MRAβ: A multimodal MRI-derived amyloid-β biomarker for Alzheimer's disease

• Published in: Human brain mapping 2023-10, Vol.44 (15), p.5139-5152
• Main Authors: Zhang, Yu, Li, Xi, Ji, Yi, Ding, Hao, Suo, Xinjun, He, Xiaoxi, Xie, Yingying, Liang, Meng, Zhang, Shijie, Yu, Chunshui, Qin, Wen
• Format: Article
• Language: English
• Subjects: Alzheimer's disease; Biomarkers; Cognition & reasoning; Cognitive ability; Datasets; Generative adversarial networks; Magnetic resonance imaging; Neurodegenerative diseases; Positron emission; Spatial variations; β-Amyloid
• ISSN: 1065-9471; 1097-0193; 1097-0193
• DOI: 10.1002/hbm.26452

Florbetapir F (AV45), a highly sensitive and specific positron emission tomographic (PET) molecular biomarker binding to the amyloid-β of Alzheimer's disease (AD), is constrained by radiation and cost. We sought to combat it by combining multimodal magnetic resonance imaging (MRI) images and a collaborative generative adversarial networks model (CollaGAN) to develop a multimodal MRI-derived Amyloid-β (MRAβ) biomarker. We collected multimodal MRI and PET AV45 data of 380 qualified participants from the ADNI dataset and 64 subjects from OASIS3 dataset. A five-fold cross-validation CollaGAN were applied to generate MRAβ. In the ADNI dataset, we found MRAβ could characterize the subject-level AV45 spatial variations in both AD and mild cognitive impairment (MCI). Voxel-wise two-sample t-tests demonstrated amyloid-β depositions identified by MRAβ in AD and MCI were significantly higher than healthy controls (HCs) in widespread cortices (p  .92, p