定量磁化率图
神经退行性变
痴呆
抗磁性
白质
正电子发射断层摄影术
标准摄取值
体素
病态的
病理
神经科学
脑脊液
磁共振成像
疾病
医学
核磁共振
生物
物理
放射科
量子力学
磁场
作者
Maruf Ahmed,Jingjia Chen,Arvin Arani,Matthew L. Senjem,Petrice M. Cogswell,Clifford R. Jack,Chunlei Liu
出处
期刊:NeuroImage
[Elsevier BV]
日期:2023-09-01
卷期号:280: 120357-120357
被引量:17
标识
DOI:10.1016/j.neuroimage.2023.120357
摘要
A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.
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