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Preterm infants’ early growth and brain white matter maturation at term age

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Preterm infants’ early growth and brain white matter maturation at term age
  See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/257381658 Preterm infants’ early growth and brain whitematter maturation at term age  Article   in  Pediatric Radiology · October 2013 DOI: 10.1007/s00247-013-2699-9 CITATION 1 READS 68 9 authors , including: Some of the authors of this publication are also working on these related projects: FinAdo, Finnish Adoption Study   View projectClose Collaboration with Parents Training Program   View projectHelena LapinleimuTurku University Hospital 115   PUBLICATIONS   1,884   CITATIONS   SEE PROFILE Leena HaatajaUniversity of Helsinki, Helsinki, Finland 79   PUBLICATIONS   1,452   CITATIONS   SEE PROFILE Paivi RautavaTurku University Hospital 172   PUBLICATIONS   2,645   CITATIONS   SEE PROFILE Riitta ParkkolaUniversity of Turku 160   PUBLICATIONS   3,102   CITATIONS   SEE PROFILE All content following this page was uploaded by Paivi Rautava on 04 December 2016. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the srcinal documentand are linked to publications on ResearchGate, letting you access and read them immediately.  ORIGINAL ARTICLE Preterm infants ’  early growth and brain white mattermaturation at term age Virva Lepomäki  &  Marika Leppänen  &  Jaakko Matomäki  &  Helena Lapinleimu  & Liisa Lehtonen  &  Leena Haataja  &  Markku Komu  &  Päivi Rautava  & Riitta Parkkola  &  the PIPARI study group Received: 29 October 2012 /Revised: 4 February 2013 /Accepted: 27 March 2013 # Springer-Verlag Berlin Heidelberg 2013 Abstract  Background   Normal intrauterine conditions are essential tonormal brain growth and development; premature birth andgrowth restriction can interrupt brain maturation. Maturation processes can be studied using diffusion tensor imaging. Objective  The aim of this study was to use tract-basedspatial statistics to assess the effect that early postnatalgrowth from birth to 40 gestational weeks has on brainwhite matter maturation.  Materials and methods  A total of 36 preterm infants wereaccepted in the study. Postnatal growth was assessed byweight, length and head circumference. Birth weight z-scoreand gestational age were used as confounding covariates.  Results  Head circumference catch-up growth was associat-ed with less mature diffusion parameters (  P  <0.05). Nosignificant associations were observed between weight or length growth and diffusion parameters. Conclusion  Growth-restricted infants seem to have delayed brain maturation that is not fully compensated at term,despite catch-up growth. Keywords  Diffusiontensorimaging .Tract-basedspatialstatistics .Catch-upgrowth . Neonate Introduction Intrauterine conditions are vital for normal brain growthand development  [1]. Premature birth and its conse- quences can interrupt ongoing microscopic maturation processes in the brain, such as organisational eventsand myelination [2], in addition to volumetric changes.The most common neuropathological finding is focal anddiffuse white matter injury [3]. Preterm infants, especial- ly those with intrauterine growth restriction or severe brain injuries, are at risk of developmental impairments[4, 5]. Our previous studies have shown that intrauterine  placental insufficiency and fetal blood flow redistributionlead to reduced total brain volumes [6] and lower cog-nitive performance at 2 years of age [7].Studies have shown that the magnitude of earlyweight gain before discharge is associated with better neurodevelopmental outcome [8  –  10]. Also, head circum-ference catch-up growth from birth to discharge in verylow birth weight (birth weight <1,501 g) [10, 11] and in extremely low birth weight (birth weight <1,001 g) V. Lepomäki : M. Komu : R. Parkkola Medical Imaging Centre of Southwest Finland, Turku UniversityCentral Hospital, Turku, FinlandV. Lepomäki ( * ) :  R. Parkkola Turku PET-Centre, Turku University Hospital, PO Box 52,20521 Turku, Finlande-mail: vikale@utu.fiM. Leppänen : J. Matomäki :  H. Lapinleimu :  L. LehtonenDepartment of Pediatrics, Turku University Hospitaland University of Turku, Turku, FinlandL. Haataja Department of Pediatric Neurology, Turku University Hospitaland University of Turku, Turku, FinlandR. Parkkola Department of Diagnostic Radiology, University of Turku,Turku, FinlandP. Rautava Department of Public Health, University of Turku, Turku, FinlandP. Rautava Turku Clinical Research Centre, Turku University Hospital,Turku, FinlandPediatr RadiolDOI 10.1007/s00247-013-2699-9   preterm infants [8] is associated with more favourableneurodevelopmental outcomes in childhood. The under-lying functional mechanisms behind the positive effectsof somatic growth on brain development have not yet  been clarified.Brain maturation can be studied using diffusion tensor imaging (DTI) [12  –  15]. Diffusion reflects brain maturation processes such as myelination and organisation of axons inwhite matter [16  –  19]. The two most commonly used DTI parameters to assess white matter maturation are fractionalanisotropy and mean diffusivity. Normal white matter mat-uration is characterised by increasing the fractional anisot-ropy values and decreasing the mean diffusivity values[20  –  22]. More recent studies have also used axial and radialdiffusivity to assess white matter microstructure [23]. Axialdiffusivity is the diffusivity parallel to the fibre bundles,while radial diffusion is the diffusion perpendicular to fibre bundles. Axial diffusivity and radial diffusivity provideadditional information about white matter; for example,increasing fractional anisotropy with age is driven by a decrease in radial diffusivity [24  –  26].Our previous study showed that good prenatal growth isassociated with better white matter maturation. We showedthat small for gestational age (birth weight z-score < − 2)infants have lower fractional anisotropy and higher meandiffusivity than appropriate-for-gestational age (birth weight z-score between  − 2 and +2 SD) infants [27].The aim of the present study was to assess the effect of early postnatal growth from birth to term age on brain whitematter maturation using tract-based spatial statistics in pre-term infants. Materials and methods SubjectsThis study is a part of the Development and Functioning inVery Low Birth Weight-Infants from Infancy to School Age(PIPARI) study conducted at Turku University Hospital.The inclusion criteria for this study were: (1) gestation-al age younger than 32 weeks or very low birth weight and (2) imaging with a 1.5-T magnetic resonance imaging(MRI) system at term age (40 gestational weeks). The brain imaging for this study was performed between June2004 and December 2006. A total of 132 infants met theinclusion criteria. The exclusion criteria were: (1) theinfant had died during neonatal period ( n =17); (2) major congenital anomalies or recognised syndromes ( n =2); (3)major brain pathology (intraventricular hemorrhage,grades 3  –  4; haemorrhage of the brain parenchyma; whitematter cysts; abnormal signal intensities in the T1- or T2-weighted images in the cortex, the basal ganglia, thethalamus, the cerebellum or the internal capsule; abnor-mality of the corpus callosum; an extracerebral spacewidth of 6 mm or more; and ventriculitis) in conventionalMR images ( n =16); (4) DTI that was incorrectly imagedor not imaged at all ( n =21); (5) movement artefacts in DTimages ( n =20); (6) infants lived outside the hospital dis-trict ( n =2), (7) parents did not speak Finnish or Swedish( n =5) and (8) families refused to participate ( n =9). Atotal of 40 preterm infants were accepted for the study;the data analysis registration process failed in 3 infantsand 1 infant had missing clinical data. The final study population consisted of 36 preterm infants. Perinatalcharacteristics of infants are presented in Table 1. Themyelination status, confirmed by conventional imaging,at term age was not delayed in our preterm study cohort.Excluded infants were more immature, smaller andhad a higher incidence of bronchopulmonary dysplasia (  P  <0.05) than included infants when background vari-ables presented in Tables 1 and 2 were tested. The study  protocol was approved by the Ethics Review Committeeof the Hospital District of South-West Finland. All fami-lies provided informed consent.Growth analysisPostnatal growth velocity was characterised as a differencein weight, length and head circumference z-scores between birth and term age in relation to postnatal age in weeks. Theinfants were measured at birth and at term age as part of their routine care and follow-up. We calculated z-score todescribe the number of standard deviations scores (SDs) bywhich the measured values of the weight, length and headcircumference differed from the mean of gender and age- Table 1  Neonatal and maternal characteristics of the study cohort  Infants ( n =36)Maternal age (years) mean ± SD 31.5±5Pre-eclampsia ( n  [no/mild/severe]) 29/1/6Chorioamnionitis ( n  [no/yes]) 26/10Antenatal steroids ( n  [no/yes]) 2/34Cesarean section ( n  [no/yes]) 13/23Gestational age at birth ([weeks] mean ± SD) 30.4±1.9Umbilical artery pH ≥ 7.00 ( n ) 35Apgar score (5 min) (Median [lower quartile,upper quartile])8 (7, 9)Postnatal steroids ( n  [no/yes]) 36/0Gestational age at MRI (weeks) mean ± SD 39.9±0.4 Pediatr Radiol  specific Finnish national growth charts at birth and at termage [28, 29]. The z-score change rate was calculated be- tween birth and term age and divided by postnatal age inweeks to minimise variation caused by differences in gesta-tional age. The z-score change rate was used as a continuousvariable and the z-score of birth weight was used as a confounding covariate in statistical analysis to study associ-ation between early postnatal growth and brain maturationmeasured by DTI at term age.To further assess growth, two groups were formed based on early postnatal growth velocity of head circum-ference between birth and term age. In the first group,infants had rapid postnatal growth of head circumference(z-score change >0) and in the other group, infants hadslow postnatal growth of head circumference (z-scorechange <0).MRI and data analysisImaging was performed with a 1.5-T MRI system(Gyroscan Intera CV Nova Dual; Philips Healthcare,Best, the Netherlands) with a SENSE head coil. MRIwas performed during postprandial sleep without any phar-macological sedation at term age. The infants were swad-dled to calm them and to reduce movement artefacts in theimages. A pulse oximeter was used routinely during MRI.A physician attended the examination to monitor the in-fant, if necessary. Ear protection was used (3M DisposableEar Plugs 1100; 3 M, Brazil; and Wurth Hearing protector art.-Nr. 899 3000 232, Wurth, Austria).The sequence used for diffusion-weighted imaging wasa single-shot echo planar imaging (EPI) with SENSE.SENSE reduction was 2. The slice thickness was 5 mm,with gaps between slices of 1 mm. A 200-mm square fieldof view (FOV) was used. The imaging matrix was 111×89and the reconstructed voxel size was 0.78 mm×0.78 mm.The number of signal averages was 2 and the EPI factor was 47. Repetition time (TR) was the shortest possible(minimum 2,264 ms) and echo time (TE) was 68 ms. The b  values were 0, 600 and 1,200 s/mm 2 with 15 directions.Fat suppression was conducted using spectral presaturationwith inversion recovery (SPIR). In addition to the diffusiontensor data set, the imaging protocol included conventionalT1, T2 and FLAIR images.Data processing was performed using FSL 4.1.7 [30]. Data was corrected for eddy currents and motion [31]. Fractional anisotropy, mean diffusivity, axial diffusivityand radial diffusivity maps were calculated using Func-tional Magnetic Resonance Imaging of the Brain(FMRIB) ’ s Diffusion Toolbox (FDT) and fslmaths, whichare part of the FSL. Tract-based spatial statistics was performed as described earlier  [32]. A study-specific target was used because an infant target is not includedin the FSL. Image registrations to target were confirmedusing visual inspection. A threshold value of 0.2 wasused in the analysis. Statistical analysis was performed Table 2  Characteristics of in-fants with rapid and slow postnatal growth of head cir-cumference. Rapid growth of head circumference: z-scorechange of head circumference>0 between birth and full termage; slow growth of head cir-cumference: z-score change<0 between birth and term age;small for gestational age (birthweight z-score < − 2)*Statistically significant differ-ence (  P  <0.05) between thesegroups Rapid postnatal growthof head circumference( n =25) mean (min, max)or %Slow postnatal growthof head circumference( n =11) mean (min, max)or %Gestational age (weeks + days) 30+5 (26+1, 33+6) 29+5 (26+5, 31+4)Birth weight (g) 1,426 (840, 1,970) 1,454 (790, 2,120)Birth length (cm) 40.8 (35, 45) 40.9 (35, 46.5)Birth head circumference (cm) 28.1 (23.5, 30.5) 28.5 (23, 32)Birth weight z-score  − 1.4 ( − 4.1, 1.1)*  − 0.1 ( − 1.8, 2.6)*Birth length z-score  − 0.2 ( − 3.6, 2.8) 1.1 ( − 1.4, 3.0)Birth head circumference z-score 0.0 ( − 3.7, 1.9)* 0.0 ( − 1.3, 2.2)*Small for gestational age (%) 24% 0%Weight z-score at gestational week 40  − 1.1 ( − 4.4, 1.3)  − 0.5 ( − 2.5, 0.9)Length z-score at gestational week 40  − 0.4 ( − 3.3, 2.0)  − 0.4 ( − 1.9, 0.7)Head circumference z-score at gestationalweek 400.1 ( − 2.4, 2.4) 0.0 ( − 1.9, 1.4)Z-score change in head circumference between birth and gestational week 400.9 (0.1, 2.2)*  − 0.8 ( − 1.8, 0.0)*Bronchopulmonary dysplasia (%) 0% 9.1% Necrotizing enterocolitis (%) 4% 9.1%Sepsis/meningitis (%) 12% 0% Pediatr Radiol  using a randomised tool with 5,000 permutations.Threshold-free cluster enhancement was used in theanalysis to enhance cluster-like structures without hav-ing to define an initial cluster-forming threshold or carryout a large amount of data smoothing [33]. Association with  P  <0.05 (corrected for multiple comparisons) wasconsidered as statistically significant. Areas were identi-fied using the John Hopkins University (Johns HopkinsUniversity) White-Matter Tractography Atlas.The comparisons between two categorical variables were performed using Fisher exact test. Continuous variableswere compared between the two groups based on different  postnatal head circumference growth rate (Table 2) and between included and excluded infants (characteristics inTables 1 and 2) using independent sample  t  -test. Results In the tract-based spatial statistics analysis, a significant negative association (  P  <0.05) was observed between z-scorechange rate of head circumference and the fractional anisotro- py values. A significant positive association (  P  <0.05) wasobserved between rapid postnatal growth of head circumfer-ence and the mean diffusivity, axial diffusivity and radialdiffusivity values. The z-score of birth weight was used as a confounding covariate.For the fractional anisotropy 1 cluster (29,292 voxels), a significant negative association (  P  <0.05) to z-score changerate of head circumference was found in the forceps major and forceps minor and bilaterally in the anterior thalamicradiation, corticospinal tract, cingulum (cingulate gyrus),cingulum (hippocampus), inferior fronto-occipital fascicu-lus, inferior longitudinal fasciculus, superior longitudinalfasciculus, uncinate fasciculus and superior longitudinalfasciculus (temporal part) (Fig. 1).For the mean diffusivity 1 cluster (25,760 voxels), a significant positive association (  P  <0.05) to z-score changerate of head circumference was found in the forceps major and forceps minor and bilaterally in the anterior thalamicradiation, corticospinal tract, cingulum (cingulate gyrus),cingulum (hippocampus), inferior fronto-occipital fascicu- Fig. 1  Fractional anisotropyand head circumference catch-up growth. A negativeassociation was found betweenhead circumference catch-upgrowth and fractionalanisotropy. Areas withsignificant difference (  P  <0.05) between groups are shown in red  . Three main white matter tracts are shown with  arrows : white arrows  forceps major,  red arrows  forceps minor,  greenarrows  right corticospinal tract Pediatr Radiol
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