The developing hippocampus: Microstructural evolution through childhood and adolescence.

The hippocampus is a structure in the medial temporal lobe which serves multiple cognitive functions. While important, the development of the hippocampus in the formative period of childhood and adolescence has not been extensively investigated, with most contemporary research focusing on macrostructural measures of volume. Thus, there has been little research on the development of the micron-scale structures (i.e., microstructure) of the hippocampus, which engender its cognitive functions. The current study examined age-related changes of hippocampal microstructure using diffusion MRI data acquired with an ultra-strong gradient (300 mT/m) MRI scanner in a sample of children and adolescents (N=88; 8-19 years). Surface-based hippocampal modelling was combined with established microstructural approaches, such as Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion Density Imaging (NODDI), and a more advanced gray matter diffusion model Soma And Neurite Density Imaging (SANDI). No significant changes in macrostructural measures (volume, gyrification, and thickness) were found between 8-19 years, while significant changes in microstructure measures related to neurites (from NODDI and SANDI), soma (from SANDI), and mean diffusivity (from DTI) were found. In particular, there was a significant increase across age in neurite MR signal fraction and a significant decrease in extracellular MR signal fraction and mean diffusivity across the hippocampal subfields and long-axis. A significant negative correlation between age and MR apparent soma radius was found in the subiculum and CA1 throughout the anterior and body of the hippocampus. Further surface-based analyses uncovered variability in age-related microstructural changes between the subfields and long-axis, which may reflect ostensible developmental differences along these two axes. Finally, correlation of hippocampal surfaces representing age-related changes of microstructure with maps derived from histology allowed for postulation of the potential underlying microstructure that diffusion changes across age may be capturing. Overall, distinct neurite and soma developmental profiles in the human hippocampus during late childhood and adolescence are reported for the first time.

MRI signatures of cortical microstructure in human development align with oligodendrocyte cell-type expression.

Neuroanatomical changes to the cortex during adolescence have been well documented using MRI, revealing ongoing cortical thinning and volume loss with age. However, the underlying cellular mechanisms remain elusive with conventional neuroimaging. Recent advances in MRI hardware and new biophysical models of tissue informed by diffusion MRI data hold promise for identifying the cellular changes driving these morphological observations. This study used ultra-strong gradient MRI to obtain high-resolution, in vivo estimates of cortical neurite and soma microstructure in sample of typically developing children and adolescents. Cortical neurite signal fraction, attributed to neuronal and glial processes, increased with age (mean R2 fneurite=.53, p<3.3e-11, 11.91% increase over age), while apparent soma radius decreased (mean R2 Rsoma=.48, p<4.4e-10, 1% decrease over age) across domain-specific networks. To complement these findings, developmental patterns of cortical gene expression in two independent post-mortem databases were analysed. This revealed increased expression of genes expressed in oligodendrocytes, and excitatory neurons, alongside a relative decrease in expression of genes expressed in astrocyte, microglia and endothelial cell-types. Age-related genes were significantly enriched in cortical oligodendrocytes, oligodendrocyte progenitors and Layer 5-6 neurons (pFDR<.001) and prominently expressed in adolescence and young adulthood. The spatial and temporal alignment of oligodendrocyte cell-type gene expression with neurite and soma microstructural changes suggest that ongoing cortical myelination processes contribute to adolescent cortical development. These findings highlight the role of intra-cortical myelination in cortical maturation during adolescence and into adulthood.

Diffusion MRI in prostate cancer with ultra-strong whole-body gradients.

Diffusion-weighted MRI (dMRI) is universally recommended for the detection and classification of prostate cancer (PCa), with PI-RADS recommendations to acquire b-values of ≥1.4 ms/µm2. However, clinical dMRI suffers from a low signal-to-noise ratio (SNR) as the consequence of prolonged echo times (TEs) attributable to the limited gradient power in the range of 40-80 mT/m. To overcome this, MRI systems with strong gradients have been designed but so far have mainly been applied in the brain. The aim of this work was to assess the feasibility, data quality, SNR and contrast-to-noise ratio (CNR) of measurements in PCa with a 300 mT/m whole-body system. A cohort of men without and with diagnosed PCa were imaged on a research-only 3T Connectom Siemens MRI system equipped with a gradient amplitude of 300 mT/m. dMRI at high b-values were acquired using high gradient amplitudes and compared with gradient capabilities mimicking clinical systems. Data artefacts typically amplified with stronger gradients were assessed and their correction evaluated. The SNR gains and lesion-to-healthy tissue CNR were statistically tested investigating the effect of protocol and b-value. The diagnostic quality of the images for different dMRI protocols was assessed by an experienced radiologist using a 5-point Likert scale and an adapted PI-QUAL scoring system. The strong gradients for prostate dMRI allowed a significant gain in SNR per unit time compared with clinical gradients. Furthermore, a 1.6-2.1-fold increase in CNR was observed. Despite the more pronounced artefacts typically associated with strong gradients, a satisfactory correction could be achieved. Smoother and less biased parameter maps were obtained with protocols at shorter TEs. The results of this study show that dMRI in PCa with a whole-body 300-mT/m scanner is feasible without a report of physiological effects, SNR and CNR can be improved compared with lower gradient strengths, and artefacts do not negate the benefits of strong gradients and can be ameliorated. This assessment provides the first essential step towards unveiling the full potential of cutting-edge scanners, now increasingly becoming available, to advance early detection and diagnostic precision.

Controlled Antenatal Thyroid Screening Study III: Effects of gestational thyroid status on adolescent brain morphology.

CONTEXT: Children born to mothers with gestational hypo- or hyperthyroidism may have increased risk of adverse neurodevelopmental outcomes. However, the effects of maternal thyroid status on offspring brain development are unclear. OBJECTIVE: To establish whether adolescent brain morphology is affected by suboptimal gestational thyroid function (SGTF). DESIGN AND SETTING: The Controlled Antenatal Thyroid Screening (CATS) study randomized mothers with SGTF to levothyroxine or no supplementation from ∼12 weeks' gestation. At age 9, children born to mothers who were over-treated with levothyroxine had a higher risk of conduct and hyperactivity traits. For the current CATS III study, children underwent neuroimaging studies, including T1-weighted structural magnetic resonance imaging (MRI). PARTICIPANTS: A total of 85 children aged 11-16 years had usable T1-weighted MRI data (exposed to untreated SGTF (n=21), normal GTF (n=24), or treated SGTF (optimally-treated (n=21), over-treated (n=20)). MAIN OUTCOME MEASURES: Primary outcome: to examine the association of SGTF and its treatment with global brain volumes. Secondary and exploratory outcomes: to investigate the association of maternal TSH and free T4 levels with global and subregional brain volumes. Results were adjusted for age, sex and pubertal scores. RESULTS: There were no significant differences in global brain volumetric measures between groups, including total gray matter volume (p=0.373). Weak positive correlations were found between maternal TSH, but not FT4, levels and several brain volumes, but these did not survive testing for multiple comparisons. CONCLUSIONS: We found no evidence that SGTF was associated with differences in adolescent brain morphology, and no impact of levothyroxine supplementation.

In vivo diffusion MRI of the human heart using a 300 mT/m gradient system.

PURPOSE: This work reports for the first time on the implementation and application of cardiac diffusion-weighted MRI on a Connectom MR scanner with a maximum gradient strength of 300 mT/m. It evaluates the benefits of the increased gradient performance for the investigation of the myocardial microstructure. METHODS: Cardiac diffusion-weighted imaging (DWI) experiments were performed on 10 healthy volunteers using a spin-echo sequence with up to second- and third-order motion compensation ( M 2 $$ {M}_2 $$ and M 3 $$ {M}_3 $$ ) and b = 100 , 450 $$ b=100,450 $$ , and 1000 s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ (twice the b max $$ {b}_{\mathrm{max}} $$ commonly used on clinical scanners). Mean diffusivity (MD), fractional anisotropy (FA), helix angle (HA), and secondary eigenvector angle (E2A) were calculated for b = [100, 450] s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ and b = [100, 1000] s / m m 2 $$ \mathrm{s}/\mathrm{m}{\mathrm{m}}^2 $$ for both M 2 $$ {M}_2 $$ and M 3 $$ {M}_3 $$ . RESULTS: The MD values with M 3 $$ {M}_3 $$ are slightly higher than with M 2 $$ {M}_2 $$ with Δ MD = 0 . 05 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 5 ) $$ \Delta \mathrm{MD}=0.05\pm 0.05\kern0.3em \left[\times 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-5\right) $$ for b max = 450 s / mm 2 $$ {b}_{\mathrm{max}}=450\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ and Δ MD = 0 . 03 ± 0 . 03 [ × 1 0 - 3 mm 2 / s ] ( p = 4 e - 4 ) $$ \Delta \mathrm{MD}=0.03\pm 0.03\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=4e-4\right) $$ for b max = 1000 s / mm 2 $$ {b}_{\mathrm{max}}=1000\kern0.3em \mathrm{s}/{\mathrm{mm}}^2 $$ . A reduction in MD is observed by increasing the b max $$ {b}_{\mathrm{max}} $$ from 450 to 1000 s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ ( Δ MD = 0 . 06 ± 0 . 04 [ × 1 0 - 3 mm 2 / s ] ( p = 1 . 6 e - 9 ) $$ \Delta \mathrm{MD}=0.06\pm 0.04\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1.6e-9\right) $$ for M 2 $$ {M}_2 $$ and Δ MD = 0 . 08 ± 0 . 05 [ × 1 0 - 3 mm 2 / s ] ( p = 1 e - 9 ) $$ \Delta \mathrm{MD}=0.08\pm 0.05\kern0.3em \left[\times \kern0.3em 1{0}^{-3}\kern0.3em {\mathrm{mm}}^2/\mathrm{s}\right]\kern0.3em \left(p=1e-9\right) $$ for M 3 $$ {M}_3 $$ ). The difference between FA, E2A, and HA was not significant in different schemes ( p > 0 . 05 $$ p>0.05 $$ ). CONCLUSION: This work demonstrates cardiac DWI in vivo with higher b-value and higher order of motion compensated diffusion gradient waveforms than is commonly used. Increasing the motion compensation order from M 2 $$ {M}_2 $$ to M 3 $$ {M}_3 $$ and the maximum b-value from 450 to 1000 s / mm 2 $$ \mathrm{s}/{\mathrm{mm}}^2 $$ affected the MD values but FA and the angular metrics (HA and E2A) remained unchanged. Our work paves the way for cardiac DWI on the next-generation MR scanners with high-performance gradient systems.

Longitudinal effects of prenatal alcohol exposure on visual neurodevelopment over infancy.

Prenatal alcohol exposure (PAE) affects neurodevelopment in over 59 million individuals globally. Prior studies using dichotomous categorization of alcohol use and comorbid substance exposures provide limited knowledge of how prenatal alcohol specifically impacts early human neurodevelopment. In this longitudinal cohort study from Cape Town, South Africa, PAE is measured continuously-characterizing timing, dose, and drinking patterns (i.e., binge drinking). High-density electroencephalography (EEG) during a visual-evoked potential (VEP) task was collected from infants aged 8 to 52 weeks with prenatal exposure exclusively to alcohol and matched on sociodemographic factors to infants with no substance exposure in utero. First trimester alcohol exposure related to altered timing of the P1 VEP component over the first 6 months postnatally, and first trimester binge drinking exposure altered timing of the P1 VEP components such that increased exposure was associated with longer VEP latencies while increasing age was related to shorter VEP latencies (n = 108). These results suggest alcohol exposure in the first trimester may alter visual neurodevelopmental timing in early infancy. Exploratory individual-difference analysis across infants with and without PAE tested the relation between VEP latencies and myelination for a subsample of infants with usable magnetic resonance imaging (MRI) T1w and T2w scans collected at the same time point as EEG (n = 47). Decreased MRI T1w/T2w ratios (an indicator of myelin) in the primary visual cortex (n = 47) were linked to longer P1 VEP latencies. Results from these two sets of analyses suggest that prenatal alcohol and postnatal myelination may both separately impact VEP latency over infancy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning.

Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2∗-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cramér-Rao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI.

PURPOSE: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. THEORY AND METHODS: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from scanning electron microscope images. RESULTS: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, although some discrepancies were observed. The spherical mean power-law method overestimated fiber radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fiber radii, but faced limitations in accurately estimating the radius in one particular phantom, possibly because of material-specific relaxation changes. CONCLUSION: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibers. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients, but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fiber radius estimation, highlights the advantages and limitations of both methods, and provides datasets for reproducible research.

Macro- and micro-structural insights into primary dystonia: a UK Biobank study.

BACKGROUND: Dystonia is a hyperkinetic movement disorder with key motor network dysfunction implicated in pathophysiology. The UK Biobank encompasses > 500,000 participants, of whom 42,565 underwent brain MRI scanning. This study applied an optimized pre-processing pipeline, aimed at better accounting for artifact and improving data reliability, to assess for grey and white matter structural MRI changes between individuals diagnosed with primary dystonia and an unaffected control cohort. METHODS: Individuals with dystonia (n = 76) were identified from the UK Biobank using published algorithms, alongside an age- and sex-matched unaffected control cohort (n = 311). Grey matter morphometric and diffusion measures were assessed, together with white matter diffusion tensor and diffusion kurtosis metrics using tractography and tractometry. Post-hoc Neurite Orientation and Density Distribution Imaging (NODDI) was also undertaken for tracts in which significant differences were observed. RESULTS: Grey matter tremor-specific striatal differences were observed, with higher radial kurtosis. Tractography identified no white matter differences, however segmental tractometry identified localised differences, particularly in the superior cerebellar peduncles and anterior thalamic radiations, including higher fractional anisotropy and lower orientation distribution index in dystonia, compared to controls. Additional tremor-specific changes included lower neurite density index in the anterior thalamic radiations. CONCLUSIONS: Analysis of imaging data from one of the largest dystonia cohorts to date demonstrates microstructural differences in cerebellar and thalamic white matter connections, with architectural differences such as less orientation dispersion potentially being a component of the morphological structural changes implicated in dystonia. Distinct tremor-related imaging features are also implicated in both grey and white matter.

Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification.

PURPOSE: To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating. METHODS: The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments. RESULTS: The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved. CONCLUSION: The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency.

Maximizing SNR per unit time in diffusion MRI with multiband T-Hex spirals.

PURPOSE: The characterization of tissue microstructure using diffusion MRI (dMRI) signals is rapidly evolving, with increasing sophistication of signal representations and microstructure models. However, this progress often requires signals to be acquired with very high b-values (e.g., b > 30 ms/µm2 ), along many directions, and using multiple b-values, leading to long scan times and extremely low SNR in dMRI images. The purpose of this work is to boost the SNR efficiency of dMRI by combining three particularly efficient spatial encoding techniques and utilizing a high-performance gradient system (Gmax ≤ 300 mT/m) for efficient diffusion encoding. METHODS: Spiral readouts, multiband imaging, and sampling on tilted hexagonal grids (T-Hex) are combined and implemented on a 3T MRI system with ultra-strong gradients. Image reconstruction is performed through an iterative cg-SENSE algorithm incorporating static off-resonance distributions and field dynamics as measured with an NMR field camera. Additionally, T-Hex multiband is combined with a more conventional EPI-readout and compared with state-of-the-art blipped-CAIPIRINHA sampling. The advantage of the proposed approach is furthermore investigated for clinically available gradient performance and diffusion kurtosis imaging. RESULTS: High fidelity in vivo images with b-values up to 40 ms/µm2 are obtained. The approach provides superior SNR efficiency over other state-of-the-art multiband diffusion readout schemes. CONCLUSION: The demonstrated gains hold promise for the widespread dissemination of advanced microstructural scans, especially in clinical populations.

In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods.

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients.

Introduction: Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods: In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results: Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion: In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

The impact of cumulative obstetric complications and childhood trauma on brain volume in young people with psychotic experiences.

Psychotic experiences (PEs) occur in 5-10% of the general population and are associated with exposure to childhood trauma and obstetric complications. However, the neurobiological mechanisms underlying these associations are unclear. Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we studied 138 young people aged 20 with PEs (n = 49 suspected, n = 53 definite, n = 36 psychotic disorder) and 275 controls. Voxel-based morphometry assessed whether MRI measures of grey matter volume were associated with (i) PEs, (ii) cumulative childhood psychological trauma (weighted summary score of 6 trauma types), (iii) cumulative pre/peri-natal risk factors for psychosis (weighted summary score of 16 risk factors), and (iv) the interaction between PEs and cumulative trauma or pre/peri-natal risk. PEs were associated with smaller left posterior cingulate (pFWE < 0.001, Z = 4.19) and thalamus volumes (pFWE = 0.006, Z = 3.91). Cumulative pre/perinatal risk was associated with smaller left subgenual cingulate volume (pFWE < 0.001, Z = 4.54). A significant interaction between PEs and cumulative pre/perinatal risk found larger striatum (pFWE = 0.04, Z = 3.89) and smaller right insula volume extending into the supramarginal gyrus and superior temporal gyrus (pFWE = 0.002, Z = 4.79), specifically in those with definite PEs and psychotic disorder. Cumulative childhood trauma was associated with larger left dorsal striatum (pFWE = 0.002, Z = 3.65), right prefrontal cortex (pFWE < 0.001, Z = 4.63) and smaller left insula volume in all participants (pFWE = 0.03, Z = 3.60), and there was no interaction with PEs group. In summary, pre/peri-natal risk factors and childhood psychological trauma impact similar brain pathways, namely smaller insula and larger striatum volumes. The effect of pre/perinatal risk was greatest in those with more severe PEs, whereas effects of trauma were seen in all participants. In conclusion, environmental risk factors affect brain networks implicated in schizophrenia, which may increase an individual's propensity to develop later psychotic disorders.

Pathway-specific polygenic scores for Alzheimer's disease are associated with changes in brain structure in younger and older adults.

Genome-wide association studies have identified multiple Alzheimer's disease risk loci with small effect sizes. Polygenic risk scores, which aggregate these variants, are associated with grey matter structural changes. However, genome-wide scores do not allow mechanistic interpretations. The present study explored associations between disease pathway-specific scores and grey matter structure in younger and older adults. Data from two separate population cohorts were used as follows: the Avon Longitudinal Study of Parents and Children, mean age 19.8, and UK Biobank, mean age 64.4 (combined n = 18 689). Alzheimer's polygenic risk scores were computed using the largest genome-wide association study of clinically assessed Alzheimer's to date. Relationships between subcortical volumes and cortical thickness, pathway-specific scores and genome-wide scores were examined. Increased pathway-specific scores were associated with reduced cortical thickness in both the younger and older cohorts. For example, the reverse cholesterol transport pathway score showed evidence of association with lower left middle temporal cortex thickness in the younger Avon participants (P = 0.034; beta = -0.013, CI -0.025, -0.001) and in the older UK Biobank participants (P = 0.019; beta = -0.003, CI -0.005, -4.56 × 10-4). Pathway scores were associated with smaller subcortical volumes, such as smaller hippocampal volume, in UK Biobank older adults. There was also evidence of positive association between subcortical volumes in Avon younger adults. For example, the tau protein-binding pathway score was negatively associated with left hippocampal volume in UK Biobank (P = 8.35 × 10-05; beta = -11.392, CI -17.066, -5.718) and positively associated with hippocampal volume in the Avon study (P = 0.040; beta = 51.952, CI 2.445, 101.460). The immune response score had a distinct pattern of association, being only associated with reduced thickness in the right posterior cingulate in older and younger adults (P = 0.011; beta = -0.003, CI -0.005, -0.001 in UK Biobank; P = 0.034; beta = -0.016, CI -0.031, -0.001 in the Avon study). The immune response score was associated with smaller subcortical volumes in the older adults, but not younger adults. The disease pathway scores showed greater evidence of association with imaging phenotypes than the genome-wide score. This suggests that pathway-specific polygenic methods may allow progress towards a mechanistic understanding of structural changes linked to polygenic risk in pre-clinical Alzheimer's disease. Pathway-specific profiling could further define pathophysiology in individuals, moving towards precision medicine in Alzheimer's disease.

Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology.

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm2) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement.

In vivo evidence of microstructural hypo-connectivity of brain white matter in 22q11.2 deletion syndrome.

22q11.2 deletion syndrome, or 22q11.2DS, is a genetic syndrome associated with high rates of schizophrenia and autism spectrum disorders, in addition to widespread structural and functional abnormalities throughout the brain. Experimental animal models have identified neuronal connectivity deficits, e.g., decreased axonal length and complexity of axonal branching, as a primary mechanism underlying atypical brain development in 22q11.2DS. However, it is still unclear whether deficits in axonal morphology can also be observed in people with 22q11.2DS. Here, we provide an unparalleled in vivo characterization of white matter microstructure in participants with 22q11.2DS (12-15 years) and those undergoing typical development (8-18 years) using a customized magnetic resonance imaging scanner which is sensitive to axonal morphology. A rich array of diffusion MRI metrics are extracted to present microstructural profiles of typical and atypical white matter development, and provide new evidence of connectivity differences in individuals with 22q11.2DS. A recent, large-scale consortium study of 22q11.2DS identified higher diffusion anisotropy and reduced overall diffusion mobility of water as hallmark microstructural alterations of white matter in individuals across a wide age range (6-52 years). We observed similar findings across the white matter tracts included in this study, in addition to identifying deficits in axonal morphology. This, in combination with reduced tract volume measurements, supports the hypothesis that abnormal microstructural connectivity in 22q11.2DS may be mediated by densely packed axons with disproportionately small diameters. Our findings provide insight into the in vivo white matter phenotype of 22q11.2DS, and promote the continued investigation of shared features in neurodevelopmental and psychiatric disorders.

Increased structural connectivity in high schizotypy.

The link between brain structural connectivity and schizotypy was explored in two healthy participant cohorts, collected at two different neuroimaging centres, comprising 140 and 115 participants, respectively. The participants completed the Schizotypal Personality Questionnaire (SPQ), through which their schizotypy scores were calculated. Diffusion-MRI data were used to perform tractography and to generate the structural brain networks of the participants. The edges of the networks were weighted with the inverse radial diffusivity. Graph theoretical metrics of the default mode, sensorimotor, visual, and auditory subnetworks were derived and their correlation coefficients with the schizotypy scores were calculated. To the best of our knowledge, this is the first time that graph theoretical measures of structural brain networks are investigated in relation to schizotypy. A positive correlation was found between the schizotypy score and the mean node degree and mean clustering coefficient of the sensorimotor and the default mode subnetworks. The nodes driving these correlations were the right postcentral gyrus, the left paracentral lobule, the right superior frontal gyrus, the left parahippocampal gyrus, and the bilateral precuneus, that is, nodes that exhibit compromised functional connectivity in schizophrenia. Implications for schizophrenia and schizotypy are discussed.

Ultra-strong diffusion-weighted MRI reveals cerebellar grey matter abnormalities in movement disorders.

Structural brain MRI has proven invaluable in understanding movement disorder pathophysiology. However, most work has focused on grey/white matter volumetric (macrostructural) and white matter microstructural effects, limiting understanding of frequently implicated grey matter microstructural differences. Using ultra-strong spherical tensor encoding diffusion-weighted MRI, a persistent MRI signal was seen in healthy cerebellar grey matter even at high diffusion-weightings (b ​≥ 10,000 s/mm2). Quantifying the proportion of this signal (denoted fs), previously ascertained to originate from inside small spherical spaces, provides a potential proxy for cell body density. In this work, this approach was applied for the first time to a clinical cohort, including patients with diagnosed movement disorders in which the cerebellum has been implicated in symptom pathophysiology. Five control participants (control group 1, median age 24.5 years (20-39 years), imaged at two timepoints, demonstrated consistency in measurement of all three measures - MD (Mean Diffusivity) fs, and Ds (dot diffusivity)- with intraclass correlation coefficients (ICC) of 0.98, 0.86 and 0.76, respectively. Comparison with an older control group (control group 2 (n = 5), median age 51 years (43-58 years)) found no significant differences, neither with morphometric nor microstructural (MD (p = 0.36), fs (p = 0.17) and Ds (p = 0.22)) measures. The movement disorder cohort (Parkinson's Disease, n = 5, dystonia, n = 5. Spinocerebellar Ataxia 6, n = 5) when compared to the age-matched control cohort (Control Group 2) identified significantly lower MD (p < 0.0001 and p < 0.0001) and higher fs values (p < 0.0001 and p < 0.0001) in SCA6 and dystonia cohorts respectively. Lobar division of the cerebellum found these same differences in the superior and inferior posterior lobes, while no differences were seen in either the anterior lobes or with Ds measurements. In contrast to more conventional measures from diffusion tensor imaging, this framework provides enhanced specificity to differences in restricted spherical spaces in grey matter (including small cells) by eliminating signals from cerebrospinal fluid and axons. In the context of human and animal histopathology studies, these findings potentially implicate the cerebellar Purkinje and granule cells as contributors to the observed signal differences, with both cell types having been implicated in several neurological disorders through both postmortem and animal model studies. This novel microstructural imaging approach shows promise for improving movement disorder diagnosis, prognosis, and treatment.