in brain microstructure imaging through DW-MRI presents water diffusion in white (WM) and gray (GM) matter as restricted diffusion in neurites, modelled by infinite cylinders of null radius embedded in the hindered extra-neurite water. The extra-neurite pool in WM corresponds to water in the extra-axonal space, but in GM it combines water in the extra-cellular space with water in soma. While several studies showed that this microstructure model successfully describe DW-MRI data in WM and GM at b ​≤ ​3,000 ​s/mm² (or 3 ​ms/μm²), it has been also shown to fail in GM at high b values (b≫3,000 ​s/mm² or 3 ​ms/μm²). Here we hypothesise that the unmodelled soma compartment (i.e. cell body of any brain cell type: from neuroglia to neurons) may be responsible for this failure and propose SANDI as a new model of brain microstructure where soma of any brain cell type is explicitly included. We assess the effects of size and density of soma on the direction-averaged DW-MRI signal at high b values and the regime of validity of the model using numerical simulations and comparison with experimental data from mouse (b_max ​= ​40,000 ​s/mm², or 40 ​ms/μm²) and human (b_max ​= ​10,000 ​s/mm², or 10 ​ms/μm²) brain. We show that SANDI defines new contrasts representing complementary information on the brain cyto- and myelo-architecture. Indeed, we show maps from 25 healthy human subjects of MR soma and neurite signal fractions, that remarkably mirror contrasts of histological images of brain cyto- and myelo-architecture. Although still under validation, SANDI might provide new insight into tissue architecture by introducing a new set of biomarkers of potential great value for biomedical applications and pure neuroscience.

The Relationship Between Axon Density, Myelination, and Fractional Anisotropy in the Human Corpus Callosum

The corpus callosum serves the functional integration and interaction between the two hemispheres. Many studies investigate callosal microstructure via diffusion tensor imaging (DTI) fractional anisotropy (FA) in geometrically parcellated segments. However, FA is influenced by several different microstructural properties such as myelination and axon density, hindering a neurobiological interpretation. This study explores the relationship between FA and more specific measures of microstructure within the corpus callosum in a sample of 271 healthy participants. DTI tractography was used to assess 11 callosal segments and gain estimates of FA. We quantified axon density and myelination via neurite orientation dispersion and density imaging (NODDI) to assess intra-neurite volume fraction and a multiecho gradient spin-echo sequence estimating myelin water fraction. The results indicate three common factors in the distribution of FA, myelin content and axon density, indicating potentially shared rules of topographical distribution. Moreover, the relationship between measures varied across the corpus callosum, suggesting that FA should not be interpreted uniformly. More specific magnetic resonance imaging-based quantification techniques, such as NODDI and multiecho myelin water imaging, may thus play a key role in future studies of clinical trials and individual differences.

Diffusion Kurtosis Imaging maps neural damage in the EAE model of multiple sclerosis

Diffusion kurtosis imaging (DKI) is an imaging modality that yields novel disease biomarkers and in combination with nervous tissue modeling, provides access to microstructural parameters. Recently, DKI and subsequent estimation of microstructural model parameters has been used for assessment of tissue changes in neurodegenerative diseases and associated animal models. In this study, mouse spinal cords from the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS) were investigated for the first time using DKI in combination with biophysical modeling to study the relationship between microstructural metrics and degree of animal dysfunction. Thirteen spinal cords were extracted from animals with varied grades of disability and scanned in a high-field MRI scanner along with five control specimen. Diffusion weighted data were acquired together with high resolution T₂* images. Diffusion data were fit to estimate diffusion and kurtosis tensors and white matter modeling parameters, which were all used for subsequent statistical analysis using a linear mixed effects model. T₂* images were used to delineate focal demyelination/inflammation. Our results reveal a strong relationship between disability and measured microstructural parameters in normal appearing white matter and gray matter. Relationships between disability and mean of the kurtosis tensor, radial kurtosis, radial diffusivity were similar to what has been found in other hypomyelinating MS models, and in patients. However, the changes in biophysical modeling parameters and in particular in extra-axonal axial diffusivity were clearly different from previous studies employing other animal models of MS. In conclusion, our data suggest that DKI and microstructural modeling can provide a unique contrast capable of detecting EAE-specific changes correlating with clinical disability.

Relating diffusion tensor imaging measurements to microstructural quantities in the cerebral cortex in multiple sclerosis

To investigate whether the observed anisotropic diffusion in cerebral cortex may reflect its columnar cytoarchitecture and myeloarchitecture, as a potential biomarker for disease-related changes, we compared postmortem diffusion magnetic resonance imaging scans of nine multiple sclerosis brains with histology measures from the same regions. Histology measurements assessed the cortical minicolumnar structure based on cell bodies and associated axon bundles in dorsolateral prefrontal cortex (Area 9), Heschl's gyrus (Area 41), and primary visual cortex (V1). Diffusivity measures included mean diffusivity, fractional anisotropy of the cortex, and three specific measures that may relate to the radial minicolumn structure: the angle of the principal diffusion direction in the cortex, the component that was perpendicular to the radial direction, and the component that was parallel to the radial direction. The cellular minicolumn microcircuit features were correlated with diffusion angle in Areas 9 and 41, and the axon bundle features were correlated with angle in Area 9 and to the parallel component in V1 cortex. This may reflect the effect of minicolumn microcircuit organisation on diffusion in the cortex, due to the number of coherently arranged membranes and myelinated structures. Several of the cortical diffusion measures showed group differences between MS brains and control brains. Differences between brain regions were also found in histology and diffusivity measurements consistent with established regional variation in cytoarchitecture and myeloarchitecture. Therefore, these novel measures may provide a surrogate of cortical organisation as a potential biomarker, which is particularly relevant for detecting regional changes in neurological disorders.

Histologically derived fiber response functions for diffusion MRI vary across white matter fibers-An ex vivo validation study in the squirrel monkey brain

Understanding the relationship between the diffusion-weighted MRI signal and the arrangement of white matter fibers is fundamental for accurate voxel-wise reconstruction of the fiber orientation distribution (FOD) and subsequent fiber tractography. Spherical deconvolution reconstruction techniques model the diffusion signal as the convolution of the FOD with a response function that represents the signal profile of a single fiber orientation. Thus, given the signal and a fiber response function, the FOD can be estimated in every imaging voxel by deconvolution. However, the selection of the appropriate response function remains relatively under-studied, and requires further validation. In this work, using 3D histologically defined FODs and the corresponding diffusion signal from three ex vivo squirrel monkey brains, we derive the ground truth response functions. We find that the histologically derived response functions differ from those conventionally used. Next, we find that response functions statistically vary across brain regions, which suggests that the practice of using the same kernel throughout the brain is not optimal. We show that different kernels lead to different FOD reconstructions, which in turn can lead to different tractography results depending on algorithmic parameters, with large variations in the accuracy of resulting reconstructions. Together, these results suggest there is room for improvement in estimating and understanding the relationship between the diffusion signal and the underlying FOD.

In vivo high-resolution diffusion tensor imaging of the developing neonatal rat cortex and its relationship to glial and dendritic maturation

Diffusion tensor imaging (DTI) is increasingly utilized as a sensitive tool for studying brain maturation and injuries during the neonatal period. In this study, we acquired high resolution in vivo DTI data from neonatal rat brains from postnatal day 2 (P2) to P10 and correlated temporal changes in DTI derived markers with microstructural organization of glia, axons, and dendrites during this critical period of brain development. Group average images showed dramatic temporal changes in brain morphology, fractional anisotropy (FA) and mean diffusivity (MD). Most cortical regions showed a monotonous decline in FA and an initial increase in MD from P2 to P8 that declined slightly by P10. Qualitative histology revealed rapid maturation of the glial and dendritic networks in the developing cortex. In the cingulate and motor cortex, the decreases in FA over time significantly correlated with structural anisotropy values computed from histological sections stained with glial and dendritic markers. However, in the sensory and visual cortex, other factors probably contributed to the observed decreases in FA. We did not observe any significant correlations between FA and structural anisotropy computed from the axonal histological marker.