Grey matter sublayer thickness estimation in themouse cerebellum
This work addresses a gap in studying cerebellar morphology for neurodegenerative diseases like Down's syndrome, but it is incremental as it applies existing imaging techniques to a new brain region.
The authors tackled the problem of estimating cerebellar grey matter sublayer thickness in mice, introducing a framework to extract the Purkinje layer and measure thicknesses of the cerebellar grey matter, granular layer, and molecular layer from ex vivo MRI, finding reduced thicknesses in a Down's syndrome mouse model.
The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer's disease or Down's syndrome. Its volume or thickness is commonly used as a surrogate imaging biomarker for such diseases. Most studies about grey matter thickness estimation focused on the cortex, and little attention has been drawn on the morphology of the cerebellum. Using ex vivo high-resolution MRI, it is now possible to visualise the different cell layers in the mouse cerebellum. In this work, we introduce a framework to extract the Purkinje layer within the grey matter, enabling the estimation of the thickness of the cerebellar grey matter, the granular layer and molecular layer from gadolinium-enhanced ex vivo mouse brain MRI. Application to mouse model of Down's syndrome found reduced cortical and layer thicknesses in the transchromosomic group.