Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

Area of Science:

• Neuroscience
• Medical Imaging
• Gerontology

Background:

• Brain aging is characterized by functional decline and increased susceptibility to neurodegenerative diseases.
• Understanding individual differences in brain aging is crucial for predicting health outcomes.
• Neuroimaging techniques offer potential for personalized brain age prediction.

Purpose of the Study:

• To present evidence for neuroimaging-based brain age as a biomarker of brain health.
• To explore the relationship between brain age, health status, and aging trajectories.
• To discuss current trends and controversies in brain age research.

Main Methods:

• Utilizing neuroimaging data to calculate an individual's 'brain age'.
• Correlating brain age with physiological health, cognitive function, and mortality risk.
• Reviewing existing literature and emerging methodologies in brain age estimation.

Main Results:

• Brain disease and poor physical health are associated with an increased brain age.
• A higher brain age correlates with advanced physiological and cognitive aging.
• An older-appearing brain is linked to an elevated risk of mortality.

Conclusions:

• Neuroimaging-based brain age serves as a valuable biomarker for assessing brain health and predicting aging-related outcomes.
• Brain age estimation can identify individuals at higher risk for accelerated aging and mortality.
• Future research directions include multimodal neuroimaging and deep learning approaches for enhanced accuracy.