The study explores the utility of new, advanced quantitative MRI metrics in brain ageing research. Like a high-resolution camera that captures intricate details, these MRI metrics allow scientists to evaluate various biological processes relevant to ageing in real time. By combining different MRI parameters, such as myelin density, cellular membrane integrity, and iron concentration, researchers gain valuable insights into the brain’s microstructural changes. The study involved 116 healthy volunteers across different age groups, enabling the identification of distinct patterns in brain ageing. Some MRI protocols were more sensitive to changes during early adulthood and plateaued at higher ages, while others exhibited stable levels in young adulthood but experienced sharp changes as individuals grew older. However, not all MRI metrics aligned with expected patterns based on previous research, highlighting the need for cautious interpretation. Additionally, intercorrelations between certain metrics suggest overlapping microstructural processes or inherent dependencies in the MRI protocol itself. This study provides a vital foundation for selecting appropriate MRI parameters depending on the age group under investigation and emphasizes the importance of comprehensive multi-modal approaches for accurate histological MRI results.

The advent of new, advanced quantitative MRI metrics allows for in vivo evaluation of multiple biological processes highly relevant for ageing. The presented study combines several MRI parameters hypothesised to detect distinct biological characteristics as myelin density, cellularity, cellular membrane integrity and iron concentration. 116 healthy volunteers, continuously distributed over the whole adult age span, underwent a multi-modal MRI protocol acquisition. Scatterplots of individual MRI metrics revealed that certain MRI protocols offer much higher sensitivity to early adulthood changes while plateauing in higher age (e.g., global functional connectivity in cerebral cortex or orientation dispersion index in white matter), while other MRI metrics provided reverse ability—stable levels in young adulthood with sharp changes with rising age (e.g., T1ρ and T2ρ). Nonetheless, despite the previously published validations of specificity towards microstructural biology based on cytoarchitectonic maps in healthy population or alterations in certain pathologies, several metrics previously hypothesised to be selective to common measures failed to show similar scatterplot distributions, pointing to further confounding factors directly related to age. Furthermore, other metrics, previously shown to detect different biological characteristics, exhibited substantial intercorrelations, be it due to the nature of the MRI protocol itself or co-dependence of relevant biological microstructural processes. All in all, the presented study provides a unique basis for the design and choice of relevant MRI parameters depending on the age group of interest. Furthermore, it calls for caution in simplistic biological inferences in ageing based on one simple MRI metric, even though previously validated under other conditions. Complex multi-modal approaches combining several metrics to extract the shared subcomponent will be necessary to achieve the desired goal of histological MRI.

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