| Title: | Age- and Sex-Specific Cerebral Blood Flow Atlases for Healthy Brain Across the Lifespan |
| Journal: | Scientific Data |
| Published: | 9 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40634347/ |
| DOI: | https://doi.org/10.1038/s41597-025-05406-w |
| URL: | https://www.nature.com/articles/s41597-025-05406-w.pdf |
Publication 16586
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Abstract
Cerebral blood flow (CBF) is a crucial biological marker providing valuable insights into the developmental and aging processes of the central nervous system. A comprehensive understanding of the age- and sex-specific distribution of CBF in healthy populations is essential for distinguishing between pathological changes and those associated with normal aging. This study introduces a collection of age- and sex-specific CBF atlases across the lifespan (7-93 years old), derived from a large data size (N = 1166) obtained from four public and one private datasets. The CBF maps were measured using pseudo-continuous arterial spin labelling (pCASL) MRI and registered to age-specific structural templates derived from corresponding T1-weighted scans. This approach enables a more precise characterization of CBF changes associated with anatomical variations across different age groups. To ensure data reliability, rigorous quality control procedures and extensive validation at both temporal and spatial scales were conducted. These openly accessible atlases serve as a valuable public neuroimaging resource, facilitating the identification of CBF patterns across various stages of development and aging. Additionally, they provide age- and sex-specific health priors, aiding in the detection of abnormal CBF associated with brain disorders throughout the lifespan.</p>
15 Keywords
- Adolescent
- Adult
- Aged
- Aged, 80 and over
- Aging
- Brain
- Cerebrovascular Circulation
- Child
- Female
- Humans
- Longevity
- Magnetic Resonance Imaging
- Male
- Middle Aged
- Young Adult
7 Authors
- Ziyu Meng
- Yuhao Ma
- Wenqi Zhang
- Huixiang Zhuang
- Chang Xu
- Yaoyu Zhang
- Yao Li
1 Application
| Application ID | Title |
|---|---|
| 93346 | Create multi-modal brain image priors for use in Bayesian models to be applied in stroke lesion segmentation and AD diagnosis studies |
Enabling scientific discoveries that improve human health