Differential effects of intrauterine growth restriction on brain structure and development in preterm infants: A magnetic resonance imaging study

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available at www.sciencedirect.com

www.elsevier.com/locate/brainres

Research Report

Differential effects of intrauterine growth restriction on brain structure and development in preterm infants: A magnetic resonance imaging study Nelly Padillaa,d,e,⁎, Carles Falcónd,f , Magdalena Sanz-Cortésa,d,e , Francesc Figuerasa,d,e , Núria Bargalloc,d , Fátima Crispia,d,e , Elisenda Eixarcha,d,e , Angela Arranza,d,e , Francesc Botet b , Eduard Gratacósa,d,e a

Department of Maternal-Fetal Medicine, Hospital Clínic, Universidad de Barcelona, Calle Sabino de Arana 1, 08028, Barcelona, Spain Department of Neonatology (ICGON), Hospital Clínic, Universidad de Barcelona, Calle Sabino de Arana 1, 08028, Barcelona, Spain c Department of Radiology (CDIC), Hospital Clínic, Universidad de Barcelona, Calle Sabino de Arana 1, 08028, Barcelona, Spain d Institut D'investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain e Centro de Investigación Biomédica en Enfermedades Raras (CIBERER), Spain f Centro de Investigación Biomédica en Enfermedades Raras en Bioingeniería, biomedicina y nanomedicina (CIBER-BBN), Calle Villarroel 170, 08036, Barcelona, Spain b

A R T I C LE I N FO

AB S T R A C T

Article history:

Previous evidence suggests that preterm newborns with intrauterine growth restriction

Accepted 11 January 2011

(IUGR) have specific neurostructural and neurodevelopmental anomalies, but it is unknown

Available online 19 January 2011

whether these effects persist in early childhood. We studied a sample of 18 preterm IUGR, 15 preterm AGA – born between 26 and 34 weeks of gestational age (GA) – and 15 healthy born-

Keywords:

term infants. Infants were scanned at 12 months corrected age (CA), in a 3T scanner, without

Premature infants

sedation. Analyses were made by automated lobar volumetry and voxel-based

Intrauterine growth restriction

morphometry (VBM). The neurodevelopmental outcome was assessed in all subjects at 18

Development

months CA with the Bayley Scale for Infant and Toddler Development, third edition. IUGR

Brain injury

infants had reduced relative volumes for the insular and temporal lobes. According to VBM,

Magnetic resonance

IUGR infants had bilateral reduced gray matter (GM) in the temporal, parietal, frontal, and

Voxel-based morphometry

insular regions compared with the other groups. IUGR infants had increased white matter (WM) in temporal regions compared to the AGA group and in frontal, parietal, occipital, and insular regions compared to the term group. They also showed decreased WM in the cerebellum and a non-significant trend in the hippocampus compared to term infants. IUGR

⁎ Corresponding author at: Department of Maternal-Fetal Medicine, Hospital Clínic, Universidad de Barcelona, Calle Sabino de Arana 1, 08028, Barcelona, Spain. Fax: +34 93 227 9336. E-mail address: [email protected] (N. Padilla). Abbreviations: AGA, appropriate for gestational age; BSID-III, Bayley Scale for Infant Development-third edition; BW, birth weight; CA, corrected age; CSF, cerebrospinal fluid; FL, frontal lobe; GA, gestational age; GM, gray matter; HC, head circumference; IL, insular lobe; ICV, intracranial volume; IUGR, intrauterine growth restriction; MRI, magnetic resonance imaging; OL, occipital lobe; PL, parietal lobe; PVL, periventricular leukomalacia; SNAP-II, score for neonatal acute physiology, version-II; TBV, total brain volume; TL, temporal lobe; US, ultrasound; VBM, voxel-based morphometry; WM, white matter 0006-8993/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2011.01.032

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infants had reduced neurodevelopmental scores, which were positively correlated with GM in various regions. These data suggest that the IUGR induces a distinct brain pattern of structural changes that persist at 1 year of life and are associated with specific developmental difficulties. © 2011 Elsevier B.V. All rights reserved.

1.

Introduction

Preterm birth is a public-health problem associated with a high risk of brain damage that can lead to neurodevelopmental disabilities including deficits in high-order neurocognitive functions, academic underachievement, and behavioral, social, and emotional difficulties (Aylward, 2005). These functional deficits are associated with macrostructural (Mathur and Inder, 2009) as well as microstructural differences (Counsell et al., 2008). A substantial proportion of premature newborns present intrauterine growth restriction (IUGR) (Alberry and Soothill, 2007), which is associated with exposure to chronic hypoxia and undernutrition in fetal life. Follow-up studies (Fattal-Valevski et al., 2009; Leitner et al., 2007; Geva et al., 2006a) suggest that the presence of IUGR in late preterm and term children results in a distinct pattern of neurodevelopmental disabilities especially in terms of cognitive skills and executive functions. In addition, neonatal MRI studies have demonstrated specific differences in the brain composition including significant volume reductions in gray matter (GM) (Tolsa et al., 2004), decreased volumes of the hippocampus (Lodygensky et al., 2008) and a discordant pattern of gyrification (Dubois et al., 2008). So far, quantitative MRI studies to document the impact of IUGR in preterm patients have been performed at birth and at term corrected age (CA). Therefore, it is not clear whether the structural brain differences are evident at 1 year of age. This represents a gap in current knowledge, considering that the period from birth until 2 years of age, involves some critical changes (Knickmeyer et al., 2008; Tzarouchi et al., 2009; Gao et al., 2009) in brain size, GM volumes, synaptogenesis, and myelination. Performing research MRI in infants is a challenging task (Altaye et al., 2008) especially due to subject motion, which may require infant sedation and consequently a low acceptance rate by parents. Taking this into account, we have recently demonstrated, using a MRI protocol without sedation in infants at 12 months of age, that IUGR infants have decreased cortical surface complexity related to neurodevelopmental difficulties (Esteban et al., 2010). To our knowledge no volumetric studies have examined the whole brain in preterm infants with and without IUGR at 12 months' CA, especially with regard to regional GM and white matter (WM) differences in brain morphology. In this study we hypothesized that at this age there would be differences between groups in brain morphology at global and local level especially with regard to regional GM and white WM distribution, which might be associated with worse performance in neurodevelopment. We evaluated global and local brain differences using automated lobar volumetry and voxel-based morphometry (VBM) respectively in preterm infants with and without IUGR at 12 months' CA.

2.

Results

2.1.

General characteristics

When the preterm groups were compared, the Apgar score at 5 min (9.3 ± 7.6 vs. 9.1 ± 1.6, P = 0.92), umbilical artery pH (7.23 ± 0.08 vs. 7.27 ± 0.18, P = 0.40), and SNAP-II (19.3 ± 13.8 vs. 18.4 ± 13.7, P = 0.85) detected were similar. No significant differences between IUGR and AGA preterm groups were found regarding late neonatal sepsis [(2/18 (11.1%) vs. 2/15 (13.3%), P = 1.0], or the use of prenatal corticosteroids [12/18 (66.6%) vs. 8/15 (53.3%), P = 0.49] or postnatal steroids [0 vs. 2/15 (13.3%), P = 0.19]. No infant was diagnosed as having necrotizing enterocolitis or chronic lung disease. Brain ultrasound at 3 days of life was normal in all cases in both preterm groups except for two IUGR neonates and one preterm control neonate who showed intraventricular hemorrhage grade I. At term-equivalent age, five preterm IUGR and two preterm infants had periventricular leukomalacia grade I. With respect to nutritional management in NICU, preterm neonates had essentially equivalent nutritional intakes. Regarding breastfeeding, no statistical differences were found between the preterm groups and the term group. No significant differences in HC at 12 months' CA were found between groups, anthropometric and demographic characteristics are shown in Table 1. The MRI evaluation revealed the presence of anomalies in two preterm IUGR (two ventricular dilatations), three preterm AGA (three ventricular dilatations), and two term infants (two increased cisterna magna). Motion artifacts on MRI were found in two AGA infants and three term infants. Thus, the final sample included 18 IUGR infants, 15 AGA infants and 15 term infants. In terms of perinatal or demographic characteristics, the infants who were excluded from the study did not significantly differ from those who were included.

2.2.

Neurodevelopment assessment

Preterm IUGR group showed significantly lower scores than the term group in motor, fine motor, and adaptive behavior (Table 2) although only the fine motor score remained significant after Bonferroni correction.

2.3.

Global and lobar brain volume data

2.3.1.

Automated lobar volumetry

No differences among groups were found respecting global brain volumes (Table 2). Absolute lobar volumes analyses (Table 3) did not show significant differences between groups. However, the relative volumes showed the IL and the TL significantly smaller in IUGR compared with term infants

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although only the IL remained significant after Bonferroni correction. Regarding the hippocampus the volumes remained similar between groups. In the whole sample, there were significant positive correlations between neonatal biometric data and relative brain volume in the TL (BW: r = 0.405, P = 0.004; length: r = 0.372, P = 0.009; HC: r = 0.296, P = 0.041) and IL (BW: r =0.472, P = 0.001; length: r = 0.446, P = 0.002; HC: r = 0.428, P = 0.002). Additionally no significant relationships between cerebral lobar volumetry and neurodevelopmental data were observed, although the correlation between adaptive behavior and relative volume in the IL showed a trend toward positive significance (r =0.28, P = 0.05).

2.3.2.

VBM analyses

The GM and WM distributions between groups are presented in Table 4 and Fig. 3. Preterm IUGR compared to the term group showed extensive areas of decreased GM volumes involving predominantly bilateral TL (superior, middle, and inferior gyri), right frontal lobe (precentral gyrus and posterior orbital gyrus), bilateral IL and bilateral parietal lobe (superior gyrus). When cases presenting PVL in their neonatal ultrasound were excluded, the comparison between preterm IUGR and preterm AGA displayed the same GM-decreased regions in number and location, with the addition of the left pallidum (cluster = 957, P = 0.04, t = 4.77). No areas of increased GM volumes were found. Comparisons between preterm IUGR and preterm AGA group showed decreased GM volumes in a bilateral distribution involving the TL (superior gyrus, posterior part), bilateral IL, left frontal lobe (middle gyrus) and left parietal lobe (postcentral gyrus). Mean differences in WM volumes between IUGR and term infants indicated decreased WM in the cerebellum bilaterally and right hippocampus, although only the left cerebellum reached statistical significance (cluster = 1222, P = 0.008, t = 5.43). Areas of greater WM volumes were identified in the left parietal lobe and left occipital lobe, FL (Right and left superior

gyrus and left precentral gyrus) and left IL. In comparison with the preterm AGA group, the IUGR infants showed a larger WM volume in the TL bilaterally (superior temporal gyrus, posterior part). Comparison between preterm AGA and term infants indicated lower GM volume in the left TL (superior gyrus posterior part), while no differences in WM volumes were found. Regarding neurodevelopment, the preterm IUGR group registered positive correlations between motor scores and GM volume in the left precuneus (Fig. 4) (cluster = 2319, P = 0.000, r = 0.80 and cluster = 1277, P= 0.002; r = 0.83) and right superiorfrontal gyrus (cluster = 997, r = 0.86, P = 0.009 and cluster 1735, P= 0.000, r = 0.82). Positive correlations were also found between fine motor subscale scores and GM in the right superior parietal gyrus (cluster = 1449, P = 0.001, r = 0.84 and between the adaptive behavior subscale scores and GM in the right superior parietal gyrus (cluster = 812, 0.03, r = 0.83). No correlation between BSIDIII scores and WM volumes were observed nor were any correlations detected in the preterm AGA group.

3.

Discussion

Findings from this study revealed that preterm IUGR infants present differences in brain lobar volumes and a specific distribution pattern of GM and WM associated with neurodevelopmental difficulties when compared to preterm AGA and term infants. The structural differences in the brain of IUGR infants were more pronounced, suggesting higher vulnerability in this group. It bears noting that no differences (or minimal differences) were found between preterm infants and term infants. These results support the notion that IUGR continues to induce specific changes in brain development at 12 months CA. However, these changes must be interpreted through the lens of the developmental stage of the brain at this age. In this study, IUGR showed worse performance in the neurodevelopmental assessment with more pronounced

Fig. 1 – Coronal, sagittal and axial slices from a term control (a) and preterm IUGR (b) infants showing the T1-weighted images (first column) and the segmentation of the gray matter (second column), white matter (third column) and cerebrospinal fluid (fourth column).

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changes involving the fine motor domain. Of note, both preterm groups were comparable in neonatal morbidity, NICU nutritional management (and together with the third group ingesting breast milk), and this allowed the exclusion of any specific impact of neonatal complications in the outcome at 1 year old. Other causes such as nutritional, environmental, genetic (Powers et al., 2008), and postnatal growth factors (Padilla et al., 2010) appear to explain the developmental differences in the IUGR infants. Developmental studies focusing specifically on preterm IUGR infants (Lodygensky et al., 2008; Padilla et al., 2010) have also failed to document clear differences in comparison with preterm AGA children. These findings contrast with the results of the present study, but it should be borne in mind that we used a more specific instrument of evaluation in the current work, since BSID-III offers significant additions and improvements over the previous editions (Albers and Grieves, 2007). However, our results are in line with those reported in long-term longitudinal studies that identify an increased rate of developmental disabilities in IUGR children (Geva et al., 2006a; Leitner et al., 2007) and suggest that developmental difficulties could be detected as early as at 18 months if sensitive evaluation methods are used. Of note, we could not find significant differences in HC between groups. The discrepancy of our results with those of other studies (Fattal-Valevski et al., 2009; Geva et al., 2006a) could reflect differences in the case-mix and in the severity of cases under study, which need to be elucidated in larger studies. However, our findings are in line with recent studies that suggest a prioritized accelerated head catch-up growth in preterm IUGR infants (Westerberg et al., 2010). The concept of accelerated catch-up growth in preterm IUGR infants has already been suggested by other groups (Jordan et al., 2005; Knops et al., 2005). We detected no significant differences in the whole brain, GM, or WM volumes among groups. Previous volumetric studies on preterm AGA subjects have yielded conflictive results. That is, several authors have reported significant differences in brain volumes between very low birth weight and full-term neonates at birth (Inder et al., 2005), during childhood (Soria-Pastor et al., 2009), and during adolescence (Ment et al., 2009), whereas others have found similar values in preterm and term infants evaluated at 40 weeks (Boardman et al., 2007) and very low birth weight adults (Allin et al., 2004). In a study designed to assess the impact of IUGR on preterm newborns, Tolsa et al. (2004) reported a significant reduction in ICV (16%) and in cerebral cortical GM volume (28%) in IUGR neonates, and these

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differences persisted at term CA but with less magnitude (10% and 21% respectively). In a later study, the same researchers (Dubois et al., 2008) observed lower cerebral volumes in preterm IUGR as compared to preterm AGA neonates at term CA, although the differences were less pronounced and did not reach statistical significance. The lack of differences in brain volumes between groups in our study may be in part related to the dynamic course of brain maturation during the first year of life when most of the progressive and regressive events take place (Lenroot and Giedd, 2006) characterized by a large increase in total brain volume and rapid gray matter growth (Knickmeyer et al., 2008). Our results may suggest an early deviation in the developmental trajectory of the brain tissues in the study groups reflecting the specific characteristics of this sample. Lobar volumetric analyses showed similar volumes in the frontal lobe and hippocampi between groups. This was an unexpected finding given that previous studies at older age have reported the compromise of the frontal lobe in IUGR infants (Geva et al., 2006a, Geva et al., 2006b) and hippocampus (Geva et al., 2006b). Even more, a previous study suggested that the hippocampus might be affected already in the neonatal period (Lodygensky et al., 2008). However, as discussed above in our study, the age at evaluation was remarkably different, and the differences in relative frontal volumes and hippocampus might no longer be observable at 1 year of age. Our findings may relate with developmental and self-organization processes at 12 months of age. Nevertheless, this does not rule out the presence of profound differences in brain organization, which require more accurate methods to be demonstrated. Volumetric analyses showed a significant marked relative reduction in the IL and a trend in the TL in preterm IUGR infants compared with term infants. Concerning differences in the IL, no previous volumetric studies have evaluated this particular brain structure. However, some authors have suggested that this structure has important connections with the frontal and limbic lobes, playing a major role in control of emotions, working memory and selective visual attention functions (Dappreto et al., 2006; Augustine, 1996). From this perspective the involvement of the insular lobe in preterm IUGR infants could partially explain at least in part some of the neuropsychological difficulties reported in this population (Geva et al., 2006a). The preferential involvement of the TL has been suggested in different studies that include preterm subjects with and without perinatal complications (Kesler et al., 2004). The temporal lobe may be particularly affected by preterm birth per se, as suggested by experimental

Fig. 2 – Atlas overlaid on the sagittal, coronal and axial T1-weighted images from a single subject. Individual anatomical regions are color coded.

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Table 1 – Anthropometric and demographic characteristics of the study group.

Gestational age Gender (M/F) Birth weight (kg) Length at birth (cm) Head circumference at birth (cm) Weight at 12 months' (kg) Height at 12 months' (cm) Head circumference at 12 months' (cm) Body mass index (weight/height², kg/m²) Corrected age at scan (months) Corrected age at BSID-III (months) Breast milk n (%) Maternal age Maternal education less than high school n (%)

IUGR n = 18

Preterm n = 15

Term n = 15

Linear tendency P value

32.1 ± 2.05 7/11 1.06 ± 0.31* 36.78 ± 3.82* 26.27 ± 2.19* 8.46 ± 1.35* 72.41 ± 3.75 45.81 ± 1.82 11.70 ± 1.49* 12.7 ± 0.75 17.83 ± 6.04 15/18 (83.3) 32.2 ± 3.76 8/18 (44.4)

31 ± 2.58* 11/7 1.58 ± 0.47* 39.73 ± 4.43* 28.63 ± 2.79* 9.41 ± 1.33 75.26 ± 4.11 46.60 ± 1.56 12.55 ± 1.53 12.6 ± 0.73 19.20 ± 6.08 12/15 (80.0) 32.3 ± 5.5 6/15 (40)

39.8 ± 1.05 7/11 3.34 ± 0.46 49.33 ± 1.87 34.11 ± 1.12 9.63 ± 0.72 73.10 ± 2.13 45.96 ± 1.17 12.48 ± 0.97 12.4 ± 0.91 19.67 ± 3.97 10/15 (66.7) 32.7 ± 5.1 6/15 (40)

0.000 0.290 0.000 0.000 0.000 0.000 0.570 0.780 0.000 0.250 0.340 0.26 0.790 0.070

IUGR, intrauterine growth restriction; *P < 0.05 compared with term infants; data are mean ± SD or n (%).

data in a baboon model of preterm delivery (Dieni et al., 2004) and imaging studies in low-risk preterm children (Soria-Pastor et al., 2009). In addition, an increased regional susceptibility to chronic hypoxia has been reported in IUGR animal models (Ress et al., 2008). We did not find any relationship between global brain volumes and neonatal data or developmental outcome, replicating previous findings by Kesler et al. (2008)) in preterm children at 12 years of age. However, we found positive correlations in the whole sample between decreased volumes in IL and TL and neonatal data but not for GA. This may reflect the influence of the biometric parameters on these structures despite the effect of prematurity. Concerning the relation between neurodevelopmental scores and brain lobar volumes, the exploratory analysis did not find any significant correlation. A trend between relative total insular lobe volume and adaptive behavior was observed and so it should be confirmed in a larger sample. The VBM analysis of IUGR infants identified several areas of lower GM volumes, accompanied by concomitant or

adjacent increases in WM volumes. The decreased WM volumes were less marked. Notably, comparisons between preterm AGA and term groups showed minimal differences in GM volumes with no differences in WM. The differences in GM distribution observed in IUGR subjects are in line with previous evidences (Tolsa et al., 2004) suggesting that adverse intrauterine environment induces specific effects on the fetal GM development (Laursen, 2007; Samuelsen et al., 2009; Kapellou et al., 2006; Krägeloh-Mann, 2004). In preterm infants controversy persists concerning the origin of GM volume reductions. Although the secondary disruption of GM due to WM injury has been proposed (Mathur and Inder, 2009), other studies have suggested that even without WM damage, prematurity is associated with decreased cortical GM volumes (Inder et al., 2005). Additionally, the role of environmental factors that may influence the normal development during the first year of life should be considered (Tzarouchi et al., 2009). This and previous studies highlight the importance of characterizing the population under study with regard to the presence or absence of IUGR in preterm infants.

Table 2 – Neurodevelopmental scores and global brain volume data (cm3). Characteristic Cognitive Language Receptive Communication Expressive Communication Motor Fine motor Gross Motor Social Emotional Adaptive Behavior Gray matter White matter Total brain volume

IUGR n = 18 100.83 92.72 9.22 8.50 93.72 8.83 9.28 116.39 94.78 683.71 243.50 927.21

± ± ± ± ± ± ± ± ± ± ± ±

9.27 12.96 3.07 2.64 17.31 * 3.05 * 3.69 24.18 13.97 * 64.54 36.89 98.50

Preterm n = 15 105.67 ± 94.73 ± 8.53 ± 102.20 ± 102.20 ± 10.27 ± 10.40 ± 114.47 ± 98.43 ± 713.99 ± 240.74 ± 954.73 ±

10.32 16.57 2.80 9.63 9.63 1.98 1.76 24.06 15.25 57.03 37.96 86.62

Term n = 15 108.67 95.07 8.80 110.0 110.0 11.93 11.40 118.00 107.20 702.98 239.70 942.68

± ± ± ± ± ± ± ± ± ± ± ±

12.88 13.63 2.852 17.18 17.18 2.60 4.68 26.30 12.20 77.07 32.17 104.15

Linear tendency P value 0.120 0.870 0.950 0.940 0.010 0.006 0.240 0.920 0.040 0.410 0.760 0.650

IUGR, intrauterine growth restriction; * P < 0.05 compared with term infants calculated by linear regression adjusted by maternal education and SNAPP-II. In bold, values that achieve statistical significance after Bonferroni correction.

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Table 3 – Lobar brain volume data. Region

IUGR n = 18

Preterm n = 15

Term n = 15

Linear tendency P value

3

Absolute volumes (mm ) ICV Frontal lobe Temporal lobe Parietal lobe Occipital lobe Insula Hippocampi Relative to ICV(%) Frontal lobe Temporal lobe Parietal lobe Occipital lobe Insula Hippocamppi

969.63 277.72 184.64 181.34 108.78 23.12 3.38

± ± ± ± ± ± ±

101.80 35.31 18.07 21.65 10.82 2.54 0.31

1001.08 ± 294.60 ± 193.01± 189.91 ± 113.15 ± 24.38 ± 3.49 ±

95.44 36.49 17.01 22.28 12.47 2.15 0.29

945.51 268.22 185.14 175.13 104.51 23.56 3.44

± ± ± ± ± ± ±

95.61 31.65 16.72 19.91 10.30 2.51 0.25

0.192 0.118 0.329 0.174 0.120 0.333 0.594

28.59 19.06 18.68 10.23 2.38 0.35

± ± ± ± ± ±

1.04 0.57 * 0.51 5.49 0.00 * 0.00

29.08 19.11 18.75 11.18 2.41 0.34

1.20 0.64 0.68 6.21 0.01 0.01

28.32 19.60 18.50 11.06 2.49 0.36

± ± ± ± ± ±

0.16 0.47 0.49 0.51 0.06 0.00

0.163 0.019 0.473 0.510 0.006 0.00

± ± ± ± ± ±

IUGR, intrauterine growth restriction. *P < 0.05 compared with term infants; calculated by linear regression adjusted by head circumference, age at assessment and SNAPP-II in absolute volumes and age at assessment and SNAPP-II in relative volumes. In bold, values that achieve statistical significance after Bonferroni correction.

Table 4 – Significant differences in gray and white matter volumes in the study groups. Anatomic region Gray matter results Superior temporal gyrus posterior part Precentral gyrus Middle and inferior temporal gyrus Insula Posterior temporal lobe Superior temporal gyrus posterior part Middle and inferior temporal gyrus Precentral gyrus Insula Superior parietal gyrus Superior parietal gyrus Posterior orbital gyrus Post-central gyrus Superior temporal gyrus posterior part Insula Insula Superior temporal gyrus posterior part Insula Middle frontal gyrus Superior temporal gyrus posterior part White matter results Cerebellum Hippocampus Inferiolateral reminder of PL and lateral remainder of OL Superior frontal gyrus Superior frontal gyrus Precentral gyrus Insula Middle frontal gyrus Superior temporal gyrus posterior part Insula Superior temporal gyrus posterior part R, right; L, left.

Hemisphere

Contrast

Cluster mm3 Cluster level P corrected

t

R

IUGR
36291

0.000

7.52

L

IUGR
37966

0.000

6.73

R L R L

IUGR
5642 1825 2592 3587

0.000 0.002 0.000 0.000

6.49 5.72 5.2 4.64

L R

IUGR
1471 1644

0.008 0.004

4.47 5.25

L L

IUGR
2133 2085

0.001 0.001

4.73 5.74

L L L R L L

IUGR< term IUGR< term IUGR>term IUGR>term IUGR>term IUGR>term

1222 722 1237 1314 1123 1560

0.008 0.06 0.007 0.005 0.01 0.002

5.43 5.25 5.01 5.20 4.47 4.68

R

IUGR>preterm

1295

0.005

5.40

L

IUGR>preterm

846

0.03

4.42

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In terms of WM distribution, significant differences were again detected only in IUGR infants as increased volumes in several regions and decreased volumes in some other regions. Similar results have been presented (Nosarti et al., 2002; Allin et al., 2004) in preterm-born adolescents and adults born with very low birth weights, respectively. It bears noting that WM increments in these studies and the present study were detected in areas with concomitant or adjacent GM decrease. The areas of decreased WM comprised the cerebellum and the hippocampus, in agreement with previous findings in experimental models of fetal growth restriction (Schober et al., 2009; Ress et al., 2008) and IUGR neonates (Lodygensky et al., 2008), which have speculated that these particular structures are more vulnerable to hypoxic conditions and stress hormones. These patterns of abnormal GM and WM distribution are proposed to reflect abnormal architecture and connectivity (Allin et al., 2004; Sowell et al., 2001). Alterations in GM and WM distribution might involve regressive (programmed cell death and synaptic pruning) and progressive (dendrite elaboration, synapses formation, myelination) events, which occur simultaneously in the brain (Knickmeyer et al., 2008; Graaf-Peters and Hadders-Algra, 2006; Huttenlocher and Dabholkar, 1997) during childhood, adolescence, and young adulthood and could be disturbed by adverse perinatal events (Mathur and Inder, 2009; Samuelsen et al., 2007).

We found significant positive correlations between regional GM volumes and motor, fine motor and adaptive behavior within the preterm IUGR group. Regarding the analysis of motor performance, we detected a striking correlation with GM volume in the parietal and frontal cortex. These results are in line with studies that have demonstrated the role of bilateral parietal cortex during motor imagery, which involves the conscious internal representation of movement and space-based attention (Fleming and Stinear, 2010; Wagner et al., 2005). Additionally, the superior-frontal gyrus is thought to contribute to higher cognitive functions, particularly related to spatial oriented processing and working memory (du Boisgueheneuc et al., 2006; Fleming and Stinear, 2010). The most noteworthy strength of the current study is that it was performed in well-defined cohorts characterized prenatally and followed prospectively, and the definition of preterm IUGR included antenatal Doppler findings. Aside from preterm GA-matched controls without IUGR, the comparison with the terms infants-group allowed a better assessment of the differential associations between preterm birth, IUGR, and neurodevelopmental disturbances. On the other hand, we acknowledge that this study has some limitations, as the relatively small sample size may have prevented statistical differences to be discerned, thereby preventing us for generalizing to a wider sample. Also, we

Fig. 3 – Axial section of images illustrating both gray matter volume reductions (warm colors) and white matter volume increases (cool colors) between IUGR and term infants (a) and GM decreases between AGA and term infants (b). The color bar represents the t scores. Display orientation: neurological convention. Differences are mapped on the mean template of our sample.

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lack information on non-formula food in the first year of life, and we recognize that poses a limitation of this study and should be taken into account in the design of future studies. Concerning MRI studies, we are aware that tissue segmentation in the 1-year-old brains is considered a challenging task due to the isointense developmental pattern which results in a poor differentiation between GM and WM (Paus et al., 2001). To minimize this limitation, we only used high-quality T1 weighted 3-Tesla Magnetic Resonance images for segmentation (Knickmeyer et al., 2008) and to guide the segmentation we used appropriate brain tissue probability maps (Altaye et al., 2008). Finally, each scan was reviewed by an anatomical expert to determine if the results of the tissue segmentation were accurate (Knickmeyer et al., 2008). Despite these efforts, we are fully aware that a quantitative validation of the segmentation would help resolve the possibility of a systematic error in the results.

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4.

Experimental Procedures

informed consent was obtained from the parents of each child to participate in the research study. Prenatal and neonatal data were prospectively recorded, including gestational age (GA), Apgar at 5 min; umbilical artery pH, Score for Neonatal Acute Physiology version-II (SNAP-II), late-onset sepsis, necrotizing enterocolitis, chronic lung disease (defined as oxygen need at 36 weeks postmenstrual age) prenatal and postnatal steroids. Growth parameters (BW, length, and head circumference – HC) and parental education (low, intermediate or high) were also recorded. Neonatal ultrasound findings were recorded. All participants underwent neonatal ultrasound using the same protocol, consisting on brain ultrasound (US) scans by expert neurosonographers on the third (US-1) and fourteenth days (US-II) after delivery and at term-equivalent age (US-III) as previously published (Padilla-Gomes et al., 2007). US images were obtained with an Antares ultrasound equipment (Siemens Medical Systems, Malvern, PA) using an 8–5 MHz sector transducer. Examination included eight coronal scans, one mid-sagittal and three parasagittal views through the anterior fontanelle.

4.1.

Participants

4.2.

This study is part of a larger prospective research program on IUGR involving fetal assessment and short- and long-term postnatal follow-up at the Hospital-Clinic (Barcelona-Spain). The study design involved recruitment of a consecutive sample of 60 neonates, all born between 2006 and 2007: 20 singleton premature infants with severe IUGR diagnosed before 34 weeks of gestation; 20 preterm infants with birth weight (BW) appropriate for gestational age (AGA), matched one-to-one for gestational age (GA) at delivery (±2 weeks); and 20 healthy full-term infants. Recruitment was prenatal in IUGR cases and at birth in the other two groups. Pregnancies were dated according to the first-trimester crown-rump length measurements (Robinson and Fleming, 1975). IUGR was defined as a fetal weight below the 10th percentile for GA confirmed at birth, and an abnormal Doppler blood flow in the umbilical artery (pulsatility index > 2 standard deviations). Preterm AGA cases were defined as a BW between the 10th and 90th customized centiles according to local reference standards. Infants with chromosomal, genetic or structural defects and signs of intrauterine infection or neonatal earlyonset sepsis were excluded from this study. The study protocol and the recruitment and scanning procedures were approved by the Institutional Ethics Committee, and written

Neurodevelopmental assessment

Neurodevelopmental outcome was assessed at 18 months CA (±2 months) with the Bayley Scale for Infant Development-III (BSID-III), which evaluates five distinct scales: cognitive; language, with a receptive and expressive communication subtest; motor, with fine and gross motor subtests; socioemotional behavior; and adaptive behavior. Average BSID-III scores in healthy infants and children are 100 ± 15. The subtests were evaluated in scalar scores considering >7 a normal value.

4.3.

MRI data acquisition and image analysis

Children in all groups were scanned at 12 ± 2 months CA, sleeping naturally. MRI was performed on a TIM TRIO 3.0 T scanner (Siemens, Erlangen-Germany). A set of high-resolution T1-weighted, 3D images, was acquired using the Magnetization Prepared Rapid Acquisition Gradient Echo sequence (MPRAGE) (TR/TE = 2050 ms/2.41 ms; TI =1050 ms; FOV= 220 × 220 mm and 256 × 256 matrix; scan time= 5:52 min). The whole-brain data were acquired in a sagittal plane, yielding contiguous slices with isotropic voxel of 0.9 × 0.9 × 0.9 mm³. MRI-DTI and spectroscopy were acquired also to be analyzed in future studies. The total acquisition time was 30 min. The

Fig. 4 – Correlation between GM volume and motor score in the left precuneus (crosshairs) and the left frontal-superior gyrus (black arrow) (corrected P < 0.05). The color bar represents the t scores. Display orientation: neurological convention.

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MRI scans were reviewed by a neuroradiologist (NB) blinded to group membership. The images were processed using SPM5 software (Statistical Parametric Mapping, http://www.fil.ion. ucl.ac.uk/spm) running in Matlab 7.5 (MathWorks, Natick, MA). A single investigator (NP) completed the prior manual steps. Line determination of the anterior–posterior commissures and image reorienting were performed.

4.3.1.

Lobar volumetry

The regions of interest comprised the frontal lobe (FL), temporal lobe (TL), parietal lobe (PL), occipital lobe (OL), insular lobe (IL) and hippoccampus. To measure brain volumes, we used previously published 3-D anatomical atlases and the corresponding MRI data of 33 premature infants (Gousias et al., 2008) adapted to our sample (Gousias et al., 2010; Shi et al., 2010). The 2-year-old infants included in the atlases had a mean age of 24.8 months, median 24.1 months ( range 21.4–34.4 months) and a standard deviation 2.4 months. The images of this cohort were acquired using a 1.0 T HPQ (TR/ TE = 23 ms/6 ms, FOV = 265 mm and 256 × 256 matrix; voxel size 1.04 × 1.04 × 1.6 mm³.

4.3.1.1. Brain segmentation and normalization of the atlases into a standard space. The first step of this procedure required the segmentation into GM, WM and cerebral spinal fluid (CSF) of the T1 structural MRI images of 48 infants from our sample and 33 infants from atlases. For this purpose, the VBM5 toolbox (http://dbm.neuro.uni-jena.de) was utilized using the infant brain probability templates of 12 months provided by Altaye et al. (2008). In this way, the images for all subjects were transformed into a standard space. All scans were reviewed by an anatomical expert to determine if the results of the tissue segmentation were accurate (Fig. 1). In a second step the 33 atlases were standardized applying the normalization transformation that resulted from the corresponding T1 image segmentation. Voxel sizes 1 × 1 × 1 mm3, and nearest neighbor interpolation was applied.

4.3.1.2. Decision fusion process. As described by Gousias et al. (2008) each resulting label image assigns a structure level to every voxel in the corresponding MR image volume. To combine the information of the 33 normalized atlases, we applied voterule based decision fusion (Heckemann et al., 2006; Gousias et al., 2008). The consensus class of each voxel was defined as the modal value of the distribution of the individual label assignments (Gousias et al., 2008; Hammers et al., 2003; Kittler et al., 1998). This procedure allowed us to combine the segmentation results from 33 multiple subject-specific atlases in a single atlas. 4.3.1.3. Atlas into the space of each target subject. The standardized atlas generated in the previous step was then warped back to every 1-year subject of our sample by mean of inverse normalization parameters that resulted from the corresponding T1 image segmentation. Visual inspection was performed for each subject by observing whether the atlas projected properly over the corresponding T1 weighted scan (Fig. 2). 4.3.2.

Volume quantification

Within the atlas a number between 1 and 83 identified each structure composed by GM and WM in the label volumes. The

volume of each structure was determined by using a proper script written in MATLAB 7.5 selecting the region of interest via its voxel value. The volume of each brain lobe was determined by summing the volume of their components. Lobar volumes were normalized by intracranial volume (ICV = sum of brain lobes, posterior fossa, central structures, and ventricles) to calculate the ratio of anatomical regions relative to the full brain (Knickmeyer et al., 2008). Analyses between groups were performed for both absolute and relative volumes. As suggested elsewhere (Knickmeyer et al., 2008), the normalization by the ICV was performed to ascertain the effect of IUGR beyond a simple biometric restriction.

4.3.3.

Voxel-based morphometry

Voxel-based morphometry was implemented in SMP5 using the VBM5 toolbox. This toolbox extends the unified segmentation model (Ashburner and Friston, 2005) as it increases the quality of segmentation by applying a Hidden Markov Random Field model on the segmented tissue maps (Cuadra et al., 2005). As previously explained T1-weighted images were segmented into GM, WM and CSF and were then normalized. The final tissue maps of GM, WM and CSF were modulated with the Jacobian determinants of the deformation parameters obtained by normalization to the standard space in order to evaluate volume differences between study groups. Probability tissue maps were smoothed with an 8-mm of fullwidth at half-maximum (FWHM) isotropic Gaussian kernel. Global GM and WM volumes, and total brain volume (TBV = GM + WM) were calculated using the native-space tissue maps of each subject. A specific value in mm3 was found for each tissue. The adapted atlas of a control subject was used to visually define the anatomic differences.

4.3.4.

Statistical analyses

For quantitative variables, the data were checked for normality before each analysis. Comparisons between groups were performed by analysis of variance (ANOVA), where a polynomial contrast was constructed to test the hypothesis of linear differences between groups. Categorical variables were analyzed by X2-Pearson and linear differences by the linear-tolinear test. Partial correlations were used to evaluate associations in neonatal, neurodevelopmental and MRI data. Analyses were adjusted by HC, age at assessment, SNAPP-II and maternal education as appropriate. All statistical analyses were carried out using the SPSS 17.0 (SPSS Inc, Chicago, IL). A P < 0.05 was considered statistically significant. To account for multiple comparisons Bonferroni correction was considered. For VBM analyses t-test group comparisons were performed to evaluate the GM and WM volume changes between groups (contrasts: IUGR < term and IUGR > term; IUGR < preterm and IUGR > preterm; preterm < term and preterm > term) Two analyses were made, first including all the subjects and secondly, excluding the subjects with evidence of periventricular leukomalacia (PVL) according to neonatal ultrasound. Intraventricular hemorrhage was not included in these analyses because there were too few infants with this diagnosis. A “simple regression” (correlation) analysis was performed to test for a possible relationship between regional GM and WM volumes and neurodevelopmental scores for each group separately. For statistical purposes, clusters surviving a

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P value of <0.05 family-wise error rate corrected for multiple comparisons were reported. For the results to be displayed, a threshold at an uncorrected voxel P value of <0.001 was considered. The adapted atlas of a control subject was used to define visually the anatomic differences.

5.

Conclusions

This study complements earlier evidence in preterm newborns suggesting that the association with IUGR can result in specific structural brain and developmental differences at 12 months CA. Our findings suggest that at globally IUGR is associated with reduced insular lobes and temporal lobes and regionally both WM and especially GM volumes abnormalities are present. Additionally in several areas, GM abnormalities are associated with neurodevelopmental difficulties. These findings suggest that IUGR induces an early deviation in the developmental trajectory of the brain reflecting the specific characteristics of this condition. The results of this study warrant further investigation with longer postnatal follow-up and other MRI modalities in order to refine the understanding of abnormal neurodevelopment in preterm patients with IUGR and to identify clinically useful biomarkers.

Acknowledgments Funding support was provided by grants from the Cerebra Foundation for the Brain-Injured Child (Carmarthen, Wales, UK), the Thrasher Research Fund (Salt Lake City, USA), Marie Curie Host Fellowships for Early Stage Researchers (FETALMED-019707-2) and the Spanish Fondo de Investigaciones Sanitarias (FIS-06/0347). NP, EE and FC were supported by a Sara Borrell postdoctoral fellowship (CD09/00263), ISCIIIMICINN, an Emili Letang fellowship (Hospital-Clinic) and Rio Hortega pre-doctoral fellowship, respectively. The authors would like to thank Cesar Garrido for imaging acquisition, Dafnis Batallé for generating the fusion of the atlases and Eloy Martinez for making the statistical analysis of the atlases.

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