Effects of variations in gestational age and birth anthropometric indicators on diffusion metrics of term neonatal white matter: a cohort study
Chao Jin1, Yanyan Li1, Xianjun Li1,2, Miaomiao Wang1, Jie Gao1, Qinli Sun1, and Jian Yang1

1Department of Radiology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi'an, China, People's Republic of, 2Department of Biomedical Engineering, School of Life Science and Technology, University of Xi'an Jiaotong, Xi'an, China, People's Republic of

Synopsis

During the life span, brain development would be affected by numerous intra- and inter- factors in a short- or/and long-term period. To reveal typical birth indicators’ short-term effects, the effects of gestational age (GA), birth weight, crown-heel length and head circumference on term neonatal white matter were investigated by DTI. Results indicate that term neonates born with higher GA, birth weight and crown-heel length may hint better maturation of brain microstructure; among four birth indicators, GA was the main factor that influenced DTI-metrics. Particularly, longer crown-heel length with leftward superiority in corona radiata may presumably support early motor function.

Introduction

During the lifespan, brain development in neonates undergoes rapid growth and microstructure maturation1. Previous large cohort studies have revealed that variation in gestational age (GA) and birth weight show long-term effects on later cerebral growth, development and maturation, such as IQ2, neuropsychological functioning3, brain volume4 and etc. Beyond, PMA-associated short-term effects indicated that for preterm infants at term age, higher PMA (postmenstrual age) may hint better maturation of brain microstructure5. However, little is known about the short-term effects of other typical birth indicators e.g. birth weight, crown-heel length and head circumference on early brain development. Therefore, this study aims to assess the effects of variations in gestational age (GA) and three birth anthropometric indicators (i.e. birth weight, crown-heel length and head circumference) on diffusion metrics of term neonatal white matter (WM).

Methods

The Internal Review Board approved this study and all the written informed consents were obtained. Patients Of 212 neonates recruited, 53 term neonates with no evidence of brain abnormality on MRI were included and scanned by DTI within 18 days after birth; here a within 18 days after birth was presumed as a close to in-uterine period6. (Table 1) MR Protocols All MR examinations were performed using a 3T scanner (GE, Signa HDxt). The protocols included: (1) a transverse 3D T1-weighted sequence (TR/TE, 10ms/4.6ms; matrix, 256×256; section-thickness, 1mm; FOV, 240mm); (2) a T2-weighted sequence (TR/TE, 4200ms/120ms; matrix, 256×256; section-thickness, 4mm; FOV, 180mm); (3) DTI (35directions; b-value, 1000s/mm2; TR/TE, 5500ms/95ms; section-thickness, 4mm; FOV, 180mm). Data and statistical analysis DTI data was processed with the aid of the FMRIB software library (FSL, www.fmrib.ox.au.uk/fsl). Firstly, to eliminate GA-associated impacts, three birth anthropometric indicators were adjusted based on GA by the linear regression. (Table 1) Then, TBSS was used to investigate the effects of GA and three adjusted anthropometric indicators on DTI-derived metrics (i.e. FA, AD, MD and RD), with postnatal days at-scan and sex as confounders. Multiple linear regression analyses were further performed to determine the main contribution to changes in DTI metrics among the four birth indicators.

Results

Three typical birth indicators, including GA, adjusted birth weight and adjusted crown-heel length showed statistically significant associations with the increasing FA and decreasing MD in whole or regional white matter (rmax=0.73, p<.001); whereas as adjusted head circumference increased, values of FA and AD remained unchanged while MD and RD statistically increased in regional white matter, e.g. optic radiation, posterior limb of internal capsule, corona radiate and genu of corpus callosum (rmin=-0.38, p=0.008). Notably as to AD and RD, negative significant correlations were found in terms of GA and adjusted birth weight (rmin=-0.69, p<.001); However, RD value statistically decreased with increment of adjusted crown-heel length, while AD was unchanged. Besides, the changes of DTI metrics in most white matter were bilateral, whereas that of crown-heel length (i.e. FA value) was found predominantly in the left corona radiata. Additionally, the multiple linear regression analysis demonstrated that GA was the main factor that influenced DTI metrics of term neonates within 18 days after birth.

Discussion

For term neonates during a close to in-uterine period, as GA increased, FA value increased while values of AD, MD and RD decreased in the whole WMs. Such changes of DTI metrics may suggest the maturation of WM microstructure, detailed as increased axon density, myelination and decreased water content1. Therefore, it may be the above changes that led to the changes of DTI metrics in the majority of whole WMs 1. Besides, both higher adjusted birth weight and longer adjusted crown-heel length were correlated with higher FA and lower MD that may hint better maturation of brain microstructure. Regardless of underlying mechanisms, hemispheric asymmetry of FA distribution was further observed in both two birth indicators. Particularly, FA distribution of adjusted birth crown-heel length showed obviously leftward lateralization in corona radiate, that may presumably support the increased development of neonatal motor ability. Beyond, as for head circumference, the increased MD and RD in regional WMs may hint the enlargement of axons; although being associated with neurodevelopmental outcome in 2yr childhood7, no changes of FA values may suggest weak short-term effect on brain maturation.

Conclusion

During a close to in-utero period, term neonates born with higher typical birth indicators like GA, birth weight and crown-heel length correlated with higher FA and lower MD that may hint better maturation of brain microstructure. Among the four birth indicators, GA was the main factor that influenced DTI metrics. Particularly, longer crown-heel length with leftward superiority in corona radiata may presumably support early motor function.

Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (No.81171317 & 81471631) and the 2011 New Century Excellent Talent Support Plan from Ministry of Education of China (NCET-11-0438).

References

1. Dubois J, et al. Assessment of the early organization and maturation of infants’ cerebral white matter fiber bundles: a feasibility study using quantitative diffusion tensor imaging and tractography. Neuroimage, 2006, 30(4): 1121-1132.
2. Matte T D, et al. Influence of variation in birth weight within normal range and within sibships on IQ at age 7 years: cohort study. BMJ, 2001, 323(7308): 310-314.
3. Wade M, et al. Normal birth weight variation and children’s neuropsychological functioning: links between language, executive functioning, and theory of mind. J Int Neuropsychol Soc, 2014, 20(09): 909-919.
4. Walhovd K B, et al. Long-term influence of normal variation in neonatal characteristics on human brain development. Proc Natl Acad Sci, 2012, 109(49): 20089-20094.
5. Rose J, Vassar R, Cahill-Rowley K, et al. Brain microstructural development at near-term age in very-low-birth-weight preterm infants: an atlas-based diffusion imaging study. Neuroimage, 2014, 86: 244-256.
6. Broekman B F P, et al. Gestational age and neonatal brain microstructure in term born infants: a birth cohort study. PloS one, 2014, 9(12): e115229.
7. Cheong JL, Hunt RW, Anderson PJ, et al. Head growth in preterm infants: correlation with magnetic resonance imaging and neurodevelopmental outcome. Pediatrics, 2008, 121 (6): e1534-1540.

Figures

Figure 2. Correlations between diffusion metrics (i.e. FA, AD, MD and RD) and (A) gestational age, (B) birth weight, (C) birth crown-heel length, (D) birth head circumference. Label green indicates the fibrous skeleton of brain white matter; the warm-toned and cool-toned labels indicate the positive and negative correlations, respectively.

Table 1. Participant demographics

Table 2. Multiple linear regression analysis of factors related to diffusion metrics at selected ROIs of neonatal brain white mattera



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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