Accelerated brain aging on MRI has shown to be able to predict cognitive decline, potentially allowing disease to be detected earlier on MRI scans. This project aims to extend the aging detection methods to detect the "wrinkles" of cerebral blood flow. Although we know that the brain's blood flow is implicated in many diseases, it is not often clinically measured with MRI. This project aims to change this.
In this project, called "Cerebrovascular Brain-age", eScience will help researchers in Amsterdam UMC and worldwide to improve the detection of blood flow patterns related to accelerated aging and ultimately cognitive decline. We will create artificial intelligence methods that can detect these cerebral blood flow "wrinkles" from any MRI scanner worldwide. Finally, we will incorporate all these in a software package that can be easily used by everyone. Ultimately, we hope to improve early disease detection and treatment evaluation.
BrainAge
Cerebrovascular Brain-age
Photo credit – Shutterstock
Participating organisations
Impact
- 1.Author(s): Pradeepa Ruwan Wanni Arachchige, Yidian Gao, Iman Idrees, Jessikah Fildes, Aliza Finch, Waheeda Hawa, Martin Craig, Matthew J. Brookes, Lisa J. Hill, Samuel J.E. Lucas, James L. Mitchell, Alexandra J. Sinclair, Jan Novak, Andrew P. Bagshaw, Martin Wilson, Davinia Fernandez-Espejo, Karen J. Mullinger, United Kingdom mTBI Predict ConsortiumPublished in Aperture Neuro by Organization for Human Brain Mapping in 202610.52294/001c.157692
- 2.Author(s): Owen CarmichaelPublished in eBioMedicine by Elsevier BV in 2026, page: 10613010.1016/j.ebiom.2026.106130
Output
Team
Contact person
HM
Henk Mutsaerts
JP
Jan Petr
MD
Mathijs Dijsselhof
FB
Frederik Barkhof
Candace Makeda Moore
Saba Amiri