Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: Detecting, quantifying, and predicting. Issue 8 (17th January 2014)

• Record Type: Journal Article
• Authors: Tang, Xiaoying; Holland, Dominic; Dale, Anders M.; Younes, Laurent; Miller, Michael I.; for the Alzheimer's Disease Neuroimaging Initiative
• Is Part Of: Human brain mapping. Volume 35:Issue 8(2014:Aug.)
• Page Start: 3701
• Page End: 3725
• Publication Date: 2014-01-17
• Subjects: Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.22431
• Languages: English
• ISSNs: 1065-9471

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects. <italic>Hum Brain Mapp 35:3701–3725, 2014</italic>. © <bold>2014 Wiley Periodicals, Inc.</bold></p> </abstract>