multimodal neuroimaging
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2022 ◽  
Vol 15 ◽  
Author(s):  
Seyed Hani Hojjati ◽  
Abbas Babajani-Feremi ◽  

Background: In recent years, predicting and modeling the progression of Alzheimer’s disease (AD) based on neuropsychological tests has become increasingly appealing in AD research.Objective: In this study, we aimed to predict the neuropsychological scores and investigate the non-linear progression trend of the cognitive declines based on multimodal neuroimaging data.Methods: We utilized unimodal/bimodal neuroimaging measures and a non-linear regression method (based on artificial neural networks) to predict the neuropsychological scores in a large number of subjects (n = 1143), including healthy controls (HC) and patients with mild cognitive impairment non-converter (MCI-NC), mild cognitive impairment converter (MCI-C), and AD. We predicted two neuropsychological scores, i.e., the clinical dementia rating sum of boxes (CDRSB) and Alzheimer’s disease assessment scale cognitive 13 (ADAS13), based on structural magnetic resonance imaging (sMRI) and positron emission tomography (PET) biomarkers.Results: Our results revealed that volumes of the entorhinal cortex and hippocampus and the average fluorodeoxyglucose (FDG)-PET of the angular gyrus, temporal gyrus, and posterior cingulate outperform other neuroimaging features in predicting ADAS13 and CDRSB scores. Compared to a unimodal approach, our results showed that a bimodal approach of integrating the top two neuroimaging features (i.e., the entorhinal volume and the average FDG of the angular gyrus, temporal gyrus, and posterior cingulate) increased the prediction performance of ADAS13 and CDRSB scores in the converting and stable stages of MCI and AD. Finally, a non-linear AD progression trend was modeled to describe the cognitive decline based on neuroimaging biomarkers in different stages of AD.Conclusion: Findings in this study show an association between neuropsychological scores and sMRI and FDG-PET biomarkers from normal aging to severe AD.


2021 ◽  
Vol 46 (6) ◽  
pp. E702-E710
Author(s):  
Gregory Overbeek ◽  
Timothy J. Gawne ◽  
Meredith A. Reid ◽  
Nina V. Kraguljac ◽  
Adrienne C. Lahti

2021 ◽  
Vol 17 (S6) ◽  
Author(s):  
Danielle V. Mayblyum ◽  
Pranitha Y Premnath ◽  
Zoe B. Rubinstein ◽  
Justin S Sanchez ◽  
Emma G. Thibault ◽  
...  

Author(s):  
Chris Moran ◽  
Stephanie Than ◽  
Michele Callisaya ◽  
Richard Beare ◽  
Velandai Srikanth

Abstract The prevalence of Type 2 diabetes (T2D) and cognitive dysfunction increases with age. As society ages, clinicians will be increasingly tasked with managing older people who have both T2D and cognitive dysfunction. T2D is associated with an increased risk of cognitive dysfunction and hence there is increasing interest in whether T2D is a causal factor in the pathogenesis of cognitive decline and dementia. Recent advances in the use of sensitive measures of in-vivo brain dysfunction in life-course studies can help understand potential mechanistic pathways and also help guide recommendations for clinical practice.In this article we will describe new horizons in the understanding of cognitive dysfunction associated with T2D. Coming from a clinical perspective, we discuss potential mechanisms and pathways linking the two conditions and the contribution of multimodal neuroimaging and study designs to advancing understanding in the field. We also highlight the important issues on the horizon that will need addressing in clinical identification, management and risk reduction for people with co-existent T2D and cognitive dysfunction.


2021 ◽  
Vol 14 (6) ◽  
pp. 1722
Author(s):  
Debby Klooster ◽  
Michael Ferguson ◽  
Paul Boon ◽  
Chris Baeken

Author(s):  
Jiajia Zhu ◽  
Chunli Wang ◽  
Yinfeng Qian ◽  
Huanhuan Cai ◽  
Shujun Zhang ◽  
...  

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