Rapid and reliable tract-based spatial statistics pipeline for diffusion tensor imaging in the neonatal brain: Applications to the white matter development and lesions

Children with autism spectrum disorder present glymphatic system dysfunction evidenced by diffusion tensor imaging along the perivascular space

This study used diffusion tensor imaging (DTI) along the perivascular space (DTI-ALPS) to assess glymphatic system function in autism spectrum disorder (ASD) compared to healthy controls. Patients with ASD may have glymphatic system dysfunction, which is related to age. We retrospectively included 30 children with ASD and 25 healthy controls in this study. 3T magnetic resonance imaging scanner was used to perform DTI magnetic resonance imaging on all participants, and the DTI-ALPS index was calculated from the DTI data. Additionally, we evaluated how the DTI-ALPS index differed between the 2 groups. Moreover, we examined the relationships between the bilateral DTI-ALPS index and the age of the participants. The DTI-ALPS index considerably differed between groups. In the left index (1.02 ± 0.12 vs. 1.27 ± 0.25, P < .001) and in the right index (1.03 ± 0.12 vs. 1.32 ± 0.20, P < .001), the DTI-ALPS in ASD patients was significantly lower than that in healthy controls. Furthermore, the DTI-ALPS index was strongly and positively associated with age. In patients with ASD, there is a glymphatic system dysfunction. This is intimately correlated to age. Our findings suggest the importance of the DTI-ALPS approach in assessing the function of the glymphatic system in ASD.

Mapping white matter maturational processes and degrees on neonates by diffusion kurtosis imaging with multiparametric analysis

White matter maturation has been characterized by diffusion tensor (DT) metrics. However, maturational processes and degrees are not fully investigated due to limitations of univariate approaches and limited specificity/sensitivity. Diffusion kurtosis imaging (DKI) provides kurtosis tensor (KT) and white matter tract integrity (WMTI) metrics, besides DT metrics. Therefore, we tried to investigate performances of DKI with the multiparametric analysis in characterizing white matter maturation. Developmental changes in metrics were investigated by using tract-based spatial statistics and the region of interest analysis on 50 neonates with postmenstrual age (PMA) from 37.43 to 43.57 weeks. Changes in metrics were combined into various patterns to reveal different maturational processes. Mahalanobis distance based on DT metrics (D_M,DT ) and that combing DT and KT metrics (D_M,DT-KT ) were computed, separately. Performances of D_M,DT-KT and D_M,DT were compared in revealing correlations with PMA and the neurobehavioral score. Compared with DT metrics, WMTI metrics demonstrated additional changing patterns. Furthermore, variations of D_M,DT-KT across regions were in agreement with the maturational sequence. Additionally, D_M,DT-KT demonstrated stronger negative correlations with PMA and the neurobehavioral score in more regions than D_M,DT . Results suggest that DKI with the multiparametric analysis benefits the understanding of white matter maturational processes and degrees on neonates.

Prediction of Communication Impairment in Children With Bilateral Cerebral Palsy Using Multivariate Lesion- and Connectome-Based Approaches: Protocol for a Multicenter Prospective Cohort Study

BACKGROUND

Bilateral cerebral palsy (BCP) is the most common type of CP in children and is often accompanied by different degrees of communication impairment. Several studies have attempted to identify children at high risk for communication impairment. However, most prediction factors are qualitative and subjective and may be influenced by rater bias. Individualized objective diagnostic and/or prediction methods are still lacking, and an effective method is urgently needed to guide clinical diagnosis and treatment. The aim of this study is to develop and validate an objective, individual-based model for the prediction of communication impairment in children with BCP by the time they enter school.

METHODS

A multicenter prospective cohort study will be conducted in four Chinese hospitals. A total of 178 children with BCP will undergo advanced brain magnetic resonance imaging (MRI) at baseline (corrected age, before the age of 2 years). At school entry, communication performance will be assessed by a communication function classification system (CFCS). Three-quarters of children with BCP will be allocated as a training cohort, whereas the remaining children will be allocated as a test cohort. Multivariate lesion- and connectome-based approaches, which have shown good predictive ability of language performance in stroke patients, will be applied to extract features from MR images for each child with BCP. Multiple machine learning models using extracted features to predict communication impairment for each child with BCP will be constructed using data from the training cohort and externally validated using data from the test cohort. Prediction accuracy across models in the test cohort will be statistically compared.

DISCUSSION

The findings of the study may lead to the development of several translational tools that can individually predict communication impairment in children newly diagnosed with BCP to ensure that these children receive early, targeted therapeutic intervention before they begin school.

TRIAL REGISTRATION

The study has been registered with the Chinese Clinical Trial Registry (ChiCTR2100049497).

Structural network performance for early diagnosis of spastic cerebral palsy in periventricular white matter injury

Periventricular white matter injury (PWMI) is a common cause of spastic cerebral palsy (SCP). Diffusion tensor imaging (DTI) shows high sensitivity but moderate specificity for predicting SCP. The limited specificity may be due to the diverse and extensive brain injuries seen in infants with PWMI. We enrolled 72 infants with corrected age from 6 to 18 months in 3 groups: PWMI with SCP (n = 20), non-CP PWMI (n = 19), and control (n = 33) groups. We compared DTI-based brain network properties among the three groups and evaluated the diagnostic performance of brain network properties for SCP in PWMI infants. Our results show abnormal global parameters (reduced global and local efficiency, and increased shortest path length), and local parameters (reduced node efficiency) in the PWMI with SCP group. On logistic regression, the combined node efficiency of the bilateral precentral gyrus and right middle frontal gyrus had a high sensitivity (90%) and specificity (95%) for differentiating PWMI with SCP from non-CP PWMI, and significantly correlated with the Gross Motor Function Classification System scores. This study confirms that DTI-based brain network has great diagnostic performance for SCP in PWMI infants, and the combined node efficiency improves the diagnostic accuracy.

Exploring Variances of White Matter Integrity and the Glymphatic System in Simple Febrile Seizures and Epilepsy

Background: Simple febrile seizures (SFS) and epilepsy are common seizures in childhood. However, the mechanism underlying SFS is uncertain, and the presence of obvious variances in white matter (WM) integrity and glymphatic function between SFS and epilepsy remain unclear. Therefore, this study aimed to investigate the differences in WM integrity and glymphatic function between SFS and epilepsy.

Material and Methods: We retrospectively included 26 children with SFS, 33 children with epilepsy, and 28 controls aged 6–60 months who underwent magnetic resonance imaging (MRI). Tract-based spatial statistics (TBSS) were used to compare the diffusion tensor imaging (DTI) metrics of WM among the above-mentioned groups. T2-weighted imaging (T2WI) was used to segment the visible Virchow-Robin space (VRS) through a custom-designed automated method. VRS counts and volume were quantified and compared among the SFS, epilepsy, and control groups. Correlations of the VRS metrics and seizure duration and VRS metrics and the time interval between seizure onset and MRI scan were also investigated.

Results: In comparison with controls, children with SFS showed no significant changes in fractional anisotropy (FA), axial diffusivity (AD), or radial diffusivity (RD) in the WM (P > 0.05). Decreased FA, unchanged AD, and increased RD were observed in the epilepsy group in comparison with the SFS and control groups (P < 0.05). Meanwhile, VRS counts were higher in the SFS and epilepsy groups than in the control group (VRS_SFS, 442.42 ± 74.58, VRS_epilepsy, 629.94 ± 106.55, VRS_control, 354.14 ± 106.58; P < 0.001), and similar results were found for VRS volume (VRS_SFS, 6,228.18 ± 570.74 mm³, VRS_epilepsy, 9,684.84 ± 7,292.66mm³, VRS_control, 4,007.22 ± 118.86 mm³; P < 0.001). However, VRS metrics were lower in the SFS group than in the epilepsy group (P < 0.001). In both SFS and epilepsy, VRS metrics positively correlated with seizure duration and negatively correlated with the course after seizure onset.

Conclusion: SFS may not be associated with WM microstructural disruption; however, epilepsy is related to WM alterations. Seizures are associated with glymphatic dysfunction in either SFS or epilepsy.

Inter-site harmonization based on dual generative adversarial networks for diffusion tensor imaging: application to neonatal white matter development

Background

Site-specific variations are challenges for pooling analyses in multi-center studies. This work aims to propose an inter-site harmonization method based on dual generative adversarial networks (GANs) for diffusion tensor imaging (DTI) derived metrics on neonatal brains.

Results

DTI-derived metrics (fractional anisotropy, FA; mean diffusivity, MD) are obtained on age-matched neonates without magnetic resonance imaging (MRI) abnormalities: 42 neonates from site 1 and 42 neonates from site 2. Significant inter-site differences of FA can be observed. The proposed harmonization approach and three conventional methods (the global-wise scaling, the voxel-wise scaling, and the ComBat) are performed on DTI-derived metrics from two sites. During the tract-based spatial statistics, inter-site differences can be removed by the proposed dual GANs method, the voxel-wise scaling, and the ComBat. Among these methods, the proposed method holds the lowest median values in absolute errors and root mean square errors. During the pooling analysis of two sites, Pearson correlation coefficients between FA and the postmenstrual age after harmonization are larger than those before harmonization. The effect sizes (Cohen’s d between males and females) are also maintained by the harmonization procedure.

Conclusions

The proposed dual GANs-based harmonization method is effective to harmonize neonatal DTI-derived metrics from different sites. Results in this study further suggest that the GANs-based harmonization is a feasible pre-processing method for pooling analyses in multi-center studies.

Treatment response prediction of rehabilitation program in children with cerebral palsy using radiomics strategy: protocol for a multicenter prospective cohort study in west China

Background

Cerebral palsy (CP) is a major cause of chronic childhood disability worldwide, causing activity limitation as well as impairments in sensation, cognition, and communication. Leveraging biomarkers to establish individualized predictions of future treatment responses will be of great value. We aim to develop and validate a model that can be used to predict the individualized treatment response in Children with CP.

Methods

A multicenter prospective cohort study will be conducted in 4 hospitals in west China. One hundred and thirty children with CP will be recruited and undergo clinical assessment using the Peabody Developmental Motor Scales, Manual Ability Classification System (MACS), Hand Assessment for Infants (HAI), Assisting Hand Assessment (AHA), and Gross Motor Function Classification System (GMFCS). The data collected will include MRI image, clinical status, and socioeconomic status. The clinical information and MRI features extracted using radiomics strategy will be combined for exploratory analysis. The accuracy, sensitivity, and specificity of the model will be assessed using multiple modeling methodologies. Internal and external validation will be used to evaluate the performance of the radiomics model.

Discussion

We hypothesized that the findings from this study could provide a critical step towards the prediction of treatment response in children with CP, which could also complement other biomarkers in the development of precision medicine approaches for this severe disorder.

Trial registration

The study was registered with clinicaltrials.gov (NCT02979743).

Associations of gestational age and birth anthropometric indicators with brain white matter maturation in full-term neonates

Newborn assessments, including gestational age (GA) and anthropometric measurements (birth weight, crown-heel length, head circumference) are routinely performed in pediatric settings, being used as important indicators in assessing neonatal development. Close associations of these birth indicators with later cognitive abilities were also reported. However, specific associations of these indicators with white matter (WM) development during the neonatal period remain unclear, as well as the extent to which they influence WM maturation. To address this issue, 51 full-term neonates (GA range, 37-42 weeks) with no abnormalities on MRI were retrospectively recruited. Specific correlations between birth indicators and WM maturation, quantified by diffusion tensor imaging (DTI)-metrics (fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity), were identified by using DTI tract-based spatial statistics and automated fiber-tract quantification. Our findings suggest that (a) higher GA, birth weight, and crown-heel length may indicate greater WM maturation in full-term neonates, while head circumference presented weak correlation with WM maturation during early newborn period; (b) among the four indicators examined, GA was the one most associated with WM maturation. We believe that this study advances our knowledge of specific correlations between birth indicators and neonatal brain development and provides a valuable reference for future neonatal studies.

Test-retest reliability of Diffusion Tensor Imaging metrics in neonates

Diffusion tensor imaging (DTI) has been widely used in children and adults to study the microstructural features of the brain. Its use in neonate brains has been limited. Neonate brains are almost completely unmyelinated, and this together with the tendency for babies to move during a scanning session may affect the reliability of the measurements. Here we divided a 96 direction acquisition into three segments, and analysed the intra scan test-retest reliability for pairs of segments. Each segment was subjected to a rigorous quality control, and from the surviving data we chose 25 diffusion encoding directions from each segment, and assessed the pairwise reliability of the most common DTI metrics. This pairwise reliability was assessed for data from 86 infants. We used tract-based spatial statistics (TBSS), voxelwise and ROI analysis schemes, to see potential differential effects of analysis strategy and post processing on the obtained DTI metrics. We found that intra class correlation coefficient (ICC) values were generally high (ICC > 0.80). Residual motion in the data, after quality control, was not found to associate with the diffusion metrics. The results indicate that DTI metrics from neonate data can be reliable, even at relatively low angular resolution that are common for neonate scans. The results lend confidence to the use of neonate DTI data in cross sectional and longitudinal analyses in brain white matter skeleton. Future studies should assess the reliability of fiber tracking techniques in neonate data.

Prediction of adverse motor outcome for neonates with punctate white matter lesions by MRI images using radiomics strategy: protocol for a prospective cohort multicentre study

INTRODUCTION

Punctate white matter lesions (PWML) are prevalent white matter disease in preterm neonates, and may cause motor disorders and even cerebral palsy. However, precise individual-based diagnosis of lesions that result in an adverse motor outcome remains unclear, and an effective method is urgently needed to guide clinical diagnosis and treatment. Advanced radiomics for multiple modalities data can provide a possible look for biomarkers and determine prognosis quantitatively. The study aims to develop and validate a model for prediction of adverse motor outcomes at a corrected age (CA) of 24 months in neonates with PWML.

METHODS AND ANALYSIS

A prospective cohort multicentre study will be conducted in 11 Chinese hospitals. A total of 394 neonates with PWML confirmed by MRI will undergo a clinical assessment (modified Neonatal Behavioural Assessment Scale). At a CA of 18 months, the motor function will be assessed by Bayley Scales of Infant and Toddler Development-III (Bayley-III). Mild-to-severe motor impairments will be confirmed using the Bayley-III and Gross Motor Function Classification System at a CA of 24 months. During the data collection, the perinatal and clinical information will also be recorded. According to the radiomics strategy, the extracted imaging features and clinical information will be combined for exploratory analysis. After using multiple-modelling methodology, the accuracy, sensitivity and specificity will be computed. Internal and external validations will be used to evaluate the performance of the radiomics model.

ETHICS AND DISSEMINATION

This study has been approved by the institutional review board of The First Affiliated Hospital of Xi'an Jiaotong University (XJTU1AF2015LSK-172). All parents of eligible participants will be provided with a detailed explanation of the study and written consent will be obtained. The results of this study will be published in peer-reviewed journals and presented at local, national and international conferences.

TRIAL REGISTRATION NUMBER

NCT02637817; Pre-results.

Baby brain atlases

The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed.

Characterization of Extensive Microstructural Variations Associated with Punctate White Matter Lesions in Preterm Neonates

BACKGROUND AND PURPOSE

Punctate white matter lesions are common in preterm neonates. Neurodevelopmental outcomes of the neonates are related to the degree of extension. This study aimed to characterize the extent of microstructural variations for different punctate white matter lesion grades.

MATERIALS AND METHODS

Preterm neonates with punctate white matter lesions were divided into 3 grades (from mild to severe: grades I-III). DTI-derived fractional anisotropy, axial diffusivity, and radial diffusivity between patients with punctate white matter lesions and controls were compared with Tract-Based Spatial Statistics and tract-quantification methods.

RESULTS

Thirty-three preterm neonates with punctate white matter lesions and 33 matched controls were enrolled. There were 15, 9, and 9 patients, respectively, in grades I, II, and III. Punctate white matter lesions were mainly located in white matter adjacent to the lateral ventricles, especially regions lateral to the trigone, posterior horns, and centrum semiovale and/or corona radiata. Extensive microstructural changes were observed in neonates with grade III punctate white matter lesions, while no significant changes in DTI metrics were found for grades I and II. A pattern of increased axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy was found in regions adjacent to punctate white matter lesion sites seen on T1WI and T2WI. Unchanged axial diffusivity, increased radial diffusivity, and reduced/unchanged fractional anisotropy were observed in regions distant from punctate white matter lesion sites.

CONCLUSIONS

White matter microstructural variations were different across punctate white matter lesion grades. Extensive change patterns varied according to the distance to the lesion sites in neonates with severe punctate white matter lesions. These findings may help in determining the outcomes of punctate white matter lesions and selecting treatment strategies.