Multivariate longitudinal shape analysis of human lateral ventricles during the first twenty-four months of life

Infant and Child MRI: A Review of Scanning Procedures

Magnetic resonance imaging (MRI) is a safe method to examine human brain. However, a typical MR scan is very sensitive to motion, and it requires the subject to lie still during the acquisition, which is a major challenge for pediatric scans. Consequently, in a clinical setting, sedation or general anesthesia is often used. In the research setting including healthy subjects anesthetics are not recommended for ethical reasons and potential longer-term harm. Here we review the methods used to prepare a child for an MRI scan, but also on the techniques and tools used during the scanning to enable a successful scan. Additionally, we critically evaluate how studies have reported the scanning procedure and success of scanning. We searched articles based on special subject headings from PubMed and identified 86 studies using brain MRI in healthy subjects between 0 and 6 years of age. Scan preparations expectedly depended on subject's age; infants and young children were scanned asleep after feeding and swaddling and older children were scanned awake. Comparing the efficiency of different procedures was difficult because of the heterogeneous reporting of the used methods and the success rates. Based on this review, we recommend more detailed reporting of scanning procedure to help find out which are the factors affecting the success of scanning. In the long term, this could help the research field to get high quality data, but also the clinical field to reduce the use of anesthetics. Finally, we introduce the protocol used in scanning 2 to 5-week-old infants in the FinnBrain Birth Cohort Study, and tips for calming neonates during the scans.

Measurement of lateral ventricle volume of normal infant based on magnetic resonance imaging

Background

Many neurophysiological diseases during infancy stage are associated with the morphology and size of the lateral ventricle. This research aims to measure the normal value range of lateral ventricle volume of normal infant and thus provide basic data for clinical treatment.

Method

By retrospective analysis of magnetic resonance inspection (MRI) cranial image of 165 infants in the Department of Pediatric Neurosurgery, Beijing Tiantan Hospital, the infants were divided into four groups according to their age, including the first group (1~3 month, n = 12), the second group (4~6 month, n = 33), the third group (7~9 month, n = 51), and the fourth group (10~12 month, n = 69). On Neurosoft image workstation, it can measure the sectional area of the lateral ventricle volume at each layer of axis T2W image and calculate the lateral ventricle volume using the Cavalieri method. Moreover, the correlations between lateral ventricle volume and gender, side difference, and month age were analyzed.

Results

95% confidence interval of total bilateral ventricle volume of normal infant: 11920.22~14,266.28 mm³ for male infant and 9922.22~12,263.17 mm³ for female infant; 95% confidence interval of left side ventricle volume: 6254.72~7546.94 mm³ for male infant and 5206.03~6479.99 mm³ for female infant; 95% confidence interval of right side ventricle volume: 5041.56~6743.29 mm³ for male infant and 4695.00~5804.40 mm³ for female infant. The lateral ventricle volume of the male infant was normally larger than that of the female infant (p < 0.05). For both male and female infants, the left side ventricle volume was larger than the right ventricle volume (p < 0.01). There was no significant difference in lateral ventricle volume between infants over 3 months old.

Conclusion

The normal value range of lateral ventricle volume of the infant can be obtained via referring MRI image. The lateral ventricle volume of infant varies upon gender and ventricle side.

Visualization of the periventricular Virchow-Robin spaces with ependymal openings

PURPOSE

The morphological relationships between the periventricular Virchow-Robin spaces (VRSs) and cerebral ventricles have been poorly documented. The present study aimed to explore the issue using magnetic resonance imaging.

METHODS

A total of 211 patients were included in this study. T2-weighted and constructive interference in steady state (CISS) sequences were performed in thin-sliced, coronal sections.

RESULTS

On T2-weighted sequence, the periventricular VRSs with ependymal openings were identified in 34% of 139 subjects. All the openings were located in the lateral wall of the anterior horn. In CISS sequences, such VRSs were found in 39% of 72 subjects. The mean age was significantly higher in the population with such VRSs compared to those without VRSs (p = 0.0047). Of the 58 periventricular VRSs with ependymal openings identified on T2-weighted images, 16% were located in the upper, 36% in the middle, and 48% in the lower part of the lateral wall. Of the 38 such VRSs identified on CISS images, 32% were located in the upper, 24% in the middle, and 42% in the lower part of the lateral wall, and 3% in the upper part of the medial wall.

CONCLUSIONS

The ependymal openings of the periventricular VRSs may be centered in the lateral wall of the anterior horn. The coronal CISS sequence can sensitively delineate the VRSs with ependymal openings.

Imaging structural and functional brain development in early childhood

In humans, the period from term birth to ∼2 years of age is characterized by rapid and dynamic brain development and plays an important role in cognitive development and risk of disorders such as autism and schizophrenia. Recent imaging studies have begun to delineate the growth trajectories of brain structure and function in the first years after birth and their relationship to cognition and risk of neuropsychiatric disorders. This Review discusses the development of grey and white matter and structural and functional networks, as well as genetic and environmental influences on early-childhood brain development. We also discuss initial evidence regarding the usefulness of early imaging biomarkers for predicting cognitive outcomes and risk of neuropsychiatric disorders.

Biomechanical Analysis of Normal Brain Development during the First Year of Life Using Finite Strain Theory

The first year of life is the most critical time period for structural and functional development of the human brain. Combining longitudinal MR imaging and finite strain theory, this study aimed to provide new insights into normal brain development through a biomechanical framework. Thirty-three normal infants were longitudinally imaged using MRI from 2 weeks to 1 year of age. Voxel-wise Jacobian determinant was estimated to elucidate volumetric changes while Lagrange strains (both normal and shear strains) were measured to reveal directional growth information every 3 months during the first year of life. Directional normal strain maps revealed that, during the first 6 months, the growth pattern of gray matter is anisotropic and spatially inhomogeneous with higher left-right stretch around the temporal lobe and interhemispheric fissure, anterior-posterior stretch in the frontal and occipital lobes, and superior-inferior stretch in right inferior occipital and right inferior temporal gyri. In contrast, anterior lateral ventricles and insula showed an isotropic stretch pattern. Volumetric and directional growth rates were linearly decreased with age for most of the cortical regions. Our results revealed anisotropic and inhomogeneous brain growth patterns of the human brain during the first year of life using longitudinal MRI and a biomechanical framework.

STGP: Spatio-temporal Gaussian process models for longitudinal neuroimaging data

Longitudinal neuroimaging data plays an important role in mapping the neural developmental profile of major neuropsychiatric and neurodegenerative disorders and normal brain. The development of such developmental maps is critical for the prevention, diagnosis, and treatment of many brain-related diseases. The aim of this paper is to develop a spatio-temporal Gaussian process (STGP) framework to accurately delineate the developmental trajectories of brain structure and function, while achieving better prediction by explicitly incorporating the spatial and temporal features of longitudinal neuroimaging data. Our STGP integrates a functional principal component model (FPCA) and a partition parametric space-time covariance model to capture the medium-to-large and small-to-medium spatio-temporal dependence structures, respectively. We develop a three-stage efficient estimation procedure as well as a predictive method based on a kriging technique. Two key novelties of STGP are that it can efficiently use a small number of parameters to capture complex non-stationary and non-separable spatio-temporal dependence structures and that it can accurately predict spatio-temporal changes. We illustrate STGP using simulated data sets and two real data analyses including longitudinal positron emission tomography data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and longitudinal lateral ventricle surface data from a longitudinal study of early brain development.