Voxel-based logistic analysis of PPMI control and Parkinson's disease DaTscans

•Voxel-wise analysis of PPMI Control and Parkinson's DaTscan images gives accurate classification and identifies voxels that are informative.•New analysis called Logistic Principal Components reveals sources of variation in control and PD images that affect classification.•Logistic features are related to MDS-UPDRS scores.•Logistic features interact with sex and age, but not with handedness.

A comprehensive analysis of the Parkinson's Progression Markers Initiative (PPMI) Dopamine Transporter Single Photon Emission Computed Tomography (DaTscan) images is carried out using a voxel-based logistic lasso model. The model reveals that sub-regional voxels in the caudate, the putamen, as well as in the globus pallidus are informative for classifying images into control and PD classes. Further, a new technique called logistic component analysis is developed. This technique reveals that intra-population differences in dopamine transporter concentration and imperfect normalization are significant factors influencing logistic analysis. The interactions with handedness, sex, and age are also evaluated.