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Pathological evidence of Alzheimer's disease (AD) can be detected years before clinical symptoms appear
.
The identification of brain structural changes in people with genetic risk of early-onset AD based on imaging technology may provide insights into how genes affect the pathological cascade leading to dementia
Jeffrey W.
Prescott et al.
published a research article in the journal Radiology to assess the differences in the structural connections of the cortical network between the cognitively normal autosomal dominant Alzheimer's disease (ADAD) mutation carriers and non-carriers, and to determine the structural connections and cortex The cross-sectional relationship between amyloid load and estimated years of onset of dementia (EYO)
.
In the exploratory analysis of this prospective trial, all participants who were included in the dominant Alzheimer's network between January 2009 and July 2014 had normal baseline cognition
.
T1-weighted MRI and diffusion tensor imaging (DTI) images were analyzed
The cerebral cortex is divided into three cortical networks: the default network, the frontal and parietal control network and the ventral attention network
.
The structural connectivity of the three networks is calculated using DTI
A general linear model was used to test the differences in structural connectivity between mutation carriers and non-carriers, as well as the relationship between mutation carriers' structural connectivity, amyloid burden and EYO
.
Identify relevant clinical and imaging markers through relevant network analysis
The study included 30 mutation carriers (mean age standard deviation 34 years and 10 years; 17 women) and 38 non-carriers (mean age 37 years and 10 years; 20 women)
.
Compared with non-carriers, mutation carriers have lower prefrontal and parietal control network structure connections (estimated mutation positive effect, 0.
The scatter plot shows the overall efficiency of the frontal-parietal control network of the cognitively normal mutation-positive participants versus the estimated time to onset (EYO) (top) and the ratio of Pittsburgh compound B amyloid PET standardized uptake value (SUVr) (bottom) Contrast
.
.
Related networks for non-carriers (top) and mutation carriers (bottom)
.
The baseline clinical and biomarker descriptors are represented by circles
Related networks for non-carriers (top) and mutation carriers (bottom)
This study showed that the mutation status and the low value - parietal OFF control of the network connection between the lines
.
In addition, as mutation carriers approach the expected age of onset of symptoms of autosomal dominant Alzheimer's disease, their frontal and parietal control network changes worsen
This study showed that the mutation status and the low amount of this study showed that the mutation status and the low amount - - parietal OFF control of the network connection between the lines
.
In addition, as mutation carriers approach the expected age of onset of symptoms of autosomal dominant Alzheimer's disease, their frontal and parietal control network changes worsen
.
Parietal OFF control between a network connection system
.
Department
.
In addition, as mutation carriers approach the expected age of onset of symptoms of autosomal dominant Alzheimer's disease, their frontal and parietal control network changes worsen
.
These findings seem to be linearly related to amyloid load, although they appear in the context of elevated amyloid
.
In the future, these findings
in longitudinal clinical trials seem to be linearly related to amyloid load, although they appear in the context of elevated amyloid .
Future research on longitudinal clinical MRI connectivity data and molecular pathology PET markers may help to further clarify the role of white matter structural connectivity in cognitive decline and use it as a potential organism for patients with genetic risk of Alzheimer's disease Markers
.
Original source
Diffusion Tensor MRI Structural Connectivity and PET Amyloid Burden in Preclinical Autosomal Dominant Alzheimer Disease: The DIAN Cohort.
Published Online:Oct 12 2021https://doi.
org/10.
1148/radiol.
2021210383
Published Online:Oct 12 2021https://doi.
org/10.
1148/radiol.
2021210383 Leave a message here