Alteration of the corpus callosum in patients with Alzheimer’s disease: Deep learning-based assessment

Abstract

Background Several studies have reported changes in the corpus callosum (CC) in Alzheimer’s disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysis of the CC in Alzheimer’s disease. Methods We used the Open Access Series of Imaging Studies (OASIS) dataset to investigate changes in the CC. The individuals were divided into three groups using the Clinical Dementia Rating (CDR); 94 normal controls (NC) were not demented (NC group, CDR = 0), 56 individuals had very mild dementia (VMD group, CDR = 0.5), and 17 individuals were defined as having mild and moderate dementia (MD group, CDR = 1 or 2). Deep learning technology using a convolutional neural network organized in a U-net architecture was used to segment the CC in the midsagittal plane. Total CC length and regional magnetic resonance imaging (MRI) measurements of the CC were made. Results The total CC length was negatively associated with cognitive function. (beta = -0.139, p = 0.022) Among MRI measurements of the CC, the height of the anterior third (beta = 0.038, p <0.0001) and width of the body (beta = 0.077, p = 0.001) and the height (beta = 0.065, p = 0.001) and area of the splenium (beta = 0.059, p = 0.027) were associated with cognitive function. To distinguish MD from NC and VMD, the receiver operating characteristic analyses of these MRI measurements showed areas under the curves of 0.65–0.74. (total CC length = 0.705, height of the anterior third = 0.735, width of the body = 0.714, height of the splenium = 0.703, area of the splenium = 0.649). Conclusions Among MRI measurements, total CC length, the height of the anterior third and width of the body, and the height and area of the splenium were associated with cognitive decline. They had fair diagnostic validity in distinguishing MD from NC and VMD.

Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer’s Disease

“…Accounting for shape changes, FA differences in OPT L in AD subjects may reflect aspects of the underlying loss of fiber integrity in AD, and FA differences in the forceps major observed in BUAN may be attributed to disease-related macrostructural changes. Prior work using structural MRI and fixel-based analysis identified structural atrophy of the corpus callosum in people with AD, possibly associated with ventricular dilation [39], [40]. Due to the partial volume effect, particularly in the CC tracts [41], disease-related macrostructural changes could contribute to changes in FA when the underlying fiber geometry is not accounted for.…”

Multi-parametric perfusion MRI by arterial spin labeling

“…The hippocampus is a memory and cognitive center and is related to the occurrence and progression of AD (Dautricourt et al, 2021). The association between the corpus callosum and insula in AD is unclear, and some theories remain controversial and contradictory (Kamal et al, 2021;Giacomucci et al, 2022). However, the mean CBF values in the right thalamus and pallidum were elevated in the AD group, but these differences were not significant (p > 0.05).…”

A diagnostic index based on pseudo-continuous arterial spin labeling and T1-mapping improves efficacy in discriminating Alzheimer’s disease from normal cognition

“…The hippocampus is a memory and cognitive center and is related to the occurrence and progression of AD (Dautricourt et al, 2021). The association between the corpus callosum and insula in AD is unclear, and some theories remain controversial and contradictory (Kamal et al, 2021;Giacomucci et al, 2022). However, the mean CBF values in the right thalamus and pallidum were elevated in the AD group, but these differences were not significant (p > 0.05).…”