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The Potential Utility of Arterial Spin Labeling in Predicting Brain Amyloidosis Publisher



Kazemzadeh K1 ; Naseri N2 ; Mombeini M3 ; Khodadadi A4 ; Jafari M3 ; Rostami R3 ; Enayat P3 ; Sadeghi M5 ; Berenjian S6 ; Amin Alavi SM7
Authors
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Authors Affiliations
  1. 1. Network of Neurosurgery and Artificial Intelligence (NONAI), Universal Scientific Education and Research Network (USERN), Tehran, Iran
  2. 2. Department of Animal Sciences and Biotechnology, Faculty of Life Sciences and Biotechnology, Shahid Beheshti University, Tehran, Iran
  3. 3. NeuroTRACT Association, Students’ Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
  5. 5. Department of Nuclear Medicine, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Department of Psychology, Islamic Azad University of Isfahan (Khorasgan) Branch, Isfahan, Iran
  7. 7. Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Source: Journal of Clinical Neuroscience Published:2025


Abstract

Background: Declines in regional cerebral blood flow (rCBF) are common in Alzheimer's disease. Previous studies have linked higher amyloid beta-protein (Aβ) loads, detected by Positron Emission Tomography (PET), with rCBF in normally aging individuals. This study aims to assess the potential of Arterial Spin Labeling (ASL) in predicting brain amyloidosis. Methods: The study included 140 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI), comprising 43 cognitively normal (CN) individuals, 70 patients with mild cognitive impairment (MCI), and 27 with Alzheimer's disease (AD). Eligible participants had comprehensive assessments of cognition, ASL, Apolipoprotein E4 (APOE4) genotyping, Polygenic Hazard Score (PHS) calculation, and amyloidosis indices. Data were analyzed using IBM SPSS ver. 20, employing chi-square, ANOVA, and linear regression models, with a significance threshold of P < 0.05. Results: There were no statistically significant differences in demographic characteristics, including age, gender, and education level. Significant differences emerged in amyloid beta-protein 42 (Aβ42) levels, APOE4 status, and cognitive performance across groups. Four brain regions, including the left middle temporal, bilateral para-hippocampal, and right lingual cortex exhibited significant CBF differences (p < 0.05). Clinical Dementia Rating (CDR) correlated strongly with various brain regions, particularly in MCI individuals. Moreover, CBF in multiple regions showed significant associations with Aβ variants and their ratios, especially Aβ42, even after adjusting for confounding factors. Conclusion: ASL demonstrates potential in predicting brain amyloidosis and monitoring AD. Significant associations between CBF and amyloid-beta levels suggest that ASL can detect early perfusion deficits related to AD progression. © 2025 Elsevier Ltd
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