This Research Topic is part of the ''Exploring Reliable Markers and Prediction Indexes for the Progression from Subjective Cognitive Decline to Cognitive Impairment'' series.
Link to the Volume I:
Exploring Reliable Markers and Prediction Indexes for the Progression from Subjective Cognitive Decline to Cognitive ImpairmentSubjective cognitive decline (SCD) is a common symptom in the aged population that seemingly healthy older individuals report a self-perceived decline in cognition function, often memory loss, without objective evidence from formal neuropsychological tests. A growing body of evidence shows that SCD may be one of the earliest noticeable symptoms of Alzheimer’s disease (AD) and related dementias. Epidemiological data also suggest that individuals with subjective cognitive decline are at greater risk of progression to AD dementia. It is a topic of ongoing research, which markers in combination with SCD are useful to predict individual cognitive decline and progression to dementia in order to provide early therapeutic interventions in the future.
The development of neuroimaging techniques has provided the potential to explore the pathology of AD. For example, the brain atrophy in structural magnetic resonance imaging (sMRI), the altered neuronal activity observed with functional magnetic resonance imaging (fMRI), or connectivity changes in diffusion tensor imaging (DTI) are all associated with the pathology of AD.
From the perspective of molecular mechanisms, changes in glucose metabolism, Amyloid-Beta, and aggregated Tau protein, as well as the genetic risk factor Apoe4 characterize or are associated with the pathology of AD.
In addition, with the development of Artificial Intelligence (AI), novel imaging analysis and data mining computational techniques could also be applied to further accelerate the exploration of AD mechanism.
The objective of this project is to explore reliable markers and prediction indexes for the progression of SCD to cognitive decline and dementia from multidisciplinary perspectives including neuroimaging techniques, genetic or inflammation mechanisms, as well as AI applications.
The sub-topics include, but are not limited to:
1. Innovative experimental research of emerging interests in SCD involving distinctive biomarkers using neuroimaging techniques (sMRI, fMRI, DTI and molecular imaging)
2. Exploration of the risk factors and/or protective factors associated with the progression from SCD to cognitive impairment through epidemiological methods
3. Clinical applications of new techniques and methods to predict the progression from SCD to cognitive impairment
4. Clinical applications of computer-aided diagnostic approaches based on AI with multi-modal medical information to predict the progression from SCD to cognitive impairment
5. Application of bioinformatics and computational biology in big data mining that analyzes a specific database or medical records system to investigate SCD
