Andrew Melbourne1, Eliza Orasanu1, Zach Eaton-Rosen1, Joanne Beckmann2, Alexandra Saborowska3, David Atkinson3, Neil Marlow2, and Sebastien Ourselin1
1Medical Physics and Biomedical Engineering, University College London, London, United Kingdom, 2Institute for Women's Health, University College London, London, United Kingdom, 3University College Hospital, London, United Kingdom
Synopsis
This work investigates the appearance of the corpus
callosum using multiple MR imaging contrasts between a population of
extremely-preterm born adolescents and their term-born peers.Introduction
Extreme preterm birth (less than 28 weeks completed gestation) is
associated with an increased risk of poor neurocognitive outcome [1,2]. The
effects of extreme prematurity on long-term brain development are not well
understood, although research studies are now available which are beginning to
address these questions. In this work we present some initial results from a neuroimaging
study of extreme prematurity carried out on preterm survivors and term-born
controls at 19 years of age. We use
multi-contrast MRI to specifically investigate structure and shape of the
corpus callosum. The appearance of this structure
has long been described as a notable neurological feature of the preterm
phenotype on neonatal studies and here we investigate to what extent these
difference remain in adolescence.
Data
Imaging data were acquired for a cohort of 119 adolescents at 19 years
of age. Data for 69 extremely preterm adolescents (F/M=41/28, mean birth
gestation=25.0±0.8wks) and 50 (F/M=30/20) term-born socioeconomically matched
peers were acquired on a 3T Phillips Achieva. We acquired 3D T1-weighted
(TR/TE=6.93/3.14ms) volume at 1mm isotropic resolution.
Diffusion weighted data was
acquired across four b-values at b = {0,300,700,2000}s.mm−2 with
n={4,8,16,32} directions respectively at TE=70ms (2.5x2.5x3.0mm). T2 weighted
data was acquired in the same space as the diffusion imaging with ten echo
times at TE={13,16,19,25,30,40,50,85,100,150}ms (2.5x2.5x3.0mm). B0 field maps were acquired to correct for EPI-based distortions between the diffusion imaging and the T1-weighted volumes.
Methods
After brain segmentation using a combined
multi-atlas, Gaussian mixture model segmentation routine [1], we extract the
corpus callosum from the mid-sagittal corpus callosum slice by identification
of the cerebral aqueduct. After manual removal of the fornix we apply an affine
transformation followed by a non-rigid (fluid-based) registration algorithm to
investigate local differences in corpus callosum volume and shape by
registration to a groupwise coordinate system of the individual control with
the median corpus callosum volume [4]. After segmentation,
we investigate the spatial microstructure by combining the results with an
analysis of the diffusion imaging data using the NODDI model which provides an
estimate of the intra-axonal volume fraction [3]. We also fit single and
multi-component T2 relaxometry to the multi-echo T2 weighted data in order to estimate
both the tissue T2 and to extract a short-T2 component that we attribute to
myelin water [6]. This facilitates an estimation of the multi-modal g-ratio in the
preterm corpus callosum [7].
Results
Analysing
the volume of the segmentation suggests that the corpus callosum is
significantly smaller in preterms (506±96mm3)
than their term-born peers (669±104mm3) (95% ci: -(123-204)mm3)
Average mid-sagittal corpus callosum values for the FA are higher in the term
group (0.58±0.07) than in the preterm group (0.52±0.10, 95% ci: -(0.02-0.10))
whilst T2 is higher at 74.2±7.4ms in the term group than in the preterm group (88.2±17.5ms
, 95% ci: (7.9-20.0)ms). Using intra-axonal and myelin water models, the
intra-axonal and myelin water fractions are both lower (0.51±0.12 / 0.61±0.08 and
0.25±0.05 / 0.29±0.04 respectively
95%ci: -(0.05-0.14) and -(0.02-0.06) respectively) in the preterm group than
the term group. Despite reaching significance between preterm and term groups,
these biomarkers do not translate into a significant difference (term=0.77±0.04
preterm=0.77±0.06) in the measured emergent g-ratio (p=0.87), either due to
measurement insensitivity or perhaps developmental compensation. These results
are summarised in the boxplots of Figure 2.
We
also analysed differences in corpus callosum shape using the results of the
non-rigid registration. Figure 3 summarises these results. Within group average
segmentations are shown for term controls (Fig 3a) and for extreme-preterms
(Fig 3b). Figures 3b and e show the colour coded 2D average absolute
deformation (red represents anterior-posterior displacement and green
superior-inferior) Finding the Jacobian determinant of the transformations
suggests that the major differences in shape between the term and preterm
cohorts is the posterior section of the corpus callosum. Both Figure 3 and
Figure 1 show marked thinning of the posterior segment of the main body of the
corpus callosum with involvement of the splenium.
Conclusion
We
have shown that the corpus callosum of extreme preterm survivors remains
altered at 19 years of age. Of note, the mid-sagittal corpus callosum area is
lower, and remains lower when correcting for an overall lower brain volume in
EPs. Notably, the posterior portion of the corpus callosum is most affected,
particularly the splenium and this may have a consequence for those areas for
which intra-hemispheric communication depends upon this pathway. Our future
work will devise functional tests to attempt to validate this hypothesis, but work
such as this, characterising the extremely preterm brain phenotype at
adolescence is crucial for understanding the long term impact on structural
appearance.
Acknowledgements
We would also like to acknowledge the MRC (MR/J01107X/1), the National
Institute for Health Research (NIHR), the EPSRC (EP/H046410/1) and the
National Institute for Health Research University College London
Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact
Initiative- BW.mn.BRC10269). This work is supported by the EPSRC-funded
UCL Centre for Doctoral Training in Medical Imaging (EP/L016478/1).References
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