Relationship between attentional performance and corpus callosum morphometry in patients with Alzheimer's disease

2002 ◽  
Vol 40 (7) ◽  
pp. 946-956 ◽  
Author(s):  
A Dorion
2018 ◽  
Vol 15 (12) ◽  
pp. 1151-1160 ◽  
Author(s):  
Zihan Jiang ◽  
Huilin Yang ◽  
Xiaoying Tang

Objective: In this study, we investigated the influence that the pathology of Alzheimer’s disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects. Method: Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC). Results: We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC. Conclusion: Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Malo Gaubert ◽  
Catharina Lange ◽  
Antoine Garnier-Crussard ◽  
Theresa Köbe ◽  
Salma Bougacha ◽  
...  

Abstract Background White matter hyperintensities (WMH) are frequently found in Alzheimer’s disease (AD). Commonly considered as a marker of cerebrovascular disease, regional WMH may be related to pathological hallmarks of AD, including beta-amyloid (Aβ) plaques and neurodegeneration. The aim of this study was to examine the regional distribution of WMH associated with Aβ burden, glucose hypometabolism, and gray matter volume reduction. Methods In a total of 155 participants (IMAP+ cohort) across the cognitive continuum from normal cognition to AD dementia, FLAIR MRI, AV45-PET, FDG-PET, and T1 MRI were acquired. WMH were automatically segmented from FLAIR images. Mean levels of neocortical Aβ deposition (AV45-PET), temporo-parietal glucose metabolism (FDG-PET), and medial-temporal gray matter volume (GMV) were extracted from processed images using established AD meta-signature templates. Associations between AD brain biomarkers and WMH, as assessed in region-of-interest and voxel-wise, were examined, adjusting for age, sex, education, and systolic blood pressure. Results There were no significant associations between global Aβ burden and region-specific WMH. Voxel-wise WMH in the splenium of the corpus callosum correlated with greater Aβ deposition at a more liberal threshold. Region- and voxel-based WMH in the posterior corpus callosum, along with parietal, occipital, and frontal areas, were associated with lower temporo-parietal glucose metabolism. Similarly, lower medial-temporal GMV correlated with WMH in the posterior corpus callosum in addition to parietal, occipital, and fontal areas. Conclusions This study demonstrates that local white matter damage is correlated with multimodal brain biomarkers of AD. Our results highlight modality-specific topographic patterns of WMH, which converged in the posterior white matter. Overall, these cross-sectional findings corroborate associations of regional WMH with AD-typical Aß deposition and neurodegeneration.


2004 ◽  
Vol 25 ◽  
pp. S278
Author(s):  
Paul Wang ◽  
Andrew J. Saykin ◽  
Laura A. Flashman ◽  
Heather A. Wishart ◽  
Laura A. Rabin ◽  
...  

2010 ◽  
Vol 6 ◽  
pp. S57-S58
Author(s):  
Kristian S. Jensen ◽  
Ellen Garde ◽  
Arnold Skimminge ◽  
Frederik Barkhof ◽  
Philip Scheltens ◽  
...  

1996 ◽  
Vol 243 (3) ◽  
pp. 231-234 ◽  
Author(s):  
Patrick Vermersch ◽  
Jean Roche ◽  
Mich�le Hamon ◽  
Christine Daems-Monpeurt ◽  
Jean-Pierre Pruvo ◽  
...  

2010 ◽  
Vol 6 ◽  
pp. S34-S34
Author(s):  
Rahyeong Juh ◽  
Chan Seung Chung ◽  
Jung Sun Lee ◽  
Jung In Son ◽  
Seong Yoon Kim

Neuroreport ◽  
2001 ◽  
Vol 12 (11) ◽  
pp. 2375-2379 ◽  
Author(s):  
F. Gonzalez-Lima ◽  
Jason D. Berndt ◽  
Jonathan E. Valla ◽  
Dora Games ◽  
Eric M. Reiman

Neurology ◽  
1998 ◽  
Vol 51 (5) ◽  
pp. 1381-1385 ◽  
Author(s):  
S. J. Teipel ◽  
H. Hampel ◽  
G. E. Alexander ◽  
M. B. Schapiro ◽  
B. Horwitz ◽  
...  

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