Automatic measurements of the corpus callosum in the follow-up of preterm children: Methodology and validation

Brain injury in preterm infants is associated with a high risk of neurodevelopmental disability. One of
the most frequent forms of brain injury is white matter injury. The largest white matter structure is the
corpus callosum and measurements of this structure have been associated with white matter volume.
Consequently, quantification of the corpus callosum could provide an insight into the white matter
injury related to preterm birth. However, manual measurements require an experienced rater, are highly
time-consuming and suffer from high inter- and intra-rater variability.

In this paper, we present an automated method for measuring the corpus callosum on T1-weighted
images of children, and we evaluate the model in terms of accuracy performance. Automatic measure-
ments of the anterior area, posterior area and length of the corpus callosum have a good intraclass
correlation coefficient while relatively low absolute error compared to the same measurement performed
manually by an expert child neurologist.