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

Hemant D. Tagare; Christine DeLorenzo; Sudhakar Chelikani; Lawrence Saperstein; Robert K. Fulbright

doi:10.1016/j.neuroimage.2017.02.067

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

Hemant D. Tagare
, Christine DeLorenzo
, Sudhakar Chelikani
, Lawrence Saperstein
, Robert K. Fulbright

Psychiatry

Yale University

Research output: Contribution to journal › Article › peer-review

29 Scopus citations

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.

Original language	English
Pages (from-to)	299-311
Number of pages	13
Journal	NeuroImage
Volume	152
DOIs	https://doi.org/10.1016/j.neuroimage.2017.02.067
State	Published - May 15 2017

Keywords

DaTscan
Logistic Lasso
Logistic Principal Components
Parkinson's disease
PPMI

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10.1016/j.neuroimage.2017.02.067

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title = "Voxel-based logistic analysis of PPMI control and Parkinson's disease DaTscans",

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, Parkinson's disease, PPMI",

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AU - Tagare, Hemant D.

AU - DeLorenzo, Christine

AU - Chelikani, Sudhakar

AU - Saperstein, Lawrence

AU - Fulbright, Robert K.

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AB - 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.

KW - DaTscan

KW - Logistic Lasso

KW - Logistic Principal Components

KW - Parkinson's disease

KW - PPMI

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VL - 152

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JO - NeuroImage

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ER -

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

Abstract

Keywords

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