Diffusion tensor imaging for understanding brain development in early life

Prediction of adolescent idiopathic scoliosis with machine learning algorithms using brain volumetric measurements

Background

It is known that neuroanatomical and neurofunctional changes observed in the brain, brainstem and cerebellum play a role in the etiology of adolescent idiopathic scoliosis (AIS). This study aimed to investigate whether volumetric measurements of brain regions can be used as predictive indicators for AIS through machine learning techniques.

Methods

Patients with a severe degree of curvature in AIS (n = 32) and healthy individuals (n = 31) were enrolled in the study. Volumetric data from 169 brain regions, acquired from magnetic resonance imaging (MRI) of these individuals, were utilized as predictive factors. A comprehensive analysis was conducted using the twelve most prevalent machine learning algorithms, encompassing thorough parameter adjustments and cross-validation processes. Furthermore, the findings related to variable significance are presented.

Results

Among all the algorithms evaluated, the random forest algorithm produced the most favorable results in terms of various classification metrics, including accuracy (0.9083), AUC (0.993), f1-score (0.970), and Brier score (0.1256). Additionally, the most critical variables were identified as the volumetric measurements of the right corticospinal tract, right corpus callosum body, right corpus callosum splenium, right cerebellum, and right pons, respectively.

Conclusion

The outcomes of this study indicate that volumetric measurements of specific brain regions can serve as reliable indicators of AIS. In conclusion, the developed model and the significant variables discovered hold promise for predicting scoliosis development, particularly in high-risk individuals.

Anatomically constrained tractography of the fetal brain

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

Combined diffusion tensor imaging and quantitative susceptibility mapping to characterize normal-appearing white matter in self-limited epilepsy with centrotemporal spikes

PURPOSE

In brain development, Myelination is the characteristic feature of white matter maturation, which plays an important role in efficient information transmitting. The white matter abnormality has been reported to be associated with self-limited epilepsy with centrotemporal spikes (SeLECTS). This study aimed to detect the altered white matter region in the SeLECTS patients by the combination of diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM) technique.

METHODS

27 children with SeLECTS and 23 age- and gender-matched healthy children were enrolled. All participants were scanned with 3.0-T MRI to acquire the structure, diffusion and susceptibility-weighted data. The susceptibility and diffusion weighted data were processed to obtain quantitative susceptibility map and fraction anisotropy (FA) map. Then voxel-wise tract-based spatial statistics (TBSS) were used to analyze quantitative susceptibility and FA data.

RESULTS

Both DTI and QSM revealed extensive white matter alterations in the frontal, parietal, and temporal lobes in SeLECTS patients. The overlapped region of DTI and QSM analyses was located in the fiber tracts of the corona radiata. The FA values in this overlapped region were negatively correlated with the magnetic susceptibility values.

CONCLUSION

Our results suggest that TBSS-based QSM can be employed as a novel approach for characterizing alterations in white matter in SeLECTS. And the combination of QSM and DTI can provide a more comprehensive evaluation of white matter integrity by utilizing different biophysical features.

The effect of spinal correction surgery on the tractography data of the pain pathway in scoliosis patients: a preliminary report

STUDY DESIGN

Cross-sectional study.

OBJECTIVE

Pain in individuals with opered scoliosis is usually evaluated with a postural analysis or questionnaire. In this study, we evaluated pain in individuals with scoliosis who underwent spinal correction surgery by tractography and compared it with individuals with non-opered scoliosis and healthy individuals.

DESIGN

Fifteen healthy individuals, 15 non-operated scoliosis patients and 15 operated scoliosis patients were included in the study.

METHODS

All female participants in this prospectively planned study used their right hand as the dominant hand. Bilateral tractography analysis of the pain pathways was performed with DSI Studio software using brain magnetic resonance images (MRI) of the participants. Statistical analysis of the study was performed with IBM SPSS 23.0 and p<0.05 values were considered significant.

RESULTS

It was observed that the tractography values of the operated scoliosis group were similar to the control group (p˃0.05). In the non-operated scoliosis group, tractography findings related to nerve conduction velocity such as fiber count, fiber ratio and axial diffusivity (AD) were found to be higher than the other two groups (p<0.05). Fractional anisotropy (FA) values of the unoperated scoliosis group were significantly different between the pain pathways projected from the right/left side of the body (p<0.05).

CONCLUSION

The fact that the pain path tractography values of patients with scoliosis who underwent surgery were similar to those of healthy individuals may be evidence of decreased pain sensation reaching the brain. Surgery may be a good choice in the treatment of pain in patients with scoliosis.

Abnormalities of brain structure and function in cervical spondylosis: a multi-modal voxel-based meta-analysis

Background

Previous neuroimaging studies have revealed structural and functional brain abnormalities in patients with cervical spondylosis (CS). However, the results are divergent and inconsistent. Therefore, the present study conducted a multi-modal meta-analysis to investigate the consistent structural and functional brain alterations in CS patients.

Methods

A comprehensive literature search was conducted in five databases to retrieve relevant resting-state functional magnetic resonance imaging (rs-fMRI), structural MRI and diffusion tensor imaging (DTI) studies that measured brain functional and structural differences between CS patients and healthy controls (HCs). Separate and multimodal meta-analyses were implemented, respectively, by employing Anisotropic Effect-size Signed Differential Mapping software.

Results

13 rs-fMRI studies that used regional homogeneity, amplitude of low-frequency fluctuations (ALFF) and fractional ALFF, seven voxel-based morphometry (VBM) studies and one DTI study were finally included in the present research. However, no studies on surface-based morphometry (SBM) analysis were included in this research. Due to the insufficient number of SBM and DTI studies, only rs-fMRI and VBM meta-analyses were conducted. The results of rs-fMRI meta-analysis showed that compared to HCs, CS patients demonstrated decreased regional spontaneous brain activities in the right lingual gyrus, right middle temporal gyrus (MTG), left inferior parietal gyrus and right postcentral gyrus (PoCG), while increased activities in the right medial superior frontal gyrus, bilateral middle frontal gyrus and right precuneus. VBM meta-analysis detected increased GMV in the right superior temporal gyrus (STG) and right paracentral lobule (PCL), while decreased GMV in the left supplementary motor area and left MTG in CS patients. The multi-modal meta-analysis revealed increased GMV together with decreased regional spontaneous brain activity in the left PoCG, right STG and PCL among CS patients.

Conclusion

This meta-analysis revealed that compared to HCs, CS patients had significant alterations in GMV and regional spontaneous brain activity. The altered brain regions mainly included the primary visual cortex, the default mode network and the sensorimotor area, which may be associated with CS patients' symptoms of sensory deficits, blurred vision, cognitive impairment and motor dysfunction. The findings may contribute to understanding the underlying pathophysiology of brain dysfunction and provide references for early diagnosis and treatment of CS.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/, CRD42022370967.

Quantitative Magnetic Resonance Imaging for Neurodevelopmental Outcome Prediction in Neonates Born Extremely Premature-An Exploratory Study

PURPOSE

Neonates born at < 28 weeks of gestation are at risk for neurodevelopmental delay. The aim of this study was to identify quantitative MR-based metrics for the prediction of neurodevelopmental outcomes in extremely preterm neonates.

METHODS

T1-/T2-relaxation times (T1R/T2R), ADC, and fractional anisotropy (FA) of the left/right posterior limb of the internal capsule (PLIC) and the brainstem were determined at term-equivalent ages in a sample of extremely preterm infants (n = 33). Scores for cognitive, language, and motor outcomes were collected at one year corrected-age. Pearson's correlation analyses detected relationships between quantitative measures and outcome data. Stepwise regression procedures identified imaging metrics to estimate neurodevelopmental outcomes.

RESULTS

Cognitive outcomes correlated significantly with T2R (r = 0.412; p = 0.017) and ADC (r = -0.401; p = 0.021) (medulla oblongata). Furthermore, there were significant correlations between motor outcomes and T1R (pontine tegmentum (r = 0.346; p = 0.049), midbrain (r = 0.415; p = 0.016), right PLIC (r = 0.513; p = 0.002), and left PLIC (r = 0.504; p = 0.003)); T2R (right PLIC (r = 0.405; p = 0.019)); ADC (medulla oblongata (r = -0.408; p = 0.018) and pontine tegmentum (r = -0.414; p = 0.017)); and FA (pontine tegmentum (r = -0.352; p = 0.045)). T2R/ADC (medulla oblongata) (cognitive outcomes (R2 = 0.296; p = 0.037)) and T1R (right PLIC)/ADC (medulla oblongata) (motor outcomes (R2 = 0.405; p = 0.009)) revealed predictive potential for neurodevelopmental outcomes.

CONCLUSION

There are relationships between relaxometry‑/DTI-based metrics determined by neuroimaging near term and neurodevelopmental outcomes collected at one year of age. Both modalities bear prognostic potential for the prediction of cognitive and motor outcomes. Thus, quantitative MRI at term-equivalent ages represents a promising approach with which to estimate neurologic development in extremely preterm infants.

Prediction of cognitive decline in Parkinson's disease based on MRI radiomics and clinical features: A multicenter study

OBJECTIVE

To develop and validate a multimodal combinatorial model based on whole-brain magnetic resonance imaging (MRI) radiomic features for predicting cognitive decline in patients with Parkinson's disease (PD).

METHODS

This study included a total of 222 PD patients with normal baseline cognition, of whom 68 had cognitive impairment during a 4-year follow-up period. All patients underwent MRI scans, and radiomic features were extracted from the whole-brain MRI images of the training set, and dimensionality reduction was performed to construct a radiomics model. Subsequently, Screening predictive factors for cognitive decline from clinical features and then combining those with a radiomics model to construct a multimodal combinatorial model for predicting cognitive decline in PD patients. Evaluate the performance of the comprehensive model using the receiver-operating characteristic curve, confusion matrix, F1 score, and survival curve. In addition, the quantitative characteristics of diffusion tensor imaging (DTI) from corpus callosum were selected from 52 PD patients to further validate the clinical efficacy of the model.

RESULTS

The multimodal combinatorial model has good classification performance, with areas under the curve of 0.842, 0.829, and 0.860 in the training, test, and validation sets, respectively. Significant differences were observed in the number of cognitive decline PD patients and corpus callosum-related DTI parameters between the low-risk and high-risk groups distinguished by the model (p < 0.05). The survival curve analysis showed a statistically significant difference in the progression time of mild cognitive impairment between the low-risk and the high-risk groups.

CONCLUSIONS

The building of a multimodal combinatorial model based on radiomic features from MRI can predict cognitive decline in PD patients, thus providing adaptive strategies for clinical practice.

Stepwise reduction of bony density in patients induces a higher risk of annular tears by deteriorating the local biomechanical environment

BACKGROUND CONTEXT

The relationship between osteoporosis and intervertebral disc degeneration (IDD) remains unclear. Considering that annular tear is the primary phenotype of IDD in the lumbar spine, the deteriorating local biomechanical environment may be the main trigger for annular tears.

PURPOSE

To investigate whether poor bone mineral density (BMD) in the vertebral bodies may increase the risk of annular tears via the degradation of the local biomechanical environment.

STUDY DESIGN

This study was a retrospective investigation with relevant numerical mechanical simulations.

PATIENT SAMPLE

A total of 64 patients with low back pain (LBP) and the most severe IDD in the L4-L5 motion segment were enrolled.

OUTCOME MEASURES

Annulus integration status was assessed using diffusion tensor fibre tractography (DTT). Hounsfield unit (HU) values of adjacent vertebral bodies were employed to determine BMD. Numerical simulations were conducted to compute stress values in the annulus of models with different BMDs and body positions.

METHODS

The clinical data of the 64 patients with low back pain were collected retrospectively. The BMD of the vertebral bodies was measured using the HU values, and the annulus integration status was determined according to DTT. The data of the patients with and without annular tears were compared, and regression analysis was used to identify the independent risk factors for annular tears. Furthermore, finite element models of the L4-L5 motion segment were constructed and validated, followed by estimating the maximum stress on the post and postlateral interfaces between the superior and inferior bony endplates (BEPs) and the annulus.

RESULTS

Patients with lower HU values in their vertebral bodies had significantly higher incidence rates of annular tears, with decreased HU values being an independent risk factor for annular tears. Moreover, increased stress on the BEP-annulus interfaces was associated with a stepwise reduction of bony density (ie, elastic modulus) in the numerical models.

CONCLUSIONS

The stepwise reduction of bony density in patients results in a higher risk of annular tears by deteriorating the local biomechanical environment. Thus, osteoporosis should be considered to be a potential risk factor for IDD biomechanically.

Differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognitive function between untreated major depressive disorder and schizophrenia with depressive mood patients

BACKGROUND

Distinguishing untreated major depressive disorder without medication (MDD) from schizophrenia with depressed mood (SZDM) poses a clinical challenge. This study aims to investigate differences in fractional amplitude of low-frequency fluctuations (fALFF) and cognition in untreated MDD and SZDM patients.

METHODS

The study included 42 untreated MDD cases, 30 SZDM patients, and 46 healthy controls (HC). Cognitive assessment utilized the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted, and data were processed using fALFF in slow-4 and slow-5 bands.

RESULTS

Significant fALFF changes were observed in four brain regions across MDD, SZDM, and HC groups for both slow-4 and slow-5 fALFF. Compared to SZDM, the MDD group showed increased slow-5 fALFF in the right gyrus rectus (RGR). Relative to HC, SZDM exhibited decreased slow-5 fALFF in the left gyrus rectus (LGR) and increased slow-5 fALFF in the right putamen. Changes in slow-5 fALFF in both RGR and LGR were negatively correlated with RBANS scores. No significant correlations were found between remaining fALFF (slow-4 and slow-5 bands) and RBANS scores in MDD or SZDM groups.

CONCLUSIONS

Alterations in slow-5 fALFF in RGR may serve as potential biomarkers for distinguishing MDD from SZDM, providing preliminary insights into the neural mechanisms of cognitive function in schizophrenia.

The Alterations in the Brain Corresponding to Low Back Pain: Recent Insights and Advances

Low back pain (LBP) is a leading cause of global disabilities. Numerous molecular, cellular, and anatomical factors are implicated in LBP. Current issues regarding neurologic alterations in LBP have focused on the reorganization of peripheral nerve and spinal cord, but neural mechanisms of exactly what LBP impacts on the brain required further researches. Based on existing clinical studies that chronic pain problems were accompanying alterations in brain structures and functions, researchers proposed logical conjectures that similar alterations occur in LBP patients as well. With recent extensive studies carried out using noninvasive neuroimaging technique, increasing number of abnormalities and alterations has been identified. Here, we reviewed brain alterations including white matters, grey matters, and neural circuits between brain areas, which are involved in chronic LBP. Moreover, brain structural and functional connectivity abnormalities are correlated to the happening and transition of LBP. The negative emotions related to back pain indicate possible alterations in emotional brain regions. Thus, the aim of this review is to summarize current findings on the alterations corresponding to LBP in the brain. It will not only further our understanding of etiology of LBP and understanding of negative emotions accompanying with back pain but also provide ideas and basis for new accesses to the diagnosis, treatment, and rehabilitation afterward based on integral medicine.

Longitudinal Biochemical and Behavioral Alterations in a Gyrencephalic Model of Blast-Related Mild Traumatic Brain Injury

Blast-related traumatic brain injury (bTBI) is a major cause of neurological disorders in the U.S. military that can adversely impact some civilian populations as well and can lead to lifelong deficits and diminished quality of life. Among these types of injuries, the long-term sequelae are poorly understood because of variability in intensity and number of the blast exposure, as well as the range of subsequent symptoms that can overlap with those resulting from other traumatic events (e.g., post-traumatic stress disorder). Despite the valuable insights that rodent models have provided, there is a growing interest in using injury models using species with neuroanatomical features that more closely resemble the human brain. With this purpose, we established a gyrencephalic model of blast injury in ferrets, which underwent blast exposure applying conditions that closely mimic those associated with primary blast injuries to warfighters. In this study, we evaluated brain biochemical, microstructural, and behavioral profiles after blast exposure using in vivo longitudinal magnetic resonance imaging, histology, and behavioral assessments. In ferrets subjected to blast, the following alterations were found: 1) heightened impulsivity in decision making associated with pre-frontal cortex/amygdalar axis dysfunction; 2) transiently increased glutamate levels that are consistent with earlier findings during subacute stages post-TBI and may be involved in concomitant behavioral deficits; 3) abnormally high brain N-acetylaspartate levels that potentially reveal disrupted lipid synthesis and/or energy metabolism; and 4) dysfunction of pre-frontal cortex/auditory cortex signaling cascades that may reflect similar perturbations underlying secondary psychiatric disorders observed in warfighters after blast exposure.

Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders

Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.

Recent Advances in Habenula Imaging Technology: A Comprehensive Review

The habenula (Hb) is involved in many natural human behaviors, and the relevance of its alterations in size and neural activity to several psychiatric disorders and addictive behaviors has been presumed and investigated in recent years using magnetic resonance imaging (MRI). Although the Hb is small, an increasing number of studies have overcome the difficulties in MRI. Conventional structural-based imaging also has great defects in observing the Hb contrast with adjacent structures. In addition, more and more attention should be paid to the Hb's functional, structural, and quantitative imaging studies. Several advanced MRI methods have recently been employed in clinical studies to explore the Hb and its involvement in psychiatric diseases. This review summarizes the anatomy and function of the human Hb; moreover, it focuses on exploring the human Hb with noninvasive MRI approaches, highlighting strategies to overcome the poor contrast with adjacent structures and the need for multiparametric MRI to develop imaging markers for diagnosis and treatment follow-up. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

IVD fibrosis and disc collapse comprehensively aggravate vertebral body disuse osteoporosis and zygapophyseal joint osteoarthritis by posteriorly shifting the load transmission pattern

BACKGROUND

Disuse is a typical phenotype of osteoporosis, but the underlying mechanism has yet to be identified in elderly patients. Disc collapse and intervertebral disc (IVD) fibrosis are two main pathological changes in IVD degeneration (IDD) progression, given that these changes affect load transmission patterns, which may lead to disuse osteoporosis of vertebral bodies and zygapophyseal joint (ZJ) osteoarthritis (ZJOA) biomechanically.

METHODS

Clinical data from 59 patients were collected retrospectively. Patient vertebral bony density, ZJOA grade, and disc collapse status were judged via CT. The IVD fibrosis grade was determined based on the FA measurements. Regression analyses identified potential independent risk factors for osteoporosis and ZJOA. L4-L5 numerical models with and without disc collapse and IVD fibrosis were constructed; stress distributions on the bony endplate (BEP) and zygapophyseal joint (ZJ) cartilages were computed in models with and without disc collapse and IVD fibrosis.

RESULTS

A significantly lower disc height ratio and significantly greater FA were recorded in patients with ZJOA. A significant correlation was observed between lower HU values and two parameters related to IDD progression. These factors were also proven to be independent risk factors for both osteoporosis and ZJOA. Correspondingly, compared to the intact model without IDD. Lower stress on vertebral bodies and greater stress on ZJOA can be simultaneously recorded in models of disc collapse and IVD fibrosis.

CONCLUSIONS

IVD fibrosis and disc collapse simultaneously aggravate vertebral body disuse osteoporosis and ZJOA by posteriorly shifting the load transmission pattern.

ECHDC3 Variant Regulates the Right Hippocampal Microstructural Integrity and Verbal Memory in Type 2 Diabetes Mellitus

ECHDC3 is a risk gene for white matter (WM) hyperintensity and is associated with insulin resistance. This study aimed to investigate whether ECHDC3 variants selectively regulate brain WM microstructures and episodic memory in patients with type 2 diabetes mellitus (T2DM). We enrolled 106 patients with T2DM and 111 healthy controls. A voxel-wise general linear model was employed to explore the interaction effect between ECHDC3 rs11257311 polymorphism and T2DM diagnosis on fractional anisotropy (FA). A linear modulated mediation analysis was conducted to examine the potential of FA value to mediate the influence of T2DM on episodic memory in an ECHDC3-dependent manner. We observed a noteworthy interaction between genotype and diagnosis on FA in the right inferior temporal WM, right anterior limb of the internal capsule, right frontal WM, and the right hippocampus. Modulated mediation analysis revealed a significant ECHDC3 modulation on the T2DM → right hippocampal FA → short-term memory pathway, with only rs11257311 G risk homozygote demonstrating significant mediation effect. Together, our findings provide evidence of ECHDC3 modulating the effect of T2DM on right hippocampal microstructural impairment and short-term memory decline, which might be a neuro-mechanism for T2DM related episodic memory impairment.

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.

Adolescents at risk for depression show increased white matter microstructure with age across diffuse areas of the brain

Maternal history of depression is a strong predictor of depression in offspring and linked to structural and functional alterations in the developing brain. However, very little work has examined differences in white matter in adolescents at familial risk for depression. In a sample aged 9-14 (n = 117), we used tract-based spatial statistics (TBSS) to examine differences in white matter microstructure between adolescents with (n = 42) and without (n = 75) maternal history of depression. Microstructure was indexed using fractional anisotropy (FA). Threshold-free cluster enhancement was applied and cluster maps were thresholded at whole-brain family-wise error < .05. There was no significant main effect of risk status on FA. However, there was a significant interaction between risk status and age, such that large and diffuse portions of the white matter skeleton showed relatively increased FA with age for youth with a maternal history of depression compared to those without. Most tracts identified by the interaction were robust to controlling for sex, youth internalizing, in-scanner motion, neighborhood SES, and intra-cranial volume, evidence that maternal depression is a unique predictor of white matter alterations in youth. Widespread increases in FA with age may correspond to a global pattern of accelerated brain maturation in youth at risk for depression.

White matter tract microstructure, macrostructure, and associated cortical gray matter morphology across the lifespan

Characterizing how, when and where the human brain changes across the lifespan is fundamental to our understanding of developmental processes of childhood and adolescence, degenerative processes of aging, and divergence from normal patterns in disease and disorders. We aimed to provide detailed descriptions of white matter pathways across the lifespan by thoroughly characterizing white matter microstructure, white matter macrostructure, and morphology of the cortex associated with white matter pathways. We analyzed 4 large, high-quality, publicly-available datasets comprising 2789 total imaging sessions, and participants ranging from 0 to 100 years old, using advanced tractography and diffusion modeling. We first find that all microstructural, macrostructural, and cortical features of white matter bundles show unique lifespan trajectories, with rates and timing of development and degradation that vary across pathways - describing differences between types of pathways and locations in the brain, and developmental milestones of maturation of each feature. Second, we show cross-sectional relationships between different features that may help elucidate biological changes occurring during different stages of the lifespan. Third, we show unique trajectories of age-associations across features. Finally, we find that age associations during development are strongly related to those during aging. Overall, this study reports normative data for several features of white matter pathways of the human brain that will be useful for studying normal and abnormal white matter development and degeneration.

Mechanical stiffness and anisotropy measured by MRE during brain development in the minipig

The relationship between brain development and mechanical properties of brain tissue is important, but remains incompletely understood, in part due to the challenges in measuring these properties longitudinally over time. In addition, white matter, which is composed of aligned, myelinated, axonal fibers, may be mechanically anisotropic. Here we use data from magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI) to estimate anisotropic mechanical properties in six female Yucatan minipigs at ages from 3 to 6 months. Fiber direction was estimated from the principal axis of the diffusion tensor in each voxel. Harmonic shear waves in the brain were excited by three different configurations of a jaw actuator and measured using a motion-sensitive MR imaging sequence. Anisotropic mechanical properties are estimated from displacement field and fiber direction data with a finite element- based, transversely-isotropic nonlinear inversion (TI-NLI) algorithm. TI-NLI finds spatially resolved TI material properties that minimize the error between measured and simulated displacement fields. Maps of anisotropic mechanical properties in the minipig brain were generated for each animal at all four ages. These maps show that white matter is more dissipative and anisotropic than gray matter, and reveal significant effects of brain development on brain stiffness and structural anisotropy. Changes in brain mechanical properties may be a fundamental biophysical signature of brain development.

Exploring the Frontiers of Neuroimaging: A Review of Recent Advances in Understanding Brain Functioning and Disorders

Neuroimaging has revolutionized our understanding of brain function and has become an essential tool for researchers studying neurological disorders. Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two widely used neuroimaging techniques to review changes in brain activity. fMRI is a noninvasive technique that uses magnetic fields and radio waves to produce detailed brain images. An EEG is a noninvasive technique that records the brain's electrical activity through electrodes placed on the scalp. This review overviews recent developments in noninvasive functional neuroimaging methods, including fMRI and EEG. Recent advances in fMRI technology, its application to studying brain function, and the impact of neuroimaging techniques on neuroscience research are discussed. Advances in EEG technology and its applications to analyzing brain function and neural oscillations are also highlighted. In addition, advanced courses in neuroimaging, such as diffusion tensor imaging (DTI) and transcranial electrical stimulation (TES), are described, along with their role in studying brain connectivity, white matter tracts, and potential treatments for schizophrenia and chronic pain. Application. The review concludes by examining neuroimaging studies of neurodevelopmental and neurological disorders such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), Alzheimer's disease (AD), and Parkinson's disease (PD). We also described the role of transcranial direct current stimulation (tDCS) in ASD, ADHD, AD, and PD. Neuroimaging techniques have significantly advanced our understanding of brain function and provided essential insights into neurological disorders. However, further research into noninvasive treatments such as EEG, MRI, and TES is necessary to continue to develop new diagnostic and therapeutic strategies for neurological disorders.

Quantification of Diffusion Magnetic Resonance Imaging for Prognostic Prediction of Neonatal Hypoxic-Ischemic Encephalopathy

Neonatal hypoxic-ischemic encephalopathy (HIE) is the leading cause of acquired neonatal brain injury with the risk of developing serious neurological sequelae and death. An accurate and robust prediction of short- and long-term outcomes may provide clinicians and families with fundamental evidence for their decision-making, the design of treatment strategies, and the discussion of developmental intervention plans after discharge. Diffusion tensor imaging (DTI) is one of the most powerful neuroimaging tools with which to predict the prognosis of neonatal HIE by providing microscopic features that cannot be assessed by conventional magnetic resonance imaging (MRI). DTI provides various scalar measures that represent the properties of the tissue, such as fractional anisotropy (FA) and mean diffusivity (MD). Since the characteristics of the diffusion of water molecules represented by these measures are affected by the microscopic cellular and extracellular environment, such as the orientation of structural components and cell density, they are often used to study the normal developmental trajectory of the brain and as indicators of various tissue damage, including HIE-related pathologies, such as cytotoxic edema, vascular edema, inflammation, cell death, and Wallerian degeneration. Previous studies have demonstrated widespread alteration in DTI measurements in severe cases of HIE and more localized changes in neonates with mild-to-moderate HIE. In an attempt to establish cutoff values to predict the occurrence of neurological sequelae, MD and FA measurements in the corpus callosum, thalamus, basal ganglia, corticospinal tract, and frontal white matter have proven to have an excellent ability to predict severe neurological outcomes. In addition, a recent study has suggested that a data-driven, unbiased approach using machine learning techniques on features obtained from whole-brain image quantification may accurately predict the prognosis of HIE, including for mild-to-moderate cases. Further efforts are needed to overcome current challenges, such as MRI infrastructure, diffusion modeling methods, and data harmonization for clinical application. In addition, external validation of predictive models is essential for clinical application of DTI to prognostication.

Associations between psychological resilience and metrics of white matter microstructure in pediatric concussion

This study investigated associations between psychological resilience and characteristics of white matter microstructure in pediatric concussion. This is a case control study and a planned substudy of a larger randomized controlled trial. Children with an acute concussion or orthopedic injury were recruited from the emergency department. Participants completed both the Connor-Davidson Resilience Scale 10 and an MRI at 72 h and 4-weeks post-injury. The association between resiliency and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) at both timepoints were examined. We examined whether these associations were moderated by group. The association between resiliency captured at 72 h and diffusion tensor imaging metrics at 4 weeks was also investigated. Clusters were extracted using a significance threshold of threshold-free cluster enhancement corrected p < .05. A total of 66 children with concussion (median (IQR) age = 12.88 (IQR: 11.80-14.36); 47% female) and 29 children with orthopedic-injury (median (IQR) age = 12.49 (IQR: 11.18-14.01); 41% female) were included. A negative correlation was identified in the concussion group between 72 h resilience and 72 h FA. Meanwhile, positive correlations were identified in the concussion group with concussion between 72 h resilience and both 72 h MD and 72 h RD. These findings suggest that 72 h resilience is associated with white matter microstructure of the forceps minor, superior longitudinal fasciculus, and anterior thalamic radiation at 72 h post-concussion. Resilience seems to be associated with neural integrity only in the acute phase of concussion and thus may be considered when researching concussion recovery.

The alterations of spontaneous neural activities and white matter microstructures in anti-N-methyl-D-aspartate receptor encephalitis: a resting-state fMRI and DTI study

BACKGROUND AND PURPOSE

Limited studies had jointly excavated the structural and functional changes in cognitive deficit in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients. We aimed to explore these changes in anti-NMDAR patients and their effect on cognitive function.

METHODS

Twenty-three patients and 25 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging, diffusion tensor imaging scanning, and neuroethology tests. The significantly differentiated brain regions via the fractional amplitude of low-frequency fluctuation (fALFF) were defined as regions of interest (ROIs). Granger causal, functional connectivity, and tract-based spatial statistical analyses were applied to explore the functional changes in ROIs and assess the structural changes.

RESULTS

HCs outperformed patients in Montreal Cognitive Assessment. The fALFF values of right gyrus rectus (RGR) in patients were significantly reduced. The fractional anisotropy (FA) values of WM in the genu of corpus callosum and right superior corona radiata were significantly decreased and positively associated with neuroethology testing scores. The Granger causal connectivity (GCC) from the left inferior parietal lobule to RGR was significantly decreased and positively associated with inherent vigilance. Indicated by the multiple linear regression result, decreased FA value of the right superior corona radiata might be a reliable marker that reflects the cognitive impairment.

CONCLUSIONS

Significant changes in spontaneous neural activities, GCC, and WM structures in anti-NMDAR encephalitis were reported. These findings promote the understanding of underlying relationships between cerebral function, structural network alterations, and cognitive dysfunction.

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.

Applications of advanced diffusion MRI in early brain development: a comprehensive review

Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.

Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b-value in diffusion MRI

Noninvasive diffusion magnetic resonance imaging (dMRI) has been widely employed in both clinical and research settings to investigate brain tissue microstructure. Despite the evidence that dMRI-derived fractional anisotropy (FA) correlates with white matter properties, the metric is not specific. Recent studies have reported that FA is dependent on the b-value, and its origin has primarily been attributed to either the influence of microstructure or the noise-floor effect. A systematic investigation into the inter-relationship of these two effects is however still lacking. This study aims to quantify contributions of the reported differences in intra- and extra-neurite diffusivity to the observed changes in FA, in addition to the noise in measurements. We used in-vivo and post-mortem human brain imaging, as well as numerical simulations and histological validation, for this purpose. Our investigations reveal that the percentage difference of FA between b-values (pdFA) has significant positive associations with neurite density index (NDI), which is derived from in-vivo neurite orientation dispersion and density imaging (NODDI), or Bielschowsky's silver impregnation (BIEL) staining sections of fixed post-mortem human brain samples. Furthermore, such an association is found to be varied with Signal-to-Noise Ratio (SNR) level, indicating a nonlinear interaction effect between tissue microstructure and noise. Finally, a multicompartment model simulation revealed that these findings can be driven by differing diffusivities of intra- and extra-neurite compartments in tissue, with the noise-floor further amplifying the effect. In conclusion, both the differences in intra- and extra-neurite diffusivity and noise-floor effects significantly contribute to the FA difference associated with the b-value.

Is the Integration Problem in the Sensoriomotor System the Cause of Adolescent Idiopathic Scoliosis?

PURPOSE

The reason behind the balance control disorder seen in adolescent idiopathic scoliosis (AIS) has been suggested as a central nervous system dysfunction, yet it has not been investigated in detail whether this problem originates from sensory, motor, or from both systems. This study aimed to reveal the differences in the pathways that provide proprioceptive sense, motor control, and coordination between these 2 systems in female individuals with AIS.

METHODS

Brain Diffusion Tensor Imaging was applied to 30 healthy individuals and 30 Lenke type 1 AIS patients. All of the individuals included in the study were predominantly right-handed and aged between 10 and 18. Diffusion tensor imaging of both groups were performed bilateral tractography on the corticospinal tract (CS tr), medial lemniscus (ML), superior longitudinal fasciculus (SLF), and inferior longitudinal fasciculus (ILF) tracts using DSI Studio software.

RESULTS

Significant differences in the parameters of CS tr, ML, SLF, ILF pathways were found between the AIS and the control groups. In the AIS group, significant differences were found in the fiber count and fiber ratio of the ML that carries the proprioceptive sense and CS tr, which is responsible for the somatomotor system. There were also significant differences between the left and right CS tr, ML, SLF, and ILF pathways of the AIS group ( P <0.05).

CONCLUSIONS

Differences in the CS tr, ML, SLF, and ILF pathways may trigger muscular asymmetry and cause postural instability and thus spinal deformity in AIS.

Multivariate associations between behavioural dimensions and white matter across children and adolescents with and without attention-deficit/hyperactivity disorder

BACKGROUND

Attention deficit/hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental disorder. Integrity of white matter microstructure plays a key role in the neural mechanism of ADHD presentations. However, the relationships between specific behavioural dimensions and white matter microstructure are less well known. This study aimed to identify associations between white matter and a broad set of clinical features across children and adolescent with and without ADHD using a data-driven multivariate approach.

METHOD

We recruited a total of 130 children (62 controls and 68 ADHD) and employed regularized generalized canonical correlation analysis to characterize the associations between white matter and a comprehensive set of clinical measures covering three domains, including symptom, cognition and behaviour. We further applied linear discriminant analysis to integrate these associations to explore potential developmental effects.

RESULTS

We delineated two brain-behaviour dimensional associations in each domain resulting a total of six multivariate patterns of white matter microstructural alterations linked to hyperactivity-impulsivity and mild affected; executive functions and working memory; externalizing behaviour and social withdrawal, respectively. Apart from executive function and externalizing behaviour sharing similar white matter patterns, all other dimensions linked to a specific pattern of white matter microstructural alterations. The multivariate dimensional association scores showed an overall increase and normalization with age in ADHD group while remained stable in controls.

CONCLUSIONS

We found multivariate neurobehavioral associations exist across ADHD and controls, which suggested that multiple white matter patterns underlie ADHD heterogeneity and provided neural bases for more precise diagnosis and individualized treatment.

Preterm birth and neonatal white matter microstructure in in-vivo reconstructed fiber tracts among audiovisual integration brain regions

Individuals born preterm are at risk of developing a variety of sequelae. Audiovisual integration (AVI) has received little attention despite its facilitating role in the development of socio-cognitive abilities. The present study assessed the association between prematurity and in-vivo reconstructed fiber bundles among brain regions relevant for AVI. We retrieved data from 63 preterm neonates enrolled in the Developing Human Connectome Project (http://www.developingconnectome.org/) and matched them with 63 term-born neonates from the same study by means of propensity score matching. We performed probabilistic tractography, DTI and NODDI analysis on the traced fibers. We found that specific DTI and NODDI metrics are significantly associated with prematurity in neonates matched for postmenstrual age at scan. We investigated the spatial overlap and developmental order of the reconstructed tractograms between preterm and full-term neonates. Permutation-based analysis revealed significant differences in dice similarity coefficients and developmental order between preterm and full term neonates at the group level. Contrarily, no group differences in the amount of interindividual variability of DTI and NODDI metrics were observed. We conclude that microstructural detriment in the reconstructed fiber bundles along with developmental and morphological differences are likely to contribute to disadvantages in AVI in preterm individuals.

Brain correlates of declarative memory atypicalities in autism: a systematic review of functional neuroimaging findings

The long-described atypicalities of memory functioning experienced by people with autism have major implications for daily living, academic learning, as well as cognitive remediation. Though behavioral studies have identified a robust profile of memory strengths and weaknesses in autism spectrum disorder (ASD), few works have attempted to establish a synthesis concerning their neural bases. In this systematic review of functional neuroimaging studies, we highlight functional brain asymmetries in three anatomical planes during memory processing between individuals with ASD and typical development. These asymmetries consist of greater activity of the left hemisphere than the right in ASD participants, of posterior brain regions-including hippocampus-rather than anterior ones, and presumably of the ventral (occipito-temporal) streams rather than the dorsal (occipito-parietal) ones. These functional alterations may be linked to atypical memory processes in ASD, including the pre-eminence of verbal over spatial information, impaired active maintenance in working memory, and preserved relational memory despite poor context processing in episodic memory.

The combined use of DTI and MR elastography for monitoring microstructural changes in the developing brain of a neurodevelopmental disorder model: Poly (I:C)-induced maternal immune-activated rats

Early neuropathology mechanisms in neurodevelopmental disorders are partially understood because routine anatomical magnetic resonance imaging (MRI) cannot detect subtle brain microstructural changes in vivo during postnatal development. Therefore, we investigated the potential value of magnetic resonance elastography (MRE) and diffusion tensor imaging (DTI) in a rat model of neurodevelopmental disorder induced by maternal immune activation. We studied 12 offspring of mothers injected with polyriboinosinic-polyribocytidylic acid (poly (I:C), 4 mg/kg) on gestational day 15, plus 8 controls. T2-weighted anatomical MR images, MRE (800 Hz) and DTI (30 gradient directions, b = 765.8 s/mm2, 5 images, b = 0 s/mm2) were collected when the rats were 4 and 10 weeks old, and results were compared with histological analysis performed at week 10. Ventricles were ~1.4 fold larger from week 4 in poly (I:C) rats than in controls. No other morphological abnormalities were detected in poly(I:C) rats. At week 4, larger ventricles were correlated with lower external capsule fractional anisotropy and internal capsule radial diffusion (Pearson, r = -0.53, 95% confidence intervals (CI) [-0.79 to -0.12], and r = -0.45, 95% CI [-0.74 to -0.01], respectively). The mean and radial diffusion of the corpus callosum, the mean and axial diffusion of the internal capsule and the radial diffusion properties in the external capsule increased with age for poly (I:C) rats only (Sidak's comparison, P<0.05). Cortical stiffness did not increase with age in poly (I:C) rats, in contrast with controls (Sidak's comparison, P = 0.005). These temporal variations probably reflected abnormal myelin content, decreased cell density and microglia activation observed at week 10 after histological assessment. To conclude, MRE and DTI allow monitoring of abnormal brain microstructural changes in poly (I:C) rats from week 4 after birth. This suggests that both imaging techniques have the potential to be used as complementary imaging tools to routine anatomical imaging to assist with the early diagnosis of neurodevelopmental disorders and provide new insights into neuropathology.

Deciphering the developmental order and microstructural patterns of early white matter pathways in a diffusion MRI based fetal brain atlas

White matter (WM) of the fetal brain undergoes rapid development to form early structural connections. Diffusion magnetic resonance imaging (dMRI) has shown to be a useful tool to depict fetal brain WM in utero, and many studies have observed increasing fractional anisotropy and decreasing diffusivity in the fetal brain during the second-to-third trimester, whereas others reported non-monotonic changes. Unbiased dMRI atlases of the fetal brain are important for characterizing the developmental trajectories of WM and providing normative references for in utero diagnosis of prenatal abnormalities. To date, the sole fetal brain dMRI atlas was collected from a Caucasian/mixed population and was constructed based on the diffusion tensor model with limited spatial resolution. In this work, we proposed a fiber orientation distribution (FOD) based pipeline for generating fetal brain dMRI atlases, which showed better registration accuracy than a diffusion tensor based pipeline. Based on the FOD-based pipeline, we constructed the first Chinese fetal brain dMRI atlas using 89 dMRI scans of normal fetuses at gestational age between 24 and 38 weeks. Complex non-monotonic trends of tensor- and FOD-derived microstructural parameters in eight WM tracts were observed, which jointly pointed to different phases of microstructural development. Specifically, we speculated that the turning point of the diffusivity trajectory may correspond to the starting point of pre-myelination, based on which, the developmental order of WM tracts can be mapped and the order was in agreement with the order of myelination from histological studies. The normative atlas also provided a reference for the detection of abnormal WM development, such as that in congenital heart disease. Therefore, the established high-order fetal brain dMRI atlas depicted the spatiotemporal pattern of early WM development, and findings may help decipher the distinct microstructural events in utero.

Key considerations for child and adolescent MRI data collection

Cognitive neuroimaging researchers' ability to infer accurate statistical conclusions from neuroimaging depends greatly on the quality of the data analyzed. This need for quality control is never more evident than when conducting neuroimaging studies with children and adolescents. Developmental neuroimaging requires patience, flexibility, adaptability, extra time, and effort. It also provides us a unique, non-invasive way to understand the development of cognitive processes, individual differences, and the changing relations between brain and behavior over the lifespan. In this discussion, we focus on collecting magnetic resonance imaging (MRI) data, as it is one of the more complex protocols used with children and youth. Through our extensive experience collecting MRI datasets with children and families, as well as a review of current best practices, we will cover three main topics to help neuroimaging researchers collect high-quality datasets. First, we review key recruitment and retention techniques, and note the importance for consistency and inclusion across groups. Second, we discuss ways to reduce scan anxiety for families and ways to increase scan success by describing the pre-screening process, use of a scanner simulator, and the need to focus on participant and family comfort. Finally, we outline several important design considerations in developmental neuroimaging such as asking a developmentally appropriate question, minimizing data loss, and the applicability of public datasets. Altogether, we hope this article serves as a useful tool for those wishing to enter or learn more about developmental cognitive neuroscience.

Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects

Cerebral small vessel disease (CSVD) is a leading cause of age-related microvascular cognitive decline, resulting in significant morbidity and decreased quality of life. Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging (MRI), key questions on CSVD remain elusive. Enhanced relationships and reliable lesion studies, such as white matter tractography using diffusion-based MRI (dMRI) are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD. Diffusion tensor imaging (DTI) and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage. However, due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting, interpreting the findings remain contentious, especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use. In this minireview, we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD, even for subclinical CSVD in at-risk individuals.

A diffusion tensor imaging analysis of white matter microstructures in non-operated craniosynostosis patients

PURPOSE

In 7 to 15-year-old operated syndromic craniosynostosis patients, we have shown the presence of microstructural anomalies in brain white matter by using DTI. To learn more about the cause of these anomalies, the aim of the study is to determine diffusivity values in white matter tracts in non-operated syndromic craniosynostosis patients aged 0-2 years compared to healthy controls.

METHODS

DTI datasets of 51 non-operated patients with syndromic craniosynostosis with a median [IQR] age of 0.40 [0.25] years were compared with 17 control subjects with a median of 1.20 [0.85] years. Major white matter tract pathways were reconstructed with ExploreDTI from MRI brain datasets acquired on a 1.5 T MRI system. Eigenvalues of these tract data were examined, with subsequent assessment of the affected tracts. Having syndromic craniosynostosis (versus control), gender, age, frontal occipital horn ratio (FOHR), and tract volume were treated as independent variables.

RESULTS

ʎ₂ and ʎ₃ of the tracts genu of the corpus callosum and the hippocampal segment of the cingulum bundle show a ƞ² > 0.14 in the comparison of patients vs controls, which indicates a large effect on radial diffusivity. Subsequent linear regressions on radial diffusivity of these tracts show that age and FOHR are significantly associated interacting factors on radial diffusivity (p < 0.025).

CONCLUSION

Syndromic craniosynostosis shows not to be a significant factor influencing the major white matter tracts. Enlargement of the ventricles show to be a significant factor on radial diffusivity in the tracts corpus callosum genu and the hippocampal segment of the cingulate bundle.

CLINICAL TRIAL REGISTRATION

MEC-2014-461.

Effects of binge drinking during adolescence and emerging adulthood on the brain: A systematic review of neuroimaging studies

Binge drinking (BD) is a common pattern of alcohol consumption which is generating great concern because of its deleterious consequences. We selected 33 neuroimaging studies of healthy young binge drinkers (BDs) by following PRISMA guidelines. This review provides a comprehensive overview of the relationship between BD and neurocognitive anomalies reported across magnetic resonance studies. Moreover, this work is the first in which results of relatively new imaging techniques, such as resting-state functional connectivity (RS-FC) and neurite orientation dispersion and density imaging (NODDI), have been reviewed using a systematic procedure. We established strict inclusion criteria in order to isolate the various potential effects of BD on the adolescent brain. Two authors independently evaluated the methodological quality, assessing different aspects related to sample size, and statistical correction methods, which are of particular importance in neuroimaging studies. BD is associated with structural and functional anomalies in several cortical and subcortical brain regions intimately involved in the control and regulation of impulsive or risky behaviours, as well as in the processing of reinforcing stimuli.

Development of white matter tracts between and within the dorsal and ventral streams

The degree of interaction between the ventral and dorsal visual streams has been discussed in multiple scientific domains for decades. Recently, several white matter tracts that directly connect cortical regions associated with the dorsal and ventral streams have become possible to study due to advancements in automated and reproducible methods. The developmental trajectory of this set of tracts, here referred to as the posterior vertical pathway (PVP), has yet to be described. We propose an input-driven model of white matter development and provide evidence for the model by focusing on the development of the PVP. We used reproducible, cloud-computing methods and diffusion imaging from adults and children (ages 5-8 years) to compare PVP development to that of tracts within the ventral and dorsal pathways. PVP microstructure was more adult-like than dorsal stream microstructure, but less adult-like than ventral stream microstructure. Additionally, PVP microstructure was more similar to the microstructure of the ventral than the dorsal stream and was predicted by performance on a perceptual task in children. Overall, results suggest a potential role for the PVP in the development of the dorsal visual stream that may be related to its ability to facilitate interactions between ventral and dorsal streams during learning. Our results are consistent with the proposed model, suggesting that the microstructural development of major white matter pathways is related, at least in part, to the propagation of sensory information within the visual system.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates-A Quantitative MRI Study

BACKGROUND AND PURPOSE

Former preterm born males are at higher risk for neurodevelopmental disabilities compared with female infants born at the same gestational age. This retrospective study investigated sex-related differences in the maturity of early myelinating brain regions in infants born <28 weeks' gestational age using diffusion tensor- and relaxometry-based MR imaging.

MATERIALS AND METHODS

Quantitative MR imaging sequence acquisitions were analyzed in a sample of 35 extremely preterm neonates imaged at term-equivalent ages. Quantitative MR imaging metrics (fractional anisotropy; ADC [10^-3mm²/s]; and T1-/T2-relaxation times [ms]) of the medulla oblongata, pontine tegmentum, midbrain, and the right/left posterior limbs of the internal capsule were determined on diffusion tensor- and multidynamic, multiecho sequence-based imaging data. ANCOVA and a paired t test were used to compare female and male infants and to detect hemispheric developmental asymmetries.

RESULTS

Seventeen female (mean gestational age at birth: 26 + 0 [SD, 1 + 4] weeks+days) and 18 male (mean gestational age at birth: 26 + 1 [SD, 1 + 3] weeks+days) infants were enrolled in this study. Significant differences were observed in the T2-relaxation time (P = .014) of the pontine tegmentum, T1-relaxation time (P = .011)/T2-relaxation time (P = .024) of the midbrain, and T1-relaxation time (P = .032) of the left posterior limb of the internal capsule. In both sexes, fractional anisotropy (P [♀] < .001/P [♂] < .001) and ADC (P [♀] = .017/P [♂] = .028) differed significantly between the right and left posterior limbs of the internal capsule.

CONCLUSIONS

The combined use of various quantitative MR imaging metrics detects sex-related and interhemispheric differences of WM maturity. The brainstem and the left posterior limb of the internal capsule of male preterm neonates are more immature compared with those of female infants at term-equivalent ages. Sex differences in WM maturation need further attention for the personalization of neonatal brain imaging.

Fiber tracing and microstructural characterization among audiovisual integration brain regions in neonates compared with young adults

Audiovisual integration has been related with cognitive-processing and behavioral advantages, as well as with various socio-cognitive disorders. While some studies have identified brain regions instantiating this ability shortly after birth, little is known about the structural pathways connecting them. The goal of the present study was to reconstruct fiber tracts linking AVI regions in the newborn in-vivo brain and assess their adult-likeness by comparing them with analogous fiber tracts of young adults. We performed probabilistic tractography and compared connective probabilities between a sample of term-born neonates (N = 311; the Developing Human Connectome Project (dHCP, http://www.developingconnectome.org) and young adults (N = 311 The Human Connectome Project; https://www.humanconnectome.org/) by means of a classification algorithm. Furthermore, we computed Dice coefficients to assess between-group spatial similarity of the reconstructed fibers and used diffusion metrics to characterize neonates' AVI brain network in terms of microstructural properties, interhemispheric differences and the association with perinatal covariates and biological sex. Overall, our results indicate that the AVI fiber bundles were successfully reconstructed in a vast majority of neonates, similarly to adults. Connective probability distributional similarities and spatial overlaps of AVI fibers between the two groups differed across the reconstructed fibers. There was a rank-order correspondence of the fibers' connective strengths across the groups. Additionally, the study revealed patterns of diffusion metrics in line with early white matter developmental trajectories and a developmental advantage for females. Altogether, these findings deliver evidence of meaningful structural connections among AVI regions in the newborn in-vivo brain.

Fetal programming of human energy homeostasis brain networks: Issues and considerations

In this paper, we present a transdisciplinary framework and testable hypotheses regarding the process of fetal programming of energy homeostasis brain circuitry. Our model proposes that key aspects of energy homeostasis brain circuitry already are functional by the time of birth (with substantial interindividual variation); that this phenotypic variation at birth is an important determinant of subsequent susceptibility for energy imbalance and childhood obesity risk; and that this brain circuitry exhibits developmental plasticity, in that it is influenced by conditions during intrauterine life, particularly maternal-placental-fetal endocrine, immune/inflammatory, and metabolic processes and their upstream determinants. We review evidence that supports the scientific premise for each element of this formulation, identify future research directions, particularly recent advances that may facilitate a better quantification of the ontogeny of energy homeostasis brain networks, highlight animal and in vitro-based approaches that may better address the determinants of interindividual variation in energy homeostasis brain networks, and discuss the implications of this formulation for the development of strategies targeted towards the primary prevention of childhood obesity.

DWI Hyperintensity in the Fornix Fimbria on MRI in Children

BACKGROUND AND PURPOSE

The fornix-fimbria complex is mainly involved in emotions and memory. In brain MR imaging studies of young children, we have occasionally noted DWI hyperintensity in this region. The significance of this finding remains unclear. This study evaluated the DWI signal in the fornix-fimbria complex of children 0-2 years of age, including the frequency of signal hyperintensity and clinical context.

MATERIALS AND METHODS

Brain MR imaging of 714 children 0-2 years of age (mean, 11 months), performed between September 2018 and May 2021, was reviewed and evaluated for DWI signal changes in the fornix-fimbria. All children with available MR imaging studies including DWI were included. Children with poor image quality, poor visualization of the fornix-fimbria region, and missing medical data were excluded. Additional imaging findings were also evaluated. Demographic data were retrieved from the medical files. We compared the ADC values of the fimbria and fornix between children with and without signal changes. The unpaired 2-tailed Student t test and χ² test were used for statistical analysis.

RESULTS

DWI signal hyperintensity of the Fornix-fimbria complex was noted in 53 (7.4%) children (mean age, 10 months). Their mean ADC values were significantly lower than those of the children with normal DWI findings (P < .05). About half of the children had otherwise normal MR imaging findings. When detected, the most common abnormality was parenchymal volume loss (15%). The most common indication for imaging was seizures (26.5%).

CONCLUSIONS

DWI hyperintensity in the fornix-fimbria complex was detected in 7.4% of children 0-2 years of age. The etiology is not entirely clear, possibly reflecting a transient phenomenon.

White matter myelination during early infancy is linked to spatial gradients and myelin content at birth

Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.

The SACT Template: A Human Brain Diffusion Tensor Template for School-age Children

School-age children are in a specific development stage corresponding to juvenility, when the white matter of the brain experiences ongoing maturation. Diffusion-weighted magnetic resonance imaging (DWI), especially diffusion tensor imaging (DTI), is extensively used to characterize the maturation by assessing white matter properties in vivo. In the analysis of DWI data, spatial normalization is crucial for conducting inter-subject analyses or linking the individual space with the reference space. Using tensor-based registration with an appropriate diffusion tensor template presents high accuracy regarding spatial normalization. However, there is a lack of a standardized diffusion tensor template dedicated to school-age children with ongoing brain development. Here, we established the school-age children diffusion tensor (SACT) template by optimizing tensor reorientation on high-quality DTI data from a large sample of cognitively normal participants aged 6-12 years. With an age-balanced design, the SACT template represented the entire age range well by showing high similarity to the age-specific templates. Compared with the tensor template of adults, the SACT template revealed significantly higher spatial normalization accuracy and inter-subject coherence upon evaluation of subjects in two different datasets of school-age children. A practical application regarding the age associations with the normalized DTI-derived data was conducted to further compare the SACT template and the adult template. Although similar spatial patterns were found, the SACT template showed significant effects on the distributions of the statistical results, which may be related to the performance of spatial normalization. Looking forward, the SACT template could contribute to future studies of white matter development in both healthy and clinical populations. The SACT template is publicly available now ( https://figshare.com/articles/dataset/SACT_template/14071283 ).

Early Influences of Microbiota on White Matter Development in Germ-Free Piglets

Abnormalities in the prefrontal cortex (PFC), as well as the underlying white matter (WM) tracts, lie at the intersection of many neurodevelopmental disorders. The influence of microorganisms on brain development has recently been brought into the clinical and research spotlight as alterations in commensal microbiota are implicated in such disorders, including autism spectrum disorders, schizophrenia, depression, and anxiety via the gut-brain axis. In addition, gut dysbiosis is common in preterm birth patients who often display diffuse WM injury and delayed WM maturation in critical tracts including those within the PFC and corpus callosum. Microbial colonization of the gut aligns with ongoing postnatal processes of oligodendrogenesis and the peak of brain myelination in humans; however, the influence of microbiota on gyral WM development remains elusive. Here, we develop and validate a neonatal germ-free swine model to address these issues, as piglets share key similarities in WM volume, developmental trajectories, and distribution to humans. We find significant region-specific reductions, and sexually dimorphic trends, in WM volume, oligodendrogenesis, and mature oligodendrocyte numbers in germ-free piglets during a key postnatal epoch of myelination. Our findings indicate that microbiota plays a critical role in promoting WM development during early life when the brain is vulnerable to environmental insults that can result in an array of disabilities manifesting later in life.

Automated Brain Masking of Fetal Functional MRI with Open Data

Fetal resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a critical new approach for characterizing brain development before birth. Despite the rapid and widespread growth of this approach, at present, we lack neuroimaging processing pipelines suited to address the unique challenges inherent in this data type. Here, we solve the most challenging processing step, rapid and accurate isolation of the fetal brain from surrounding tissue across thousands of non-stationary 3D brain volumes. Leveraging our library of 1,241 manually traced fetal fMRI images from 207 fetuses, we trained a Convolutional Neural Network (CNN) that achieved excellent performance across two held-out test sets from separate scanners and populations. Furthermore, we unite the auto-masking model with additional fMRI preprocessing steps from existing software and provide insight into our adaptation of each step. This work represents an initial advancement towards a fully comprehensive, open-source workflow, with openly shared code and data, for fetal functional MRI data preprocessing.

Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies

The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging.

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The field of infant MRI is young with evolving standards.

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We address 20 questions that researchers commonly receive reviewers.

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These come from research ethics boards, grant, and manuscript reviewers.

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This article reflects the cumulative knowledge of experts in the FIT’NG community.

Distinguishing Tumor Recurrence From Radiation Necrosis in Treated Glioblastoma Using Multiparametric MRI

PURPOSE

The purpose of this study was to evaluate the diagnostic performance of single-parameter, unimodal and bimodal magnetic resonance imaging (MRI) in differentiating tumor recurrence (TR) from radiation necrosis (RN) in patients with glioblastoma (GBM) after treatment using diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), dynamic susceptibility contrast enhancement-perfusion weighted imaging (DSC-PWI), and proton magnetic resonance spectroscopy (¹H-MRS).

MATERIALS AND METHODS

Patients with histologically proven GBM who underwent surgical intervention followed by chemoradiotherapy and developed a new, progressively enhanced lesion on follow-up MRI were included in our study. Subsequently, DWI, DTI, DSC-PWI, and ¹H-MRS were performed. Then, these patients underwent a second surgical operation or follow-up MRI to prove TR or RN. MRI metrics include apparent diffusion coefficient (ADC) and relative ADC (rADC) values derived from DWI; fractional anisotropy (FA), axial diffusion coefficient (DA) and radial diffusion coefficient (DR) values derived from DTI; and relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) derived from DSC-PWI. Spectral metabolites such as choline (Cho), creatine (Cr), N-acetylaspartate (NAA), lactate (Lac), and lipids (Lip) were derived from MRS, and the ratios of these metabolites were calculated, including Cho/NAA, Cho/Cr, NAA/Cr, Lac/Cr, and Lip/Cr. These indices were compared between the TR group and RN group, and the receiver operating characteristic (ROC) curve was used to evaluate the performance in distinguishing TR from RN by using single-parameter, unimodal and bimodal MRI.

RESULTS

There were significant differences between the TR and RN groups in terms of ADC (p = 0.001), rADC (p < 0.001), FA (p = 0.001), DA (p = 0.003), DR (p = 0.003), rCBV (p < 0.001), rCBF (p < 0.001), Cho/NAA (p < 0.001), Lac/Cr (p < 0.001) and Lip/Cr (p < 0.001). ROC analysis suggested that rCBV, MRS, and DSC + MRS were the optimal single-parameter, unimodal, and bimodal MRI classifiers for distinguishing TR from RN, with AUC values of 0.909, 0.940, and 0.994, respectively.

CONCLUSION

The combination of parameters based on multiparametric MRI in the region of enhanced lesions is a valuable noninvasive tool for discriminating TR from RN.

The structural connectome in ADHD

Attention-deficit/hyperactivity disorder (ADHD) has been conceptualized as a brain dysconnectivity disorder. In the past decade, noninvasive diffusion magnetic resonance imaging (dMRI) studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome, and that these alterations are associated with core symptoms and cognitive deficits in patients. This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-, tractography-, and network-based perspectives. Voxel- and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts, the corpus callosum, the corticospinal tracts, and the cingulum bundle in patients with ADHD. Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes. The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification. These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation. However, given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations, these ADHD-related white matter alterations are still far from informing clinical practice. Future studies with larger and more homogeneous samples are needed to validate the consistency of current results; advanced dMRI techniques can help to generate much more precise estimation of white matter pathways and assure specific fiber configurations; and finally, dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.