Schematic representation for the capabilities of using the surface-based deformation in PD. Surface deformation analysis of subcortical structures can be used to explain longitudinal changes in atrophy due to PD progression. Even more interesting, surface deformations can be used as variables of interest in multivariate models to perform predictions of DaTscan density in the initial stages of PD.
Morphological biomarkers of the brain, particularly in subcortical structures, refer to measurable changes in brain anatomy that can indicate disease processes or alterations in cognitive and motor functions. Structural changes in these regions, particularly in the putamen and caudate nucleus, have been implicated in Parkinson’s disease (PD), Huntington’s disease, and other movement disorders.
Traditionally, volumetric quantification of subcortical structures has been the gold-standard biomarker for tracking anatomical changes as it is easy to measure and able to be compared across different subjects. On the other hand, surface-based biomarkers of subcortical areas focus on their outer surface morphology and are particularly useful in detecting local atrophy, cortical folding or surface deformation along spatial directions. Although surface-shape analysis complements volumetric analysis, it has been consistently reported that subcortical structures might undergo significant morphological changes in several diseases and disorders that may not be visible through volumetric measures alone.
Despite several studies having used morphological shape analysis of subcortical regions to successfully discriminate Parkinson’s disease patients from control subjects, very little is known about the ability of such analysis to track the disease progression and detect significant changes in longitudinal settings.
We defined the projection of the nonlinear template-to-subject transformation onto the direction of the normal vector to the surface as our local measure of inward or outward displacement. Using this metric, we showed that such quantification of the local deformations in the shape of subcortical structures, like the Midbrain and Thalamus, is a more sensitive biomarker than volume for tracking the longitudinal progression of atrophy in PD. Importantly, we also determined that local deformations in the shape of the Midbrain are able to predict the reduction of Dopamine Transporter (DaT) density in the striatum, a very early hallmark of PD.