Cerebral Cortex, Vol. 12, No. 12, 1237-1243,
December 2002
© 2002 Oxford University Press
Radial Organization of Developing Preterm Human Cerebral Cortex Revealed by Non-invasive Water Diffusion Anisotropy MRI
1 Mallinckrodt Institute of Radiology, , 2 Department of Neonatology, , 3 Department of Neurology, , 4 Program in Occupational Therapy, , 5 Department of Pediatrics, , 6 Division of Pediatric Neurology, St Louis Children’s Hospital at the Washington University Medical Center, St Louis, MO, USA and , 7 Department of Radiology, Rabin Medical Center, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
Jeffrey J. Neil, Pediatric Neurology, St Louis Children’s Hospital, 1 Children’s Place, St Louis, MO 63110, USA. Email: neil{at}wuchem.wustl.edu.
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Abstract |
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Cerebral cortical development involves a complex cascade of events which are difficult to visualize in intact, living subjects. In this study, we apply diffusion tensor imaging (DTI) to the evaluation of cortical development in human infants ranging from 26 to 41 weeks gestational age (GA). Apparent diffusion of water in cortex is maximally anisotropic at 26 weeks GA and anisotropy values approach zero by 36 weeks GA. During this period, the major eigenvector of the diffusion tensor in cerebral cortex is oriented radially across the cortical plate, in accord with a predominately radial deployment of its neuronal constituents. Values for the rotationally averaged water diffusion coefficient increase between 26 and 32 weeks GA, then decrease thereafter. These changes in DTI parameters are specific to cerebral cortex and reflect changes in underlying cortical architecture and formation of neuronal connections. Because of its correlation with tissue microstructure and non-invasive nature, DTI offers unique insight into cortical development in preterm human newborns and, potentially, detection of derangements of its basic cytoarchiteture.
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Introduction |
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The remarkable events which comprise cerebral cortical development take place in a well-ordered manner. The majority of cortical neurons are generated near the cerebral ventricles and migrate towards the pial surface along a radially arranged scaffolding of glial cells, arriving at their final destination in the fetal cortical plate and assuming a well-defined, radially oriented, columnar organization (Rakic, 1972
, 1988b). Subsequent cortical maturation involves elaboration of dendrites and axons, formation and regression of synaptic connections, and selective elimination of cell populations (Poliakov, 1959; Sidman and Rakic, 1982; Rakic, 1988a). To study the morphology and intricate biochemical processes involved in cortical development in animal model systems, ex vivo techniques such as electron microscopy, autoradiography, immunohistochemistry and analysis of spontaneous or induced mutations have been utilized (Cowan et al., 1997; Rubenstein and Rakic, 1999). In contrast, studies of human regional brain differentiation have been done traditionally on post mortem tissue using classic histological methods (Poliakov, 1959; Sidman and Rakic, 1973, 1982; Honig et al., 1996; Volpe, 2001) and only more recently with magnetic resonance imaging (MRI) of fixed tissue (Kostovic et al., 2002) and in vitro analysis of living slice preparations (Letinic and Rakic, 2001, 2002).
In the present study, we evaluate cortical development in live human infants using a form of magnetic resonance imaging — diffusion tensor imaging (DTI). DTI is a means of measuring the translational motion of water within tissue and is sensitive to molecular displacements on the order of 10 µm. This motion is often referred to as the ‘apparent diffusion’ of water in acknowledgment of the fact that water motion in tissue may reflect processes in addition to stochastic, thermally driven Brownian motion (Neil, 1997).
One unique feature of DTI is that the directionality of water motion can be determined. A sample of pure water, for example, has water displacements which are equal in all directions (isotropic diffusion). In tissue, on the other hand, water motion is hindered by cellular constituents. If this hindrance is greater in one direction than another, water motion is anisotropic. For example, water molecules in white matter move less freely perpendicular to fibers than parallel to them because motion perpendicular to fibers requires passing through or around layers of myelin membrane, whereas motion parallel to them does not. Thus, water apparent diffusion in mature white matter is highly anisotropic. In this manner, DTI characterizes tissue microstructure. Three quantities extracted from DTI are particularly useful for microstructural characterization: the directionally averaged water apparent diffusion coefficient (Dav); the degree of anisotropy of water motion (A
); and the orientation along which water apparent diffusion is greatest (the direction of the major eigenvector of the diffusion tensor). Dav represents how freely water diffuses through tissue. Dav is greater when tissue water content is higher or when barriers to water motion, such as cell membranes, are widely spaced. For reference, Dav for pure water at body temperature is on the order of 3.0 x 10-3 mm2/s, that for infant brain ranges from 1.0 to 2.0 x 10-3 mm2/s (Huppi et al., 1998; Neil et al., 1998) and that for adult brain is on the order of 0.8 x 10-3 mm2/s (Pierpaoli et al., 1996; Shimony et al., 1999). A ranges from near zero for adult cerebral cortex (isotropic diffusion) to 0.5 for adult commissural white matter (Shimony et al., 1999). The orientation of the major eigenvector of the diffusion tensor, since it is parallel to the predominant fiber direction in white matter, has been used to trace the course of white matter tracts in intact brain (Conturo et al., 1999; Mori et al., 1999; Basser et al., 2000).
Using current DTI methodology, water diffusion in the adult cerebral cortex is isotropic or very mildly anisotropic (Shimony et al., 1999; Sorensen et al., 1999). However, a previous study from our laboratory indicated that cerebral cortex in premature infants may be strongly anisotropic transiently during development [see fig. 2 of Neil et al. (Neil et al., 1998)]. Similar observations have been made in studies of live cat (Baratti et al., 1997) and piglet (Thornton et al., 1997), as well as fixed mouse brain (Mori et al., 2001). In this study, we characterize water diffusion in cortical gray matter in a series of human neonates at gestational ages (GA) ranging from 26 to 41 weeks. The orderly progression of water diffusion parameters during development, as it reflects changes in cortical microstructure, may ultimately provide novel information regarding both cortical development and abnormalities of that development.
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Materials and Methods |
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Subjects
All studies were approved by the Washington University Human Studies Committee. Infants were studied only after parental consent was obtained. The study included an initial scan within the first 36 h after birth. A total of 24 infants were imaged. Ten of these underwent a single scan within the first 2 days of life as part of a previous study (Neil et al., 1998). The remaining 14 underwent two scans, one near the time of birth and a second prior to discharge from the hospital.
Preterm infants were recruited from the neonatal intensive care unit and special care nursery. Infants were all products of uncomplicated deliveries. Their GAs ranged from 26 to 41 weeks. The GA was based on the mother’s last menstrual period, the infant’s Ballard score (Ballard et al., 1991) and fetal ultrasound (if available). Subjects were excluded if these GA estimates did not agree to within 1 week. The GAs used for data analysis were the averages of these values. Infants were also excluded if there was evidence of drug exposure in utero, brain injury (seizures, altered mental status), significant hypoxia (reduced urine output, cardiac injury requiring administration of pressor agents), severe respiratory distress, or congenital malformations. In addition, infants on continuous positive airway pressure were excluded because of equipment incompatibility with the MR scanner. Infants whose MR scan prior to discharge from the hospital were included in the data were those for whom there were no known complications during the hospital course that would cause cortical injury.
Infants were transported in an incubator to and from the MR scanner under supervision of a pediatric transport nurse and a physician. Infants were swaddled in warm sheets/blankets, placed on the scanner table on an MR-compatible chemical heating pad (Portawarm mattress; Abbott Laboratories, Abbott Park, IL) and their heads restrained with soft cushions. No sedation was used. The infant’s heart rate and oxygenation were monitored via pulse-oximetry. Infants needing ventilator support were hand ventilated for the duration of the study.
The data were obtained on a 1.5 T Siemens Magnetom Vision system (Erlangen, Germany) using a circularly polarized extremity coil. Conventional T1- and T2-weighted MR scans were obtained using contiguous, 5 mm, transverse sections. The field of view (FOV) was 150 mm, yielding 0.6 x 0.6 mm in-plane resolution. DTI consisted of single-shot, multisection, spin echo planar imaging (EPI) with FOV 240 mm, in-plane resolution 1.9 x 1.9 mm interpolated to a 256 x 256 matrix for display and analysis, repetition time (TR) 3000 ms and echo time (TE) 106 ms. Four tetrahedrally oriented, diffusion-weighted images (diffusion sensitivity, b = 800 s/mm2), three orthogonally oriented, diffusion-weighted images (b = 340 s/mm2) and a reference T2-weighted intensity image (b = 0 s/mm2) were obtained at each transverse section. Two, nine-slice DTI acquisitions were obtained and manually interleaved. Each individual DTI acquisition with image transfer took ~2 min. Wherever possible, each slice location was repeated three times to provide data redundancy for reconstruction of images should the infant move during the scan. The typical total time in the scanner was 40 min for conventional and DTI data collection.
Image Analysis
All raw diffusion DTI MR images were realigned in two dimensions using a combination of intra- and cross-modality affine realignment procedures to correct for image displacements and linear stretch or shear due to eddy currents (Neil et al., 1998). For each pixel, the elements of the diffusion tensor were derived from this combination of reference T2-weighted images, tetrahedral diffusion measurements and perpendicular diffusion measurements (Neil et al., 1998; Shimony et al., 1999). Image quality was assessed by evaluating anisotropy maps. These maps are extremely sensitive to changes in image quality caused by movement artifact or poor signal-to-noise ratio. If anisotropy values were excessively high for the region of the centrum semiovale, a region of typically low anisotropy, the data set was not used.
A single contiguous region-of-interest (ROI) encompassing the parietal and occipital cortex was outlined on T2-weighted MR images, where there is especially strong contrast between the developing gray and white matter in the premature brain. These ROIs were translated to DTI maps and sampled for water apparent diffusion coefficient and anisotropy using ANALYZE software (Mayo Foundation Rochester, MN). In an effort to minimize within-slice partial volume effects, which may contribute to inaccurate measurement of DTI indices, cortical regions were outlined on the slice of interest and then verified to include only the cortex on the image slices above and below the slice of interest. To accomplish this, the outline of parietal and occipital cortex from the slice of interest was projected onto the slices above and below the slice of interest. Any region that was not composed of gray matter on these slices was removed from the outline (such regions typically contained cerebrospinal fluid due to curvature of the cortex). ROIs from occipital and parietal cortex were chosen for analysis to avoid magnetic susceptibility artifacts that sometimes arise in frontal and temporal cortex due to the proximity of nasal cavities or auditory canals. All ROI placements were verified by a CAQ-certified neuroradiologist (R.C.M.) and a board certified pediatric neurologist (J.J.N.). ‘Whisker plots’ were generated using Matlab (MathWorks Inc., Natick, MA) to superimpose lines representing the projection of the major eigenvector onto the Dav map.
Data were analyzed using a Spearman rank correlation. The relationship between GA and Dav for cortex was analyzed using the general linear model procedure (SAS Software, Cary, NC).
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Results |
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A total of 24 infants were evaluated for the study. Of these, 14 underwent two scans, giving a total of 38 available studies. Of these 38 studies, 28 were sufficiently free of movement artifact for further analysis. The infants selected for study were those with relatively uneventful prenatal and perinatal courses. Never-theless, the majority were born prematurely and premature birth is often associated with other complications. Pregnancy was complicated by gestational diabetes mellitus for one, pregnancy-induced hypertension for two, twin gestation for four and proteinuria for two. Prolonged rupture of membranes was present for three, though none of these three infants had sepsis detected on routine blood, cerebrospinal fluid and urine culture. None of these complications would be expected to lead directly to brain injury. Of the 24 infants studied, six were delivered by Caesarean section and the rest vaginally. All infants were healthy at delivery except for those needing ventilator support due to lung immaturity.
Figure 1 shows axial images from the level of the basal ganglia at differing GAs. As seen on the T1-weighted images, the gyral pattern of the cortex becomes more complex between 26 and 35 weeks GA. On the Dav maps, cerebral cortex appears dark because Dav values in cortex are lower than those of white matter at this age (Huppi et al., 1998; Neil et al., 1998). In the corresponding A maps, the cerebral cortex shows relatively high anisotropy at 26 and 31 weeks GA, but this diminished by 35 weeks GA. Note that cortical anisotropy is not seen consistently in the frontal region (see Discussion). Note also that the outermost rim of high anisotropy present in the images is an artifact. In regions where signal is low (such as in the skull), anisotropy values are artifactually increased because the DTI acquisition parameters are not optimized for the signal from this particular area — instead, they are optimized for signal from brain. The anisotropy maps have been cropped so that the areas outside the skull are not shown. Relatively high anisotropy is also present in central, projectional and commissural white matter tracts, including the genu and splenium of the corpus callosum as well as the internal and external capsules.
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Figure 2
shows the values for A as a function of GA. For the posterior limb of the internal capsule (Fig. 2A, closed circles), these values gradually increase with increasing GA (rank sum = 0.97, P < 0.01, Spearman rank correlation). Values for the head of the caudate nucleus (Fig. 2A, open circles), on the other hand, are consistent with zero and remain so throughout the GAs studied (rank sum = –0.11, P > 0.10). (Note that A values are calculated as the standard deviation of the magnitudes of the principal eigenvalues. These magnitudes are never exactly equal, even for isotropic diffusion, because of noise in the measurement. As a result, As values do not reach zero, but approach a ‘noise floor.’ For this study, the noise floor is ~0.05.) For cerebral cortex (Fig. 2B), there is a statistically significant decline in diffusion anisotropy with increasing GA (rank sum = –0.94, P < 0.01).
Values for Dav as a function of GA are shown in Figure 3. Dav values for the posterior limb of the internal capsule (Fig. 3A, closed circles) and head of the caudate (Fig. 3A, open circles) decrease monotonically with increasing GA. Spearman rank correlation of data from the posterior limb of the internal capsule show rank sum = –0.92, P < 0.01; for the head of the caudate, rank sum = –0.66, P < 0.01. Values for cortex (Fig. 3B), on the other hand, increase between 26 and 32 weeks GA and decrease thereafter. These data were examined using a polynomial regression approach to identify the degree of polynomial required to fit the data appropriately. Using a model involving linear, quadratic and cubic terms, the cubic term was not statistically significant (P > 0.05). After dropping this term and using a model involving linear and quadratic terms, R2 was 0.48 and the quadratic term was statistically significant (P < 0.01). Finally, using a model with only a linear term, R2 fell to 0.04. Thus, fitting the data to a quadratic expression is statistically justifiable and reflects the observation that Dav values vary with GA in a nonlinear fashion (Fig. 3B).
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The orientation of the major eigenvectors of the diffusion tensors is shown in Figure 4
. For cerebral cortex, the orientation is primarily radial (orthogonal to the cortical surface) at 26 weeks GA (Fig. 4A). By 35 weeks GA, this orientation is no longer detectable (Fig. 4B) as the diffusion anisotropy values approach the noise floor (Fig. 2B). For central white matter, the orientation of the major eigenvectors follows the general direction of white matter tracts in the genu and splenium of the corpus callosum (Fig. 4A,B).
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Discussion |
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The key finding of this study is that the cerebral cortex demonstrates a pronounced radial organization that is clearly visible at 26 weeks GA, but disappears by 36 weeks GA. One means of visualizing this mathematical result is by representing water diffusion with a diffusion ellipsoid, a construct which has been used for decades to describe diffusion in three dimensions. If one places a drop of colored dye into a glass of water and allows it to diffuse for some time, the shape assumed by the dye is a sphere because dye molecules are equally likely to diffuse in any direction (provided they do not encounter the walls of the container). If a dye droplet is placed into the white matter of brain and allowed to diffuse for some time, the resultant shape is not spherical. Rather, it is similar to a rugby ball with the long axis oriented parallel to the white matter tracts. This non-spherical shape is present because the dye molecules move more freely parallel to axons than orthogonal to them, as motion orthogonal to fibers is more strongly restricted by barriers to diffusion, such as myelin layers. A
is a means of quantifying this phenomenon. When diffusion is isotropic (A = 0), the ellipsoid shape is spherical; when diffusion is anisotropic (A > 0), the ellipsoid shape is more akin to the shape of a rugby ball. The longer and thinner the ellipsoid, the higher the value for A. Such prolate ellipsoids are shown schematically in Figure 5.
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Water diffusion properties are strongly influenced by tissue microstructure. It is generally agreed that diffusion anisotropy in white matter is due to the ordered architecture of axons and myelin in fiber bundles (Beaulieu and Allen, 1994
). However, some other microstructural explanation is called for in developing cerebral cortex, as ordered bundles of axons are absent. Although adult cerebral cortex is believed to operate as an ensemble of functionally linked radial columns (Mountcastle, 1997), this organization is obscured in adult cerebrum by the predominance of laminar organization. Here, we report that this basic, radial organization is clearly visible during a specific developmental time period. Neuronal migration from the ventricular zone to the cortical plate in the human fetal cerebrum is essentially complete by 26 weeks GA (Sidman and Rakic, 1973; Kostovic et al., 2002). Therefore, the microstructural changes taking place in human cerebral cortex between 26 and 41 weeks GA correspond to the stage of ‘cortical maturation’ of Sidman and Rakic (Sidman and Rakic, 1982) or the ‘perinatal period’ of Marín-Padilla (Marin-Padilla, 1992). Early in this period, large pyramidal cells begin their maturation and extend dendrites into layer 1, along radial glial cells (Marin-Padilla, 1992). This organization may preferentially hinder water motion orthogonal to the cortical surface as compared with radial to it, accounting for both the relatively high anisotropy and the radial orientation of the major eigenvectors. Subsequently, this developmental period is characterized by progressive neuronal maturation. This includes formation of cell processes and their connections (Poliakov, 1959; Sidman and Rakic, 1982; Kostovic and Rakic, 1990), as well as the arrival of a large number of local circuit neurons and their differentiation in the cortical plate (Letinic and Rakic, 2002). These changes in microstructure may disrupt the initially more pronounced radial organization. By 36 weeks GA, the elaboration of basal dendrites of pyramidal cells, formation of local circuits, addition of thalamocortical afferent fibers (Kostovic and Rakic, 1990) and disappearance of radial glia (Sidman and Rakic, 1973, 1982) lead to roughly equivalent hind-rance of water motion both orthogonal to the cortical surface and radial to it. This sequence of cellular events would explain the gradual loss of anisotropy which takes place between 26 and 36 weeks GA (Fig. 5). This pattern of anisotropy change is specific to cerebral cortex. Areas of high anisotropy in white matter areas generally show steadily increasing A values with increasing GA (Huppi et al., 1998; Neil et al., 1998).
The reason for not consistently finding high anisotropy values in frontal cortex is not clear from this study. It is most likely due to the presence of bulk magnetic susceptibility effects in this area caused by the proximity of the air–tissue interface of the nasal cavity. These susceptibility effects disrupt the local static magnetic field, producing artifacts that interfere with the measurement of diffusion. Alternatively, it may represent a different pattern of maturation for frontal cortex. For example, it has been shown that formation of columns in the prefrontal cortex in primates precedes formation of columnar dominance columns in the visual cortex (Schwartz and Goldman-Rakic, 1991). Thus it is possible that, by 26 weeks GA, frontal cortex has already passed through the stage at which anisotropy values are high.
The finding that cortical Dav values increase between 26 and 32 weeks GA, then decrease from 32 to 41 weeks, is also unique to developing cortex. Previous studies have shown that Dav values decrease monotonically with increasing GA for all areas studied, including cerebral cortex (Huppi et al., 1998; Neil et al., 1998). However, neither of these studies included infants <30 weeks GA, so this phenomenon could not have been detected. Nevertheless, data from non-cortical brain areas — the head of the caudate (this study) and white matter areas (data not shown) — show a steady decrease of Dav values even before 30 weeks GA. For those brain areas which show a steady decrease in Dav values throughout development, this finding is readily explained by the dramatic decrease in water content which takes place during brain maturation (Dobbing and Sands, 1973). As water content decreases, barriers to motion move closer together, leading to a decrease in Dav values. For cortical plate, phenomena that could explain an increase rather than decrease in Dav values early during maturation include a decrease in cell density associated with programmed cell death (Bayer and Altman, 1991; Chan and Yew, 1998) and, in particular, the addition of neuropil between the neuronal somas (Bourgeois and Rakic, 1993). (This argument includes the assumption that neuropil has low hindrance to water motion as compared with cell somas, which is not proven.) Thus, it is plausible that competing mechanisms — addition of neuropil and programmed cell death versus decreasing water content — cause a rise in Dav values between 26 and 32 weeks GA, followed by a fall after 32 weeks GA.
In summary, this study represents the first characterization of the magnitude and orientation of water diffusion anisotropy in premature newborn human cerebral cortex. The dramatic changes in diffusion parameters which accompany cortical maturation parallel changes in the underlying cellular architecture. Diffusion methodology offers the potential for unique insight into the cortical development of both normal infants and those with brain injury. It may also be possible to detect alterations in cortical microstructure caused by various genetic and environmental factors (Rakic, 1988a; Volpe, 2001; Buxhoeveden and Casanova, 2002).
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Footnotes |
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This research was supported by NIH grants NS37357 and CA83060. The authors thank Dr Brad Schlaggar for useful discussion and Dr Paul Thompson for assistance with statistical analysis.
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C. D. Kroenke, D. C. Van Essen, T. E. Inder, S. Rees, G. L. Bretthorst, and J. J. Neil Microstructural Changes of the Baboon Cerebral Cortex during Gestational Development Reflected in Magnetic Resonance Imaging Diffusion Anisotropy J. Neurosci., November 14, 2007; 27(46): 12506 - 12515. [Abstract] [Full Text] [PDF]
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P. G. P. Nucifora, R. Verma, S.-K. Lee, and E. R. Melhem Diffusion-Tensor MR Imaging and Tractography: Exploring Brain Microstructure and Connectivity Radiology, November 1, 2007; 245(2): 367 - 384. [Abstract] [Full Text] [PDF]
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S. V. Sizonenko, E. J. Camm, J. R. Garbow, S. E. Maier, T. E. Inder, C. E. Williams, J. J. Neil, and P. S. Huppi Developmental Changes and Injury Induced Disruption of the Radial Organization of the Cortex in the Immature Rat Brain Revealed by In Vivo Diffusion Tensor MRI Cereb Cortex, November 1, 2007; 17(11): 2609 - 2617. [Abstract] [Full Text] [PDF]
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M. F. Casanova, J. Trippe II, and A. Switala A Temporal Continuity to the Vertical Organization of the Human Neocortex Cereb Cortex, January 1, 2007; 17(1): 130 - 137. [Abstract] [Full Text] [PDF]
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J.S. Shimony, H. Burton, A.A. Epstein, D.G. McLaren, S.W. Sun, and A.Z. Snyder Diffusion Tensor Imaging Reveals White Matter Reorganization in Early Blind Humans Cereb Cortex, November 1, 2006; 16(11): 1653 - 1661. [Abstract] [Full Text] [PDF]
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R. Verma, S. Mori, D. Shen, P. Yarowsky, J. Zhang, and C. Davatzikos Spatiotemporal maturation patterns of murine brain quantified by diffusion tensor MRI and deformation-based morphometry PNAS, May 10, 2005; 102(19): 6978 - 6983. [Abstract] [Full Text] [PDF]
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S. Rakic and N. Zecevic Emerging Complexity of Layer I in Human Cerebral Cortex Cereb Cortex, October 1, 2003; 13(10): 1072 - 1083. [Abstract] [Full Text] [PDF]
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