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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Material-based neuroimaging and biomarker detection for central nervous system disorder
Liqun Yu1,2, Yanjing Zhu1,2,3,4, Xinxin Zheng1,2
1Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Tongji Hospital Affiliated to Tongji University, School of Medicine, School of Life Science and Technology, Tongji University, Shanghai, 200065, China.
None:
Central nervous system (CNS) disorders, including neurodegenerative diseases, brain tumors, and cerebrovascular conditions, remain difficult to detect at early stages due to nonspecific clinical manifestations, limited sensitivity of conventional diagnostic methods, and the restrictive nature of the blood-brain barrier (BBB). Recent advances in nanomaterials offer transformative potential for neuroimaging and biomarker detection, enabling high resolution, targeted, and multimodal diagnostics. This review summarizes progress in material-based magnetic resonance imaging, positron emission tomography, and emerging modalities such as photoacoustic, near-infrared, and surface-enhanced Raman scattering imaging, as well as nanoparticle-enabled biosensors for detecting Aβ, tau, α-synuclein, neurofilament light chain, and microRNAs in cerebrospinal fluid, blood, and other biofluids. The integration of multimodal imaging platforms with artificial intelligence and high-throughput optimization offers improved BBB penetration, targeting precision, and patient-specific diagnostic strategies. Future translation will depend on rigorous safety profiling, standardized performance metrics, and validation in large multicenter trials. Collectively, these material-enabled platforms are poised to advance precision diagnostics and therapeutic monitoring, offering new possibilities for improving clinical outcomes in CNS disorders.

