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Neuroimage. 2017 May 15;152:299-311. doi: 10.1016/j.neuroimage.2017.02.067. Epub 2017 Feb 27.

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

Author information

1
Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA; Department of Biomedical Engineering, Yale University, New Haven, CT, USA. Electronic address: hemant.tagare@yale.edu.
2
Department of Psychiatry, Stony Brook University, NY, USA.
3
Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA.

Abstract

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.

KEYWORDS:

DaTscan; Logistic Lasso; Logistic Principal Components; PPMI; Parkinson's disease

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