Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer’s Disease

被引:0
作者
Rachel F. Buckley
机构
[1] Massachusetts General Hospital & Brigham and Women’s,Department of Neurology
[2] Harvard Medical School,Melbourne School of Psychological Sciences and Florey Institutes
[3] University of Melbourne,Department of Neurology
[4] Massachusetts General Hospital,undefined
来源
Neurotherapeutics | 2021年 / 18卷
关键词
Alzheimer’s disease; Neuroimaging; Positron emission tomography; Magnetic resonance imaging; Autosomal dominant; Preclinical AD;
D O I
暂无
中图分类号
学科分类号
摘要
Observing Alzheimer’s disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.
引用
收藏
页码:709 / 727
页数:18
相关论文
共 230 条
[1]  
Jack CR(2016)A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers Neurology 87 539-547
[2]  
Jack CR(2013)Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers Lancet Neurol 12 207-216
[3]  
La Joie R(2019)Multisite study of the relationships between antemortem [11C] PIB-PET Centiloid values and postmortem measures of Alzheimer's disease neuropathology Alzheimer's & Dementia 15 205-216
[4]  
Jansen WJ(2018)Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia JAMA Psychiatry 75 84-95
[5]  
Franzmeier N(2020)Functional brain architecture is associated with the rate of tau accumulation in Alzheimer’s disease Nature Communications 11 347-1385
[6]  
Mormino EC(2014)Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals JAMA Neurology 71 1379-319
[7]  
Klunk WE(2004)Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B Annals of Neurology 55 306-1547
[8]  
Price JC(2005)Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B Journal of Cerebral Blood Flow & Metabolism 25 1528-384
[9]  
Joshi AD(2012)Performance characteristics of amyloid PET with florbetapir F 18 in patients with Alzheimer's disease and cognitively normal subjects Journal of Nuclear Medicine 53 378-77
[10]  
Landau SM(2013)Amyloid-β imaging with Pittsburgh compound B and florbetapir: comparing radiotracers and quantification methods Journal of Nuclear Medicine 54 70-2059