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

被引：24

作者：

Tagare, Hemant D. ^{[1
,2
]}

DeLorenzo, Christine ^{[3
]}

Chelikani, Sudhakar ^{[1
]}

Saperstein, Lawrence ^{[1
]}

Fulbright, Robert K. ^{[1
]}

机构：

[1] Yale Univ, Dept Radiol & Biomed Imaging, New Haven, CT 06520 USA

[2] Yale Univ, Dept Biomed Engn, New Haven, CT USA

[3] SUNY Stony Brook, Dept Psychiat, Stony Brook, NY 11794 USA

来源：

NEUROIMAGE | 2017年 / 152卷

关键词：

Parkinson's disease; DaTscan; PPMI; Logistic Lasso; Logistic Principal Components; DOPAMINE TRANSPORTER SPECT; AUTOMATIC CLASSIFICATION; GENDER-DIFFERENCES; BRAIN IMAGES; DIAGNOSIS; QUANTIFICATION; SYSTEM;

D O I：

10.1016/j.neuroimage.2017.02.067

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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.

引用

页码：299 / 311

页数：13

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