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Published on: November 6, 2017
Relationship Between Cognitive Dysfunction and Systemic Metabolic Disorders in Elderly: Dementia Might be a
1Department of Electrical and Electronic Engineering, NEWCAT Research Institute, Koriyama, Japan.
Insights
Deep learning identified links between cognitive decline in vascular cognitive impairment (VCI) and metabolic issues. Systemic metabolic disorders and cerebral circulatory disturbances contribute to VCI, impacting elderly dementia risk.
Area of Science:
- Neurology
- Geriatrics
- Medical Imaging
- Artificial Intelligence
Background:
- Vascular cognitive impairment (VCI) is a significant factor in elderly dementia.
- VCI encompasses a spectrum of cognitive disorders linked to vascular pathology.
- Lifestyle diseases and cerebrovascular disorders are prevalent in VCI patients.
Purpose of the Study:
- To investigate the relationship between cognitive dysfunction and systemic metabolic disorders using deep learning (DL).
- To evaluate the utility of time-resolved near infrared spectroscopy (TNIRS) and blood examination data in predicting cognitive function in VCI patients.
Main Methods:
- Studied 202 patients (mean age 73.4 years) with VCI, assessing cognitive function via Mini Mental State Examination (MMSE).
- Collected general blood examination data (Complete Blood Count, Basic Metabolic Panel) and measured cerebral blood oxygenation in the prefrontal cortex (PFC) using TNIRS.
- Employed deep neural networks to predict MMSE scores based on TNIRS and blood data independently, then compared predictions.
Main Results:
- A significant positive correlation (r=0.6, p<0.01) was found between TNIRS parameters and blood examination data.
- Deep learning models demonstrated the potential to predict cognitive function (MMSE scores) from both TNIRS and blood data.
Conclusions:
- Cognitive dysfunction in VCI patients is likely influenced by a combination of systemic metabolic disorders (energy/oxygen metabolism) and cerebral circulatory disturbances.
- Arteriosclerosis, stemming from lifestyle-related diseases, appears to be a key contributor to these circulatory issues in VCI.
Abstract:
Vascular cognitive impairment (VCI) plays an important role in dementia in elderly people, and refers to the contribution of vascular pathology to the entire spectrum of cognitive disorders, ranging from mild cognitive impairment to severe dementia, as well as the pathological spectrum, from 'pure' Alzheimer disease through degrees of vascular comorbidity to 'pure' vascular dementia. In the present study, we investigated the relationship between cognitive dysfunction and systemic metabolic disorders, by employing deep learning (DL). We studied 202 patients (73.4 ± 13.0 years), 94.6% of whom were undergoing treatment for lifestyle diseases, and 68.8% of whom had a history of cerebrovascular disorder. We evaluated cognitive dysfunction by performing a Mini Mental State Examination (MMSE). We performed general blood examination, including Complete Blood Count and Basic Metabolic Panel, and measured cerebral blood oxygenation in the prefrontal cortex (PFC) using time-resolved near infrared spectroscopy (TNIRS). We then used deep neural networks to assess the MMSE scores of the subjects based on the TNIRS parameters and the blood examination data, independently. Next, we compared predicted MMSE scores based on the TNIRS and the blood examination. There was a significant positive correlation between the TNIRS parameters and the blood examination data (r = 0.6, p < 0.01). These observations suggest that cognitive dysfunction in patients with VCI may be caused by combinations of systemic metabolic disorders such as energy and oxygen metabolisms and cerebral circulatory disturbance due to arteriosclerosis resulting from lifestyle-related diseases.
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