The Relationship of High-Intensity Signals on Magnetic Resonance Images to Cognitive and Psychiatric State in Alzheimer's Disease

1991 ◽  
Vol 48 (11) ◽  
pp. 1136-1140 ◽  
Author(s):  
L. E. Harrell ◽  
E. Duvall ◽  
D. G. Folks ◽  
L. Duke ◽  
A. Bartolucci ◽  
...  
2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Manan Binth Taj Noor ◽  
Nusrat Zerin Zenia ◽  
M Shamim Kaiser ◽  
Shamim Al Mamun ◽  
Mufti Mahmud

Abstract Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have opened up possibilities to unprecedentedly identify neurological disorders. However, similarities in disease phenotypes make it very difficult to detect such disorders accurately from the acquired neuroimaging data. This article critically examines and compares performances of the existing deep learning (DL)-based methods to detect neurological disorders—focusing on Alzheimer’s disease, Parkinson’s disease and schizophrenia—from MRI data acquired using different modalities including functional and structural MRI. The comparative performance analysis of various DL architectures across different disorders and imaging modalities suggests that the Convolutional Neural Network outperforms other methods in detecting neurological disorders. Towards the end, a number of current research challenges are indicated and some possible future research directions are provided.


Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Carlos López-Gómez ◽  
Rafael Ortiz-Ramón ◽  
Enrique Mollá-Olmos ◽  
David Moratal ◽  

The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD.


Nutrients ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 206 ◽  
Author(s):  
Reale ◽  
Costantini ◽  
Jagarlapoodi ◽  
Khan ◽  
Belwal ◽  
...  

Background: Alzheimer’s disease (AD), the most threatening neurodegenerative disease, is characterized by the loss of memory and language function, an unbalanced perception of space, and other cognitive and physical manifestations. The pathology of AD is characterized by neuronal loss and the extensive distribution of senile plaques and neurofibrillary tangles (NFTs). The role of environment and the diet in AD is being actively studied, and nutrition is one of the main factors playing a prominent role in the prevention of neurodegenerative diseases. In this context, the relationship between dementia and wine use/abuse has received increased research interest, with varying and often conflicting results. Scope and Approach: With this review, we aimed to critically summarize the main relevant studies to clarify the relationship between wine drinking and AD, as well as how frequency and/or amount of drinking may influence the effects. Key Findings and Conclusions: Overall, based on the interpretation of various studies, no definitive results highlight if light to moderate alcohol drinking is detrimental to cognition and dementia, or if alcohol intake could reduce risk of developing AD.


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