  Ultrasound (US) can be used to assess brain development in newborns, as MRI
is challenging due to immobilization issues, and may require sedation.
Dilatation of the lateral ventricles in the brain is a risk factor for poorer
neurodevelopment outcomes in infants. Hence, 3D US has the ability to assess
the volume of the lateral ventricles similar to clinically standard MRI, but
manual segmentation is time consuming. The objective of this study is to
develop an approach quantifying the ratio of lateral ventricular dilatation
with respect to total brain volume using 3D US, which can assess the severity
of macrocephaly. Automatic segmentation of the lateral ventricles is achieved
with a multi-atlas deformable registration approach using locally linear
correlation metrics for US-MRI fusion, followed by a refinement step using
deformable mesh models. Total brain volume is estimated using a 3D ellipsoid
modeling approach. Validation was performed on a cohort of 12 infants, ranging
from 2 to 8.5 months old, where 3D US and MRI were used to compare brain
volumes and segmented lateral ventricles. Automatically extracted volumes from
3D US show a high correlation and no statistically significant difference when
compared to ground truth measurements. Differences in volume ratios was 6.0 +/-
4.8% compared to MRI, while lateral ventricular segmentation yielded a mean
Dice coefficient of 70.8 +/- 3.6% and a mean absolute distance (MAD) of 0.88
+/- 0.2mm, demonstrating the clinical benefit of this tool in paediatric
ultrasound.
