Do brain image databanks support understanding of normal ageing brain structure? A systematic review

Area of Science:

• Neuroimaging
• Gerontology
• Medical Informatics

Background:

• Existing brain image databanks often lack comprehensive data for studying normal aging.
• Diagnosing dementia relies on understanding structural brain changes in older adults.

Purpose of the Study:

• To document accessible magnetic resonance (MR) brain images, metadata, and statistical results from normal older subjects.
• To identify limitations in current databanks for dementia diagnosis research.

Main Methods:

• Systematic review of published brain image databanks (print and internet).
• Evaluation of databanks for subject numbers, metadata representativeness, image sequences, searchability, and stored statistical results.

Main Results:

• Nine databanks were identified, containing approximately 343 representative normal subjects aged ≥60 years, with only 98 openly accessible.
• No databank offered a complete range of MR image sequences (e.g., T2*, FLAIR) or random subject retrieval.
• None of the databanks provided stored statistical analysis results.

Conclusions:

• Brain image databanks need enhanced open access, larger subject pools, comprehensive metadata, diverse MR sequences, and searchability.
• Incorporating statistical results into databanks is crucial for validation and improved dementia diagnosis.
• These improvements will facilitate a better understanding of normal brain aging and enhance diagnostic accuracy for dementia.