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Diffusion tensor imaging has the potential to be used as a neuroimaging marker of natural ageing and assist in elucidating trajectories of cerebral maturation and ageing. In this study, we applied a multivariate technique relevance vector regression (RVR) to predict individual subject's age using whole brain fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) from a cohort of 188 subjects aged 4–85years. High prediction accuracy as derived from Pearson correlation coefficient of actual versus predicted age (FA — r=0.870 p<0.0001; MD — r=0.896 p<0.0001; AD — r=0.895 p<0.0001; RD — r=0.899 p<0.0001) was achieved. Cerebral white-matter regions that contributed to these predictions include; corpus callosum, cingulum bundles, posterior longitudinal fasciculus and the cerebral peduncle. A post-hoc analysis of these regions showed that FA follows a nonlinear rational-quadratic trajectory across the lifespan peaking at approximately 21.8years. The MD, RD and AD volumes were particularly useful for making predictions using grey matter cerebral regions. These results suggest that diffusion tensor imaging measurements can reliably predict individual subject's age and demonstrate that FA cerebral maturation and ageing patterns follow a non-linear trajectory with a noteworthy peaking age. These data will contribute to the understanding of neurobiology of cerebral maturation and ageing. Most notably, from a neuropsychiatric perspective our results may allow differentiation of cerebral changes that may occur due to natural maturation and ageing, and those due to developmental or neuropsychiatric disorders. •Machine-learning is used to predict age using whole-brain diffusion tensor images.•A cross-validation approach is used to separate training and testing datasets.•White matter follows a rational-quadratic trajectory peaking at 21.8years.•Diffusivity in grey-matter tissue increases with maturation and ageing.

Cortical gyrification of the brain represents the folding characteristic of the cerebral cortex. How the brain cortical gyrification changes from childhood to old age in healthy human subjects is still unclear. Additionally, studies have shown regional gyrification alterations in patients with major psychiatric disorders, such as major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ). However, whether the lifespan trajectory of gyrification over the brain is altered in patients diagnosed with major psychiatric disorders is still unknown. In this study, we investigated the trajectories of gyrification in three independent cohorts based on structural brain images of 881 subjects from age 4 to 83. We discovered that the trajectory of gyrification during normal development and aging was not linear and could be modeled with a logarithmic function. We also found that the gyrification trajectories of patients with MDD, BD and SCZ were deviated from the healthy one during adulthood, indicating altered aging in the brain of these patients.

Chronic cocaine and alcohol use impart significant stress on biological and cognitive systems, resulting in changes consistent with an allostatic load model of neurocognitive impairment. The present study measured potential markers of allostatic load in individuals with comorbid cocaine/alcohol use disorders (CUD/AUD) and control subjects. Measures of brain white matter (WM), telomere length, and impulsivity/attentional bias were obtained. WM (CUD/AUD only) was indexed by diffusion tensor imaging metrics, including radial diffusivity (RD) and fractional anisotropy (FA). Telomere length was indexed by the telomere to single copy gene (T/S) ratio. Impulsivity and attentional bias to drug cues were measured via eye-tracking, and were also modeled using the Hierarchical Diffusion Drift Model (HDDM). Average whole-brain RD and FA were associated with years of cocaine use (R2 = 0.56 and 0.51, both p < .005) but not years of alcohol use. CUD/AUD subjects showed more anti-saccade errors (p < .01), greater attentional bias scores (p < .001), and higher HDDM drift rates on cocaine-cue trials (Bayesian probability CUD/AUD > control = p > 0.99). Telomere length was shorter in CUD/AUD, but the difference was not statistically significant. Within the CUD/AUD group, exploratory regression using an elastic-net model determined that more years of cocaine use, older age, larger HDDM drift rate differences and shorter telomere length were all predictive of WM as measured by RD (model R2 = 0.79). Collectively, the results provide modest support linking CUD/AUD to putative markers of allostatic load.

In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lack of automated assessment methods. Supervised deep learning (DL) methods are highly capable in this domain, but require large sets of labeled data. To overcome this challenge, a DL-based network (DAWM-Net) was trained using semi-supervised learning on a limited set of labeled data for segmentation of DAWM, focal lesions, and normal-appearing brain tissues on multiparametric MRI. DAWM-Net segmentation performance was compared to a previous intensity thresholding-based method on an independent test set from expert consensus ( N  = 25). Segmentation overlap by Dice Similarity Coefficient (DSC) and Spearman correlation of DAWM volumes were assessed. DAWM-Net showed DSC > 0.93 for normal-appearing brain tissues and DSC > 0.81 for focal lesions. For DAWM-Net, the DAWM DSC was 0.49 ± 0.12 with a moderate volume correlation (ρ = 0.52, p < 0.01). The previous method showed lower DAWM DSC of 0.26 ± 0.08 and lacked a significant volume correlation (ρ = 0.23, p = 0.27). These results demonstrate the feasibility of DL-based DAWM auto-segmentation with semi-supervised learning. This tool may facilitate future investigation of the role of DAWM in MS.

Magnetic resonance imaging data were acquired at ∼24 h and ∼3 months post-injury on mild traumatic brain injury (mTBI; n = 75) and orthopedic injury (n = 60) cohorts. The mTBI subjects were randomly assigned to a treatment group with atorvastatin or a non-treatment mTBI group. The treatment group was further divided into drug and placebo subgroups. FreeSurfer software package was used to compute cortical thickness based on the three dimensional T1-weighted images at both time-points. Cross-sectional analysis was carried out to compare cortical thickness between the mTBI and control groups. Longitudinal unbiased templates were generated for all subjects and cortical thickness measurements were compared between baseline and follow-up scans in the mTBI group. At baseline, significant reduction in cortical thickness was observed in the left middle temporal and the right superior parietal regions in the mTBI group, relative to the control group (p = 0.01). At follow-up, significant cortical thinning was again observed in the left middle temporal cortex in the mTBI group. Further analysis revealed significant cortical thinning only in the non-treatment group relative to the control group. In the follow-up, small regions with significant but subtle cortical thinning and thickening were seen in the frontal, temporal, and parietal lobes in the left hemisphere in the non-treatment group only. Our results indicate that cortical thickness could serve as a useful measure in identifying subtle changes in mTBI patients.

Background and purpose The discovery of glymphatic function in the human brain has generated interest in waste clearance mechanisms in neurological disorders such as multiple sclerosis (MS). However, noninvasive in vivo functional assessment is currently lacking. This work studies the feasibility of a novel intravenous dynamic contrast MRI method to assess the dural lymphatics, a purported pathway contributing to glymphatic clearance. Methods This prospective study included 20 patients with MS (17 women; age = 46.4 [27, 65] years; disease duration = 13.6 [2.1, 38.0] years, expanded disability status score (EDSS) = 2.0 [0, 6.5]). Patients were scanned on a 3.0T MRI system using intravenous contrast‐enhanced fluid‐attenuated inversion recovery MRI. Signal in the dural lymphatic vessel along the superior sagittal sinus was measured to calculate peak enhancement, time to maximum enhancement, wash‐in and washout slopes, and the area under the time‐intensity curve (AUC). Correlation analysis was performed to examine the relationship between the lymphatic dynamic parameters and the demographic and clinical characteristics, including the lesion load and the brain parenchymal fraction (BPF). Results Contrast enhancement was detected in the dural lymphatics in most patients 2–3 min after contrast administration. BPF had a significant correlation with AUC (p < .03), peak enhancement (p < .01), and wash‐in slope (p = .01). Lymphatic dynamic parameters did not correlate with age, BMI, disease duration, EDSS, or lesion load. Moderate trends were observed for correlation between patient age and AUC (p = .062), BMI and peak enhancement (p = .059), and BMI and AUC (p = .093). Conclusion Intravenous dynamic contrast MRI of the dural lymphatics is feasible and may be useful in characterizing its hydrodynamics in neurological diseases. We study the feasibility of a novel intravenous, dynamic, contrast‐enhanced MRI method to assess the dural lymphatic vessels. Initial results in multiple sclerosis patients confirm feasibility, and show interesting associations between the lymphatic signal and patient characteristics. The proposed functional method could enable in vivo study of waste clearance mechanisms in neurological disorders.

Abstract BACKGROUND: Severe traumatic brain injury (TBI) in children is associated with substantial long-term morbidity and mortality. Currently, there are no successful neuroprotective/neuroreparative treatments for TBI. Numerous preclinical studies suggest that bone marrow-derived mononuclear cells (BMMNCs), their derivative cells (marrow stromal cells), or similar cells (umbilical cord blood cells) offer neuroprotection. OBJECTIVE: To determine whether autologous BMMNCs are a safe treatment for severe TBI in children. METHODS: Ten children aged 5 to 14 years with a postresuscitation Glasgow Coma Scale of 5 to 8 were treated with 6 × 106 autologous BMMNCs/kg body weight delivered intravenously within 48 hours after TBI. To determine the safety of the procedure, systemic and cerebral hemodynamics were monitored during bone marrow harvest; infusion-related toxicity was determined by pediatric logistic organ dysfunction (PELOD) scores, hepatic enzymes, Murray lung injury scores, and renal function. Conventional magnetic resonance imaging (cMRI) data were obtained at 1 and 6 months postinjury, as were neuropsychological and functional outcome measures. RESULTS: All patients survived. There were no episodes of harvest-related depression of systemic or cerebral hemodynamics. There was no detectable infusion-related toxicity as determined by PELOD score, hepatic enzymes, Murray lung injury scores, or renal function. cMRI imaging comparing gray matter, white matter, and CSF volumes showed no reduction from 1 to 6 months postinjury. Dichotomized Glasgow Outcome Score at 6 months showed 70% with good outcomes and 30% with moderate to severe disability. CONCLUSION: Bone marrow harvest and intravenous mononuclear cell infusion as treatment for severe TBI in children is logistically feasible and safe.

The mammillary bodies as part of the hypothalamic nuclei are in the central limbic circuitry of the human brain. The mammillary bodies are shown to be directly or indirectly connected to the amygdala, hippocampus, and thalami as the major gray matter structures of the human limbic system. Although it is not primarily considered as part of the human limbic system, the thalamus is shown to be involved in many limbic functions of the human brain. The major direct connection of the thalami with the hypothalamic nuclei is known to be through the mammillothalamic tract. Given the crucial role of the mammillothalamic tracts in memory functions, diffusion tensor imaging may be helpful in better visualizing the surgical anatomy of this pathway noninvasively. This study aimed to investigate the utility of high spatial resolution diffusion tensor tractography for mapping the trajectory of the mammillothalamic tract in the human brain. Fifteen healthy adults were studied after obtaining written informed consent. We used high spatial resolution diffusion tensor imaging data at 3.0 T. We delineated, for the first time, the detailed trajectory of the mammillothalamic tract of the human brain using deterministic diffusion tensor tractography.

Major psychiatric disorders are increasingly being conceptualized as ‘neurodevelopmental’, because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of neuroanatomical measurements may reliably identify individual subjects deviating from a normative neurodevelopmental trajectory. However, while recent studies have shown great promise in developing accurate brain maturation indices using neuroimaging data and multivariate machine learning techniques, this approach has not been validated using a large sample of longitudinal data from children and adolescents. T1-weighted scans from 303 healthy subjects aged 4.88 to 18.35years were acquired from the National Institute of Health (NIH) pediatric repository (http://www.pediatricmri.nih.gov). Out of the 303 subjects, 115 subjects were re-scanned after 2years. The least absolute shrinkage and selection operator algorithm (LASSO) was ‘trained’ to integrate neuroanatomical changes across chronological age and predict each individual's brain maturity. The resulting brain maturation index was developed using first-visit scans only, and was validated using second-visit scans. We report a high correlation between the first-visit chronological age and brain maturation index (r=0.82, mean absolute error or MAE=1.69years), and a high correlation between the second-visit chronological age and brain maturation index (r=0.83, MAE=1.71years). The brain maturation index captured neuroanatomical volume changes between the first and second visits with an MAE of 0.27years. The brain maturation index developed in this study accurately predicted individual subjects' brain maturation longitudinally. Due to its strong clinical potentials in identifying individuals with an abnormal brain maturation trajectory, the brain maturation index may allow timely clinical interventions for individuals at risk for psychiatric disorders. •The brain maturation index can predict individual brain maturation longitudinally.•Prediction accuracy is similar on cross-sectional and longitudinal brain scans.•Brain regions with high predicting powers capture the longitudinal brain changes.

Cerebellar white matter (WM) connections to the central nervous system are classified functionally into the Spinocerebellar (SC), vestibulocerebellar (VC), and cerebrocerebellar subdivisions. The SC pathways project from spinal cord to cerebellum, whereas the VC pathways project from vestibular organs of the inner ear. Cerebrocerebellar connections are composed of feed forward and feedback connections between cerebrum and cerebellum including the cortico-ponto-cerebellar (CPC) pathways being of cortical origin and the dentate-rubro-thalamo-cortical (DRTC) pathway being of cerebellar origin. In this study we systematically quantified the whole cerebellar system connections using diffusion tensor magnetic resonance imaging (DT-MRI). Ten right-handed healthy subjects (7 males and 3 females, age range 20-51 years) were studied. DT-MRI data were acquired with a voxel size = 2 mm × 2 mm × 2 mm at a 3.0 Tesla clinical MRI scanner. The DT-MRI data were prepared and analyzed using anatomically-guided deterministic tractography methods to reconstruct the SC, DRTC, fronto-ponto-cerebellar (FPC), parieto-ponto-cerebellar (PPC), temporo-ponto-cerebellar (TPC) and occipito-ponto-cerebellar (OPC). The DTI-attributes or the cerebellar tracts along with their cortical representation (Brodmann areas) were presented in standard Montréal Neurological Institute space. All cerebellar tract volumes were quantified and correlated with volumes of cerebral cortical, subcortical gray matter (GM), cerebral WM and cerebellar GM, and cerebellar WM. On our healthy cohort, the ratio of total cerebellar GM-to-WM was ~3.29 ± 0.24, whereas the ratio of cerebral GM-to-WM was approximately 1.10 ± 0.11. The sum of all cerebellar tract volumes is ~25.8 ± 7.3 mL, or a percentage of 1.6 ± 0.45 of the total intracranial volume (ICV).