Corpus callosum shape changes in early Alzheimer's disease: an MRI study using the OASIS brain database

Abstract

The corpus callosum (CC) is the largest fiber bundle connecting the left and right cerebral hemispheres. It has been a region examined extensively for indications of various pathologies, including Alzheimer's disease (AD). Almost all previous studies of the CC in AD have been concerned with its size, particularly its mid-sagittal cross-sectional area (CCA). In this study, we show that the CC shape, characterized by its circularity (CIR), may be affected more profoundly than its size in early AD. MRI scans (n = 196) were obtained from the publicly available Open Access Series of Imaging Studies database. The CC cross-sectional region on the mid-sagittal section of the brain was automatically segmented using a novel algorithm. The CCA and CIR were compared in 98 normal controls (NC) subjects, 70 patients with very mild AD (AD-VM), and 28 patients with mild AD (AD-M). Statistical analysis of covariance controlling for age and intracranial capacity showed that both the CIR and the CCA were significantly reduced in the AD-VM group relative to the NC group (CIR: p = 0.004; CCA: p = 0.005). However, only the CIR was significantly different between the AD-M and AD-VM groups (p = 0.006) being smaller in the former. The CCA was not significantly different between the AD-M and AD-VM groups. The results suggest that CC shape may be a more sensitive marker than its size for monitoring the progression of AD. In order to facilitate independent analyses, the CC segmentations and the CCA and CIR data used in this study have been made publicly available (http://www.nitrc.org/projects/art).

Fig. 1

The automatically detected mid-sagittal plane (MSP) using the algorithm of Ardekani et al. (1997) is shown in the background. The automatically detected anterior commissure (AC) and posterior commissure (PC) using the algorithm of Ardekani and Bachman (2009) are shown by the plus signs. The MSP is aligned so that the AC-PC line is horizontal with respect to the image coordinates. The rectangular box shows the search region for the corpus callosum (CC) obtained a priori using 38 manually delineated corpora callosa on AC-PC aligned MSP images as training data. The outline shows the detected CC using the algorithm described in this paper and in more detail in Ardekani et al. (2012a, b)

Fig. 2

Correlation between CCA and age (ρ = −0.408; p < 10⁻⁸)

Fig. 3

Correlation between CCA and intracranial capacity variable eTIV^2/3 (ρ = 0.321; p < 10⁻⁵)

Fig. 4

Adjusted corpus callosum area (CCA) mean values for the three diagnostic groups. The error bars indicate 1 SE. *The mean CCA in AD-VM was statistically smaller than NC (p = 0.005). **The mean in AD-M was statistically smaller than NC (p = 0.002). The AD-VM and AD-M groups were not statistically different (p = 0.266)

Fig. 5

Correlation between CIR and age (ρ = −0.452; p < 10⁻¹⁰)

Fig. 6

Correlation between CIR and intracranial capacity variable eTIV^2/3 (ρ = −0.348; p < 10⁻⁶)

Fig. 7

Corrected corpus callosum circularity (CIR) mean values for female and male groups. The error bars indicate 1 SE. *The mean CIR of the female group was significantly smaller than the male group (p = 0.015)

Fig. 8

Corrected corpus callosum circularity (CIR) mean values for the three diagnostic groups. The error bars indicate 1 SE. *The mean CIR in AD-VM was statistically smaller than NC (p = 0.004). **The mean in AD-M was statistically smaller than NC (p < 10⁻⁵). ***The mean AD-M was statistically smaller that AD-VM (p = 0.006)