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Spatial and functional gradients of development have been described for the maturation of cerebral gray and white matter using histological and radiological approaches. We evaluated these patterns in very preterm (VPT) infants using diffusion tensor imaging. Data were obtained from 3 groups: 1) 22 VPT infants without white matter injury (WMI), of whom all had serial MRI studies during the neonatal period, 2) 19 VPT infants with WMI, of whom 3 had serial MRI studies and 3) 12 healthy, term-born infants. Regions of interest were placed in the cortical gray and adjacent white matter in primary motor, primary visual, visual association, and prefrontal regions. From the MRI data at term-equivalent postmenstrual age, differences in mean diffusivity were found in all areas between VPT infants with WMI and the other 2 groups. In contrast, minimal differences in fractional anisotropy were found between the 3 groups. These findings suggest that cortical maturation is delayed in VPT infants with WMI when compared with term control infants and VPT infants without WMI. From the serial MRI data from VPT infants, synchronous development between gray and white matter was evident in all areas and all groups, with maturation in primary motor and sensory regions preceding that of association areas. This finding highlights the regionally varying but locally synchronous nature of the development of cortical gray matter and its adjacent white matter.
Spatial and functional gradients in neuronal genesis and differentiation within the developing cortex have been well established. Cortex near the insula matures relatively early, with maturation rates decreasing as one moves farther from the insula (Sidman and Rakic 1982). Further, a number of studies demonstrate that maturation rates are also related to local function, with primary motor and sensory cortex differentiating prior to cortical association areas (Flechsig Of Leipsic 1901; Brodmann 1909; Conel 1939a, 1939b; Miller et al. 2012; Elston and Fujita 2014). Alternatively, the timing and sequence of white matter development is typically described in terms of brain region rather than function (Yakovlev and Lecours 1967; Brody et al. 1987; Kinney et al. 1988; Kizildag et al. 2005), though it has long been recognized that the corticospinal tracts and optic radiations myelinate early (Yakovlev and Lecours 1967). Myelination begins in the posterior limb of the internal capsule and optic radiations, progressing outward from the central sulcus toward the poles, with posterior sites preceding frontotemporal locations (Kinney et al. 1988). While these descriptions of regional development for white and gray matter do not seem to have a strong correspondence, it is plausible that myelination of axonal tracts occurs in synchrony with differentiation of associated cortical areas.
Microstructural development within both gray and white matter has been investigated using diffusion tensor imaging (DTI), a magnetic resonance imaging (MRI) technique that is based upon water displacements in tissue. Diffusion anisotropy reflects the spatial variation of these displacements. For example, high anisotropy is present in white matter (where cellular processes are locally ordered on a submillimeter scale) because water displacements are greater when measured parallel to the longitudinal axis of axons than transverse to them (Zhang et al. 2003; Deipolyi et al. 2005; Kroenke et al. 2005, 2007, 2009). For developing white matter, the early stages of maturation—the premyelinating state—is associated with a relatively modest but detectable increase in anisotropy and reduction in mean diffusivity (MD) related to reduced transverse water displacements (Wimberger et al. 1995). Subsequent maturation of oligodendrocytes and myelin formation lead to larger increases in anisotropy. However, not all white matter areas mature at the same rate, and early-maturing white matter areas that show an early rise in anisotropy include the posterior limb of the internal capsule and optic radiations (Huppi et al. 1998; Neil et al. 1998; Drobyshevsky et al. 2005). In contrast, maturation in gray matter is associated with a reduction in both fractional anisotropy (FA) and average diffusivity. In this case, the highly radial organization of immature cortical plate is disrupted by the elaboration of dendrites, myelination of intracortical white matter, and regression of radial glia. This occurs first in cortical areas that develop early, the primary sensory and motor cortical areas, and takes place later in association cortex (McKinstry et al. 2002; Kroenke et al. 2007, 2009). Thus, DTI studies have confirmed differential maturation rates of white and gray matter development as originally identified via the histological studies listed above (Zhang et al. 2003; Deipolyi et al. 2005; Kroenke et al. 2005, 2007, 2009; Ball et al. 2013; Melbourne et al. 2014).
In the current investigation, we have taken a systems-based approach to evaluate the developmental changes of anisotropy and diffusivity in cortical gray and adjacent white matter, focusing on primary motor, primary visual, visual association, and prefrontal areas in very preterm (VPT) infants age 26–40 weeks postmenstrual age (PMA). “VPT” infants were divided into 2 groups based upon the presence of brain injury at term equivalent PMA. Results were compared with those from a control group of healthy, term-born infants. We hypothesized that gray and white matter would develop in concert, such that the rate at which cortical gray matter anisotropy decreases parallels the rate at which adjacent subcortical white matter anisotropy increases. Furthermore, we anticipated changes in primary motor and visual regions would precede those of visual association and prefrontal regions. Finally, we hypothesized that both prematurity and the presence of moderate–severe white matter injury (WMI) would result in delayed gray and white matter development in VPT subjects when compared to healthy, term-born infants.
One hundred thirty-six VPT infants born prior to 30 weeks gestation were prospectively recruited from the St Louis Children's Hospital Neonatal Intensive Care Unit (NICU). Of these infants, 8 withdrew and one was excluded for congenital anomalies. Twenty died during their NICU course and 2 died prior to age 2 years. Of the 105 remaining surviving infants, 22 (12 females, 13 white) underwent 3 or more MRI scans during their hospital course and had no cystic lesions or extensive focal “WMI” on T1- and T2-weighted images. These infants will hereafter be referred to as the VPT group. An additional 3 infants from the same cohort (3 females, 1 white) underwent 3 or more serial scans and were found to have grade III/IV intraventricular hemorrhage and/or cystic WM lesions at term equivalent PMA, as determined by a single neonatologist (see Notes). These 3 infants were included in the WMI group described below. A total of 80 scans (70 from infants without injury and 10 from infants with injury) were collected across all time points for these infants. Demographic data and clinical information are provided in Table 1.
Sixteen VPT infants (4 females, 8 white) from the St Louis Children's Hospital Neonatal Intensive Care Unit (NICU) were identified to have grade III/IV intraventricular hemorrhage and/or cystic WM lesions based upon results of head ultrasound studies obtained routinely by the clinical teams. These infants will hereafter be referred to as the WMI group. These infants underwent a single MRI scan at term equivalent PMA with confirmation of previously observed head ultrasound findings (see Supplementary Table 1). A total of 16 scans were collected for these infants. Demographic and clinical information are provided in Table 1. Supplementary Table 1 provides a description of the injury type and location for each infant.
Twelve term-born infants (6 males, 6 white) were recruited from the Barnes-Jewish Hospital Newborn Nursery for the control group. All term infants had no history of in utero illicit substance exposure and no evidence of acidosis (pH <7.20) on umbilical cord or arterial blood gas assessments during the first hour of life. Demographic and clinical information for this group are provided in Table 2.
Exclusion criteria for all infants included chromosomal abnormalities or proven congenital infections (e.g., cytomegalovirus, toxoplasma, rubella). Parental informed written consent was obtained for each subject prior to participation in the study. All studies were approved by the Washington University Human Studies Committee.
VPT infants were imaged up to 4 times at designated intervals (<30, 30–31, 34–35, and 38–40 weeks PMA) depending on when they were sufficiently clinically stable for imaging. Term-born infants underwent MRI within the first 4 days of life. All infants were prepared and transported to the scanner using institutional neonatal MRI guidelines (Mathur et al. 2008). Infants were imaged without sedation during natural sleep or while resting quietly. Noise protection during scanning was provided using neonatal earmuffs (Natus Medical, Foster City, CA, USA). Heart rate and arterial oxygen saturation were continuously monitored throughout acquisition. A NICU staff member was present in the scanner room throughout the scan.
For all infants, MR images were acquired using a 3-T Siemens TIM Trio system (Erlangen, Germany) using an infant-specific, quadrature head coil (Advanced Imaging Research, Cleveland, OH, USA). Structural scans included a T2-weighted fast spin echo sequence [repetition time (TR) 8500 ms, echo time (TE) 160 ms, 1 × 1 × 1 mm3 voxels]. DTI data were also collected using a diffusion-weighted sequence [TR 13 300 ms, TE 112 ms, 1266 Hz/Px bandwidth, 128 mm field of view (FoV), 1.2 × 1.2 × 1.2 mm3 voxels, 48 b-directions with amplitudes ranging from 0 to 1200 s/mm2]. Total acquisition time for all sequences was approximately 60 min.
The diffusion signal attenuation curve was modeled as a monoexponential function plus a constant. MD and FA values were estimated using Bayesian Probability Theory (Kroenke et al. 2006). Regions of interest (ROIs) were manually placed by 2 raters (K.H. and T.S.) in native space using MD and b = 0 s/mm2 maps to identify anatomical structures. An inter-rater reliability rating of greater than 0.87 was calculated for all regions. Multiple small ROIs were positioned bilaterally in gray matter and immediately adjacent subcortical white matter in 4 regions: primary motor, primary visual, visual association, and prefrontal (Fig. 1). ROIs for each region were assessed on a consistent plane across subjects and were placed on 3 consecutive axial slices. ROI placement was validated against corresponding T2-weighted (b = 0 s/mm2) images to confirm placement within the cortical ribbon and adjacent white matter (and excluding cerebrospinal fluid).
FA and MD values were averaged across all ROIs located in each region. Because there was no statistical difference in these values between hemispheres, measures were also averaged across hemispheres. For each region, mean FA and MD measures for gray and white matter were plotted as a function of PMA. Results were fit using linear regression. Note that the relationships between the diffusion parameters and PMA are likely not linear, but the signal-to-noise ratio of the data and the relatively short period of development over which it was obtained did not support modeling with a more complex mathematical function. The PMA at which gray and white matter regression lines intersected (i.e., “crossover point”) was calculated for each subject.
Statistical analyses were performed using SPSS version 21 (IBM Corporation, NY, USA) and SAS 9.3 (SAS Institute, Cary, NC, USA). For each area, a general linear model including PMA at time of scan was used to test for differences in FA and MD values between groups. Random mixed-effects ANOVA was used to test for differences in crossover points for each area. Due to the number of diffusion measures that were simultaneously analyzed in the 4 regions, a Tukey adjustment was applied to account for multiple comparisons with a level of significance determined at P ≤ 0.01.
Figure 2 shows FA values for VPT infants as a function of PMA at time of scan for each of the 4 regions (Fig. 2A, motor; Fig. 2B, visual; Fig. 2C, visual association; Fig. 2D, prefrontal). Results for term control infants are provided for comparison. For gray matter (black diamonds), FA values decrease monotonically with increasing PMA. Conversely, white matter FA measures increase in conjunction with PMA (open squares). Similar patterns are evident in plots for the 3 infants from the WMI group on whom we had serial diffusion data (Supplementary Fig. 1). The plots of MD versus PMA showed both cortical gray and adjacent white matter values decrease with increasing PMA (Fig. 3). White matter MD values are greater than those of gray matter and decline at a faster rate. Similar patterns are again noted in the 3 infants of the WMI group with serial data (Supplementary Fig. 2).
The crossover point in each FA plot differed as a function of region (Figs 2 and and4).4). The crossover occurred earliest in the motor area, followed by visual, visual association, and finally prefrontal areas (Fig. 2A, 32.5 weeks PMA; Fig. 2B, 34.6 weeks PMA; Fig. 2C, 37.5 weeks PMA; Fig. 2D, 41.6 weeks PMA, respectively). Similar differences were seen in the 3 WMI infants with serial data (Supplementary Fig. 1).
On quantitative comparisons of FA and MD values from the MRI scans obtained at term equivalent PMA, there were no differences in FA measures for either the gray or white matter across investigated regions except for between term control and WMI groups in the white matter of the primary motor region (Table 3). For MD, differences were seen in nearly all regions studied when comparing WMI infants with infants from the VPT or term control groups. In contrast, when comparing the VPT and term control groups, the only differences found were in the white matter of the primary motor and prefrontal areas (Table 4).
In this study of serial VPT MRI scanning, microstructural development of the cortical gray and associated white matter occurred in concert. The crossover point between white and gray matter maturation curves provides a construct for assessing the rate of white and gray matter development. Regional differences in maturation rates were observed, with the primary motor and visual areas preceding visual association and prefrontal areas. At term equivalent PMA, differences in FA were found in only the white matter of the primary motor cortex when comparing the term control and WMI groups. In contrast, MD values were different in nearly all areas studied when comparing WMI infants with those in the VPT and term control groups. However, the only differences found between the term control and VPT groups were in the white matter of the primary motor and prefrontal areas.
The regionally specific patterns of synchronous development of the cortical gray and associated white matter demonstrated in our investigation are consistent with existing evidence. For developing cortex, a variety of means have been applied to assess relative rates of maturation in different regions. As early as 1901, myelination of intracortical white matter was noted to occur earlier in primary motor and sensory cortex than other areas (Flechsig Of Leipsic 1901). Subsequently, the relative order of cortical myelination of motor preceding visual preceding frontopolar was confirmed by others (Miller et al. 2012). (Note that myelination of intracortical axons may be among the main contributors to the loss of diffusion anisotropy that characterizes cortical development. Consequently, the current study could be interpreted as an extension of these earlier reports.) In his historic monograph (Brodmann 1909), Brodmann observed that the initial attainment of 6 recognizable layers during early cortical development takes place at regionally varying rates, with occipital regions preceding prefrontal cortex. Conel, using cresyl violet staining, noted that the development of primary motor cortex occurred earlier than striate cortex (Conel 1939a, 1939b). Careful assessment of pyramidal cell morphology and electrophysiology (Elston and Fujita 2014) has also shown that development in primary visual cortex precedes that of inferotemporal and granular prefrontal cortex. Regional maturation of synapses has also been evaluated. There is some controversy regarding whether rates of synapse formation vary regionally (Rakic et al. 1994; Huttenlocher and Dabholkar 1997; Bianchi et al. 2013). In contrast, synapse maturation/elimination proceeds for decades (Petanjek et al. 2008) and attains adult morphology earlier in motor, somatosensory, and visual association cortex than prefrontal cortex (Travis et al. 2005). Finally, gene expression in developing brain has been used as an indicator of maturation. Based upon these data, it was suggested that medial prefrontal cortex and inferior temporal cortex develop early (Pletikos et al. 2014). While this last finding contradicts ours and many others listed above, the areas evaluated in this genetic study are small and do not precisely correspond to those employed in the present study. Overall, the preponderance of evidence is consistent with the synthesis of Sidman and Rakic that areas near the insula are the most developmentally advanced, while areas further away undergo progressively more delayed development and, further, that primary motor and sensory areas undergo morphological differentiation prior to nonprimary areas (Sidman and Rakic 1982). This matches the order observed in the present study.
With regards to white matter, myelination progresses from the central sulcus outward toward the poles, with posterior sites preceding anterior frontotemporal sites (Kinney et al. 1988). Among the first fibers to myelinate are those in the posterior limb of the internal capsule and the optic radiations (Brody et al. 1987; Kinney et al. 1988). Primary motor and visual cortex contribute to and receive projections from the early myelinating posterior limb of the internal capsule and optic radiations (Brody et al. 1987; Kinney et al. 1988; Kostovic et al. 2002; Kizildag et al. 2005). Identical to these described spatial and functional gradients, measured diffusion values reflecting coordinated cortical differentiation and early myelination in adjoining gray and white matter reach more mature values earliest in the motor and visual areas followed by association and prefrontal areas.
Prior neuroimaging investigations in both animal models and human infants demonstrate similar patterns of cerebral development. DTI studies in mouse, ferret, baboon, and premature human infants have reported patterns of cortical diffusion anisotropy consistent with a cortical maturation gradient (Deipolyi et al. 2005; Kroenke et al. 2005, 2007, 2009; Ball et al. 2013). Furthermore, these investigations have shown that primary sensory and motor cortical areas precede non-primary cortex in reaching mature anisotropy values (Deipolyi et al. 2005; Kroenke et al. 2007, 2009; Ball et al. 2013). Similarly, studies of white matter anisotropy have reported findings consistent with regional variation in white matter development (Huppi et al. 1998; Neil et al. 1998). More recently, DTI tractography was used to quantify the early maturation of the main cerebral fascicles with results consistent with histological findings (Dubois et al. 2008). Finally, analysis of white matter diffusion data in which water compartments are separated based on displacement characteristics indicates that long association and callosal fibers mature earlier than short cortico-cortical fibers (Kunz et al. 2014). The present investigation extends these findings to illustrate coupled patterns of development in corresponding white and gray matter in both early and late developing regions in the brain.
The gray matter ROIs used in this study are on the order of 1.2 mm on each side and abut the cortical surface. At 24 weeks PMA, the cortical plate is roughly 1.2 mm wide. From 30 weeks PMA forward, it is approximately 1.1 mm wide (Kostovic and Rakic 1990). Thus, the gray matter ROIs are composed mainly of cortical plate and, due to partial volume averaging, some of the superficial portion of the subplate, sometimes known as the external capsule (Kostovic et al. 2014). In contrast, the white matter ROIs are, for the earliest time points of this study, located in subplate that is destined to become white matter. By 30 weeks PMA, the white matter ROIs consist of developing white matter, as the subplate has shrunk to <0.2 mm in width (Kostovic and Rakic 1990).
MD values tended to be higher in VPT infants compared with term infants, though this met statistical significance criteria in only 2 white matter areas (primary motor and prefrontal white matter). These brain areas include both early and late developing regions, suggesting a global susceptibility to the effects of prematurity. In contrast, FA values tended to be lower in VPT infants in all white and gray matter areas studied, but did not reach statistical significance in any, perhaps because FA measurements are inherently noisier than MD measurements. The finding of consistently lower white matter FA values in VPT infants, though not statistically significant, is consistent with studies showing regional differences in FA (Miller et al. 2002; Deipolyi et al. 2005; Ball et al. 2013). The differences in our results may be related to differences in ROI size and placement, as our ROIs were immediately subjacent to the cortex of interest and typically smaller than those typically used in previous studies.
These differences in diffusion parameters could be related to delayed maturation, as the MD and FA values for VPT infants were closer to those associated with less mature tissue in nearly all areas studied. However, they could also be related to injury. During their early NICU course, VPT infants are exposed to potential hypoxic–ischemic brain injury secondary to lung disease, severe illness, and other clinical variables. In the subacute phase of injury, MD values decrease, and this phenomenon is highly useful in the clinical setting for identifying injury (Moseley et al. 1990; Zhong et al. 1993; Ito et al. 1996; Dijkhuizen et al. 1998). However, the infants in this study were evaluated after the subacute phase of injury. During this chronic phase, the subacute reduction in MD has progressed to higher MD values, as measured in our study. It will be important to assess whether this pattern of elevated diffusion measures persists beyond infancy as has been previously described (Allin et al. 2011; Fischi-Gomez et al. 2014). FA values, in contrast, change relatively little during the acute phase of injury. However, in the longer term, injury to developing oligodendrocytes with subsequent reduction of myelination would lead to lower FA values for white matter, as suggested in this and other studies.
We found no differences in the crossover points and rates of maturation of associated gray and white matter in VPT infants without and the 3 VPT infants with WMI. This result should be considered preliminary at best, as the number of WMI infants is small. We did find consistent results in MD values at term equivalent PMA, which were higher for WMI infants than for both the term control and VPT groups. As discussed, these high MD values may reflect either delayed maturation or injury. No differences were found for FA values, but, as noted, this may be related to the fact that FA measures are inherently noisier than MD measures. Overall, these results suggest that the effects of WMI are more severe than those of preterm birth alone. Of note, Miller et al. (2002) previously observed differences in maturation rates for diffusivity and anisotropy measures in infants with WMI, though these findings were variable based upon injury severity and/or region. Other investigations of similar populations have demonstrated WMI, including moderate–severe injury, has relatively limited effects on diffusivity and anisotropy measures, particularly in regions remote from the injury site (Huppi et al. 2001; Tam et al. 2009).
Though it does not have any direct physical or physiological underpinning, the crossover point for FA is a convenient parameter for evaluating relative rates of brain development. The different PMAs at which this point occurs for different brain regions confirms what has been discovered in histologic studies, lending credence to the use of FA from both gray and white matter of living human brain as a means of assessing rates of maturation. In VPT infants, one might expect the crossover point to reflect disruption of brain development, occurring later in infants who ultimately will have worse outcomes. While the current study is not sufficiently powered to detect correlations between crossover point and outcome, we have performed a preliminary analysis of the FA crossover points and two-year outcomes on the Bayley Scales of Infant Development-III for the 19 VPT infants for whom we have outcome data. No correlation reaches statistical significance for this small number of subjects, though there are trends for negative correlations between motor outcome scores and crossover points in primary motor cortex (P = 0.170) and primary visual cortex (P = 0.047). However, should studies with more subjects and longer term follow-up confirm that crossover points correlate with outcomes, it would suggest that the processes leading to abnormal developmental outcome are set in motion early in the hospital course of these VPT infants, consistent with hypotheses put forth in some histologic studies (Petanjek et al. 2011; Petanjek and Kostovic 2012). From a clinical perspective, until it is more practical to routinely obtain longitudinal MRI studies on each preterm infant, the clinical utility of this measure will remain limited. From a scientific standpoint, this approach provides an additional means of evaluating brain maturation.
Several technical considerations are important for interpreting our results in the context of prior related investigations. The data used in the current investigation possessed both higher spatial resolution (voxel size 1.2 × 1.2 × 1.2 mm3) and greater dimensionality (48 b vectors) than these previous studies. These are key considerations when assessing the fidelity of observed measures. Because the observed cortical thickness of the gray matter is approximately 1 mm, higher spatial resolution and the increased accuracy of parameter estimations conferred by higher dimensionality are critical for limiting partial volume averaging effects. Additionally, multiple small ROIs were placed bilaterally in gray and white matter on individual native space images rather than atlas space images. This directed examination and individualization of ROI placement presumably increases the accuracy of measured values and sensitivity to alterations in microstructure observed when using global ROIs in atlas space.
While strict criteria regarding the number of serial scans required for inclusion produced robust measures of developmental trajectories, this investigation subsequently included a relatively small sample size—25 infants with serial data, including only 3 with heterogeneous moderate–severe WMI. The small number of subjects with WMI may be related to the fact that sicker infants were less likely to be included in this study because they were more often not sufficiently stable for MRI scanning at each time point. Another potential issue with detecting differences in infants with WMI is our methodological approach in which ROI placement did not take into account the location of WMI. The ROIs were placed bilaterally regardless of injury location, which was typically unilateral. Thus, the effects of injury may have been mitigated by this approach. In addition, ROI analyses have the potential for subjectivity and risk of poor reproducibility, though the precision of small ROIs and an inter-rater reliability rating of greater than 0.87 limited these effects. It is also important to note that while group-level results potentially inform our understanding of the neuroanatomical consequences of prematurity, they do not necessarily translate into diagnostic tests applicable in single infants.
The cortex and adjacent white matter in the developing preterm brain mature in concert and at varying rates according to region. Prematurity and WMI produce delayed development in both areas, with WMI exerting the greater effect. Finally, the crossover point of FA between white and gray matter maturation provides a helpful research metric for evaluating relative rates of brain development.
This work was supported by the National Institutes of Health (grant numbers R01 HD05709801 to T.E.I. and J.J.N., P30 HD062171 to T.E.I. and J.J.N., K02 NS089852 to C.D.S., K23 MH105179 to C.E.R., UL1 TR000448 to C.D.S. and C.E.R.), the Cerebral Palsy International Research Foundation (C.D.S), the Dana Foundation (C.D.S), and the Child Neurology Foundation (C.D.S). The funders had no role in study design, data collection, and analysis, decision to publish or preparation of the manuscript.
We acknowledge the members of the research team who assisted in acquiring the MRI scans and performing data analysis, including Joseph Ackerman, Karen Lukas, Anthony Barton, Michael Wallendorf, Erin Reynolds, and Kayla Hannon. White matter injury scores were provided by Hiroyuki Kidokoro. Finally, we thank the many infants and families who participated in the investigation for their generous assistance and dedication. Conflict of Interest: None declared.