Detecting Beta-amyloid Plaque via Low Rank Based Orthogonal Projection and Spatial-spectrum Detector Using High-resolution Quantitative Susceptibility Mapping for Preclinical Studies

Detecting beta-amyloid (Aβ) plaques at different stages is crucial for accurate assessment and effective intervention in Alzheimer's disease (AD). In this study, we developed a novel method for reliably identifying Aβ plaques, characterized by sparse negative susceptibility values, in preclinical studies using high-resolution quantitative susceptibility mapping (QSM), named QSM-PLAQUE Aβ Detector. This approach decomposes a high-resolution QSM MRI image into three components: L (representing the background subspace), S (representing the signals subspace), and N (representing the noise). Subsequently, we established an orthogonal subspace based on L to eliminate the background from the sum of L and S. Finally, a plaque detection process was conducted, where Aβ plaques were identified based on the neighbor spectrum (NS) of a voxel being tested rather than just analyzing the voxel itself alone. Experiments demonstrated that the proposed method effectively detects Aβ plaques of varying shapes and intensities across the entire mouse brain. It shows robust performance across histology, highresolution QSM MRI, and synthesized datasets, without requiring training samples. The QSM-PLAQUE Aβ Detector provides a practical framework for identifying and visualizing Aβ plaques in preclinical studies, offering a new strategy for quantitative assessment of Aβ plaques and may guide the development of advanced techniques for preclinical AD research.