Background
Intrauterine growth restriction is associated with short- and long-term neurodevelopmental problems. Structural brain changes underlying these alterations have been described with the use of different magnetic resonance–based methods that include changes in whole structural brain networks. However, evaluation of specific brain circuits and its correlation with related functions has not been investigated in intrauterine growth restriction.
Objectives
In this study, we aimed to investigate differences in tractography-related metrics in cortico-striatal-thalamic and motor networks in intrauterine growth restricted children and whether these parameters were related with their specific function in order to explore its potential use as an imaging biomarker of altered neurodevelopment.
Methods
We included a group of 24 intrauterine growth restriction subjects and 27 control subjects that were scanned at 1 year old; we acquired T1-weighted and 30 directions diffusion magnetic resonance images. Each subject brain was segmented in 93 regions with the use of anatomical automatic labeling atlas, and deterministic tractography was performed. Brain regions included in motor and cortico-striatal-thalamic networks were defined based in functional and anatomic criteria. Within the streamlines that resulted from the whole brain tractography, those belonging to each specific circuit were selected and tractography-related metrics that included number of streamlines, fractional anisotropy, and integrity were calculated for each network. We evaluated differences between both groups and further explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales from Bayley Scale at 2 years of age.
Results
Reduced fractional anisotropy (cortico-striatal-thalamic, 0.319 ± 0.018 vs 0.315 ± 0.015; P = .010; motor, 0.322 ± 0.019 vs 0.319 ± 0.020; P = .019) and integrity cortico-striatal-thalamic (0.407 ± 0.040 vs 0.399 ± 0.034; P = .018; motor, 0.417 ± 0.044 vs 0.409 ± 0.046; P = .016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877).
Conclusions
These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases.
Intrauterine growth restriction (IUGR) is a prevalent condition that affects 5-10% of all pregnancies in developed countries and is associated with short- and long-term neurodevelopmental problems, which include motor and cognitive delay. IUGR has been proposed, together with prematurity, as the cause of one-quarter of cases of special educational need because of sensory, motor, and intellectual disabilities. Moreover, IUGR has been proposed as a risk factor for the development of autism spectrum disorders (ASD) and attention deficit hyperactivity disorder (ADHD). Structural brain changes underlying altered neurodevelopment have been described with the use of magnetic resonance imaging (MRI), starting in prenatal period and persisting at neonatal and early infancy and at adolescence. However, we are still far from identifying those individuals who are at high risk of abnormal neurodevelopment, who are the potential target for early therapeutic interventions. Being a crucial clinical and experimental need for the development of imaging biomarkers, it is extremely important to better characterize the brain reorganization underlying neurodevelopmental and cognitive dysfunctions in IUGR.
Several brain regions have been demonstrated to be affected by IUGR, including both gray and white matter (WM). Specifically, not only global reduction of WM volume but also changes in specific regions such as thinning of corpus callosum have been reported, which are part of these changes already present in prenatal period. Recently, diffusion MRI, which provides indirect information about brain microstructure, has been used to detect changes that occur in IUGR and other fetal conditions that are associated with reduced brain oxygen supply, such as cardiac defects. Aside from assessing changes in diffusivity parameters, diffusion MRI allows us to reconstruct the trajectory of the WM tracts within the brain by means of tractography, which, combined with brain segmentation, allows is to build brain networks. In this line, structural brain networks of 1-year-old IUGR infants have been reported to have reduced level of organization together with a pattern of regional network features that is associated with latter neurodevelopmental outcomes. However, to the best of our knowledge, the evaluation of specific brain circuits and their correlation with related functions has not been investigated in IUGR. Tractography-related metrics can be obtained to estimate features along the WM pathways among brain regions that regulate specific brain functions. This approach has been used to identify changes in diseases of neurodevelopment such as ADHD, ASD, and periventricular leukomalacia.
Several metrics have been proposed to be used to describe WM characteristics within specific networks, such as number of fibers, fractional anisotropy (FA), and radial diffusivity. Recently, integrity (INT) has been proposed as a parameter to further evaluate intrinsic properties of WM tracts, which considers both anisotropy and radial diffusivity, being more sensitive to a lack of linear diffusion into the tissue. The application of tractography-related metrics to IUGR could provide additional relevant information for a better understanding of the problem and its consequences, because it could bring straightforward information in relation to the identification of specific disorders in IUGR population.
In the present study, we investigated tractography-related metrics in cortico-striatal-thalamic and motor networks that were obtained from a group of 1-year-old infants with and without IUGR. We computed the number of streamlines that were obtained by tractography, mean FA, and INT of each network and evaluated differences between both groups. We also explored the correlation of these parameters with the results of socioemotional, cognitive, and motor scales of Bayley’s test at 2 years of age.
Material and Methods
Subjects
In this study, we included part of prospective cohort of IUGR that was included in a previous study of our group. From an original sample size of 83 fetuses (42 fetuses with IUGR and 41 control subjects) who were recruited consecutively, we excluded 5 control subjects who were born at <28 weeks of pregnancy. We also excluded 8 fetuses with IUGR and in 5 control subjects based on structural MRI findings (4 increased cisterna magna, 7 ventricular dilations, and 2 WM lesions). In addition, 10 fetuses with IUGR and 4 control subjects did not pass quality criteria because of motion artifacts that hampered proper tractography reconstruction, comprising a final sample of 24 fetuses with IUGR and 27 control subjects. Following well-established criteria, IUGR was defined as a fetal with an estimated weight below 10th percentile confirmed at birth, both according to local reference standards. Control subjects were defined as fetuses with fetal estimated weight between the 10th and 90th customized percentiles according to local reference confirmed at birth. Pregnancies were dated according to the first-trimester crown-rump length measurements. Infants with chromosomal, genetic, or structural defects and signs of intrauterine infection or neonatal early onset sepsis were excluded from this study. Neonatal data that were recorded prospectively included gestational age (GA), birthweight, gender, Apgar score at 5 minutes, umbilical artery pH, and neonatal complications. Maternal education was recorded as low, intermediate, or high educational level. Maternal smoking status during pregnancy and breastfeeding were also recorded. Growth parameters (weight, length, body mass index, and head circumference) were recorded at 12 months and were normalized for local standards. The study protocol was approved by the local Ethics Committee, and written informed consent was obtained from the parents or legal guardians of all participants (2008/4422).
Neurodevelopmental assessment
Neurodevelopmental outcome was assessed at 21 months of corrected age (±3 months) with the Bayley Scale for Infant and Toddler Development, Third edition (BSID-III), which evaluates 5 distinct scales of development. For this study, we considered results in cognitive, socioemotional behavior, and motor scales. The scales have scores with a mean of 100 and standard deviation of 15. All developmental examinations were performed by a blinded single trained psychologist examiner with previous experience with the BSID-III.
MRI data acquisition
Children were scanned at 12 ± 2 months during natural sleep with the use of a whole body magnetic resonance scanner (TIM TRIO 3.0 T; Siemens, Munich, Germany). High-resolution structural T1 and T2 weighted images and 30 diffusion volumes were acquired as previously described. Structural T1 and T2 weighted images were evaluated to exclude brain abnormalities. All acquired MRI structural and diffusion images were inspected visually for apparent or aberrant artifacts, and subjects were excluded accordingly.
MRI processing
The method performed to process MRI has been described previously. Briefly, the acquired images of each subject were skull-stripped, segmented into WM, gray matter, and cerebrospinal fluid with the use of specific probability maps. Each subject brain was parcellated regionally in the native space with a version of the anatomical automatic labeling atlas of 116 regions, adapted to 1-year-old infants. Cerebellar regions were merged into vermis and right and left cerebellum, which resulted in a total of 93 regions per subject. Whole-brain deterministic tractography was performed for each subject with a diffusion tensor imaging–based fiber tracking algorithm with log-Euclidean metrics (available on MedINRIA 1, http://www-sop.inria.fr/asclepios/software/MedINRIA/ ). A FA threshold of 0.2 was chosen as a stopping criterion for the tractography algorithm, and streamlines were confined to the WM mask.
Tractography metrics
Definition of circuits of interest
In this study, 2 specific brain circuits were studied: motor and cortico-striatal-thalamic (CST). Motor network was defined as those fibers that start at the motor cortex (primary motor cortex or supplementary motor area) and pass through 1 of the following regions: postcentral gyrus, superior parietal gyrus, cerebellum, nucleus pallidus, caudate nucleus, putamen nucleus, and thalami. CST network was defined as those fibers that start in the frontal cortex (superior frontal gyrus, medial superior frontal gyrus, middle frontal gyrus, and inferior frontal gyrus opercular and triangular part) and pass through the striatum or nucleus pallidus and the thalami. Within the streamlines that result from the whole brain tractography, those belonging to each specific circuit were selected and described by a set of parameters described later ( Figure 1 ; Supplemental Table ).
Tractography metrics
Three different measures were considered for the quantitative analysis of brain circuits previously defined: number of streamlines belonging to each circuit, FA, and INT.
The number of streamlines was obtained by a count of those that belonged to the defined circuits. FA describes the diffusion anisotropy, which has been related with the presence, organization, and/or maturation of fibers. The mean FA along each streamline in the circuit was computed, and the resulting values were averaged on the whole circuit to obtain a single value. INT was defined as the relationship between FA and radial diffusivity, being higher values related to a high level of myelination, and being more sensitive to a lack of linear diffusion into the tissue. INT was computed in each streamline and averaged in all the streamlines of the circuit as:
where DradDrad
D r a d
is the radial diffusivity Drad=12(λ2+λ3)
D r a d = 1 2 ( λ 2 + λ 3 )
, being λ 2 y λ 3 the second and third eigenvalues of the matrix that represent the diffusion tensor.
Statistical analysis
Statistical comparisons among groups were performed by general linear models with gender, maternal education level, smoking during pregnancy, and breastfeeding as cofactors and GA at delivery as a covariate. When tractography-related metrics were analyzed, brain volume was added as covariate. For categoric variables, chi-squared test was used. Partial correlations between tractography metrics and BSID-III results were also performed with gender, GA at delivery, maternal education level, smoking during pregnancy, breastfeeding, and brain volume as controlling variables. Because of the exploratory nature of this analysis, significance was declared at a probability of <.05 (uncorrected). The SPSS software package (vrsion19.0; SPSS Inc, Chicago, IL) was used for the statistical analyses.
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