scholarly journals Functional signature of conversion in Mild Cognitive Impairment patients

2018 ◽  
Author(s):  
Stefano Delli Pizzi ◽  
Miriam Punzi ◽  
Stefano L Sensi ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Atrophy ◽  
Cortical Atrophy ◽  
Study Cohort ◽  
Dramatic Decline ◽  
Healthy Control ◽  
Cortical Regions

AbstractThe entorhinal-hippocampal circuit is a strategic hub for memory but also the first site to be affected in the Alzheimer’s Disease (AD)-related pathology. We investigated MRI patterns of brain atrophy and functional connectivity in a study cohort obtained from the Alzheimer’s Disease Neuroimaging Initiative database including healthy control (HC), Mild Cognitive Impairment (MCI), and AD subjects. MCI individuals were clinically evaluated 24 months after the MRI scan, and the group further divided into a subset of subjects who either did (c-MCI) or did not (nc-MCI) convert to AD. Compared to HC subjects, AD patients exhibited a collapse of long-range connectivity from the hippocampus and entorhinal cortex, pronounced cortical/sub-cortical atrophy, and a dramatic decline in cognitive performances. c-MCI patients showed entorhinal and hippocampal hypo-connectivity, no signs of cortical thinning but evidence of right hippocampus atrophy. On the contrary, nc-MCI patients showed lack of brain atrophy, largely preserved cognitive functions, hippocampal and entorhinal hyper-connectivity with selected neocortical/sub-cortical regions mainly involved in memory processing and brain meta-stability. This hyper-connectivity can represent an early compensatory strategy to overcome the progression of cognitive impairment. This functional signature can also be employed for the diagnosis of c-MCI subjects.

P1-352: Cortical atrophy rates in Alzheimer's disease and mild cognitive impairment from the ADNI study

2011 ◽  
Vol 7 ◽  
pp. S225-S225 ◽  
Author(s):  
Christian Spenger ◽  
Simon Eskildsen ◽  
Niclas Sjogren ◽  
Per Julin ◽  
Eric Westman ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cortical Atrophy

scholarly journals Cortical Microstructural Alterations in Mild Cognitive Impairment and Alzheimer’s Disease Dementia

2020 ◽  
Vol 30 (5) ◽  
pp. 2948-2960 ◽  
Author(s):  
Nicholas M Vogt ◽  
Jack F Hunt ◽  
Nagesh Adluru ◽  
Douglas C Dean ◽  
Sterling C Johnson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cortical Thickness ◽  
Gray Matter ◽  
Brain Regions ◽  
Cortical Atrophy ◽  
Microstructural Alterations ◽  
Additional Information

Abstract In Alzheimer’s disease (AD), neurodegenerative processes are ongoing for years prior to the time that cortical atrophy can be reliably detected using conventional neuroimaging techniques. Recent advances in diffusion-weighted imaging have provided new techniques to study neural microstructure, which may provide additional information regarding neurodegeneration. In this study, we used neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion model, in order to investigate cortical microstructure along the clinical continuum of mild cognitive impairment (MCI) and AD dementia. Using gray matter-based spatial statistics (GBSS), we demonstrated that neurite density index (NDI) was significantly lower throughout temporal and parietal cortical regions in MCI, while both NDI and orientation dispersion index (ODI) were lower throughout parietal, temporal, and frontal regions in AD dementia. In follow-up ROI analyses comparing microstructure and cortical thickness (derived from T1-weighted MRI) within the same brain regions, differences in NODDI metrics remained, even after controlling for cortical thickness. Moreover, for participants with MCI, gray matter NDI—but not cortical thickness—was lower in temporal, parietal, and posterior cingulate regions. Taken together, our results highlight the utility of NODDI metrics in detecting cortical microstructural degeneration that occurs prior to measurable macrostructural changes and overt clinical dementia.

Multivariate deformation-based analysis of brain atrophy to predict Alzheimer's disease in mild cognitive impairment

NeuroImage ◽  
2007 ◽  
Vol 38 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Stefan J. Teipel ◽  
Christine Born ◽  
Michael Ewers ◽  
Arun L.W. Bokde ◽  
Maximilian F. Reiser ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Atrophy

scholarly journals Automated Brain Volumetric Program Measuring Regional Brain Atrophy in Diagnosis of Mild Cognitive Impairment and Alzheimer’s Disease Dementia

2021 ◽  
Author(s):  
Dong-Woo Ryu ◽  
Yun Jeong Hong ◽  
Jung Hee Cho ◽  
Kichang Kwak ◽  
Jong-Min Lee ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Diagnostic Accuracy ◽  
Predictive Model ◽  
Brain Atrophy ◽  
Brain Volume ◽  
Volume Ratio ◽  
Rater Reliability

Abstract A quantitative analysis of brain volume can assist in diagnosis of Alzheimer’s disease (AD) ususally accompannied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 minutes 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability were high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo as a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.

P1-204: Identifying novel CSF markers of brain atrophy in Alzheimer's disease and mild cognitive impairment using a multiplex panel of analytes

2013 ◽  
Vol 9 ◽  
pp. P227-P227
Author(s):  
Steven Kiddle ◽  
Wasim Khan ◽  
Carlos Aguilar ◽  
Madhav Thambisetty ◽  
Martina Sattlecker ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Atrophy
Sign in / Sign up

Export Citation Format

Share Document