Novel spatial analysis method for PET images using 3D moment invariants: applications to Parkinson's disease

Abstract

We present a novel analysis method for positron emission tomography (PET) data that uses the spatial characteristics of the radiotracer's distribution within anatomically-defined regions of interest (ROIs) to provide an independent feature that may aid in characterizing pathological and normal states. The analysis of PET data for research purposes traditionally involves kinetic modeling of the concentration of the radiotracer over time within a ROI to derive parameters related to the uptake/binding of the radiotracer in the body. Here we describe an analysis method to quantify the spatial changes present in PET images based on 3D shape descriptors that are invariant to translation, scaling, and rotation, called 3D moment invariants (3DMIs). An ROI can therefore be characterized not only by the radiotracer's uptake rate constant or binding potential within the ROI, but also the 3D spatial shape and distribution of the radioactivity throughout the ROI. This is particularly relevant in Parkinson's disease (PD), where both the kinetic and the spatial distribution of the tracer are known to change due to disease: the posterior parts of the striatum (in particular in the putamen) are affected before the anterior parts. Here we show that 3DMIs are able to quantify the spatial distribution of PET radiotracer images allowing for discrimination between healthy controls and PD subjects. More importantly, 3DMIs are found to be well correlated with subjects' scores on the United Parkinson's Disease Rating Scale (a clinical measure of disease severity) in all anatomical regions studied here (putamen, caudate and ventral striatum). On the other hand, kinetic parameters only show significant correlation to clinically-assessed PD severity in the putamen. We also find that 3DMI-characterized changes in spatial patterns of dopamine release in response to l-dopa medication are significantly correlated with PD severity. These findings suggest that quantitative studies of a radiotracer's spatial distribution may provide complementary information to kinetic modeling that is relatively robust to intersubject variability and may contribute novel information in PET neuroimaging studies.