Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment

V. Camus; P. Payoux; L. Barré; B. Desgranges; T. Voisin; C. Tauber; R. La Joie; M. Tafani; C. Hommet; G. Chételat

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Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment

机译：将PET与 18 F-AV-45（florbetapir）结合使用以量化临床环境中的脑淀粉样蛋白负荷

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Purpose Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer’s disease (AD). The aim of this study was to test the feasibility of using PET imaging with 18F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC).

机译：目的正电子发射断层扫描（PET）对脑淀粉样蛋白负荷的成像已被建议作为阿尔茨海默氏病（AD）的核心生物标志物。这项研究的目的是测试在常规临床环境中将PET成像与 18 F-AV-45（florbetapir）进行区分在轻度至中度AD和轻度认知障碍患者中的可行性（正常健康对照（HC）。

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《European Journal of Nuclear Medicine and Molecular Imaging》 |2012年第4期|p.621-631|共11页
作者
V. Camus; P. Payoux; L. Barré; B. Desgranges; T. Voisin; C. Tauber; R. La Joie; M. Tafani; C. Hommet; G. Chételat;
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1. Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment. [J] . V Camus, P Payoux, L Barré, European Journal of Nuclear Medicine and Molecular Imaging . 2012,第4期

机译：将PET与18F-AV-45（florbetapir）结合使用以量化临床环境中的脑淀粉样蛋白负荷。
2. Amyloid deposition detected with florbetapir F 18 (18F-AV-45) is related to lower episodic memory performance in clinically normal older individuals [J] . SperlingR.A., JohnsonK.A., DoraiswamyP.M., Neurobiology of Aging: Experimental and Clinical Research . 2013,第3期

机译：在临床正常的老年人中，用florbetapir F 18（18F-AV-45）检测到的淀粉样蛋白沉积与较低的情景记忆表现有关
3. QUANTIFICATION OF AMYLOID BURDEN FROM FLORBETAPIR PET WITHOUT USING TARGET AND REFERENCE REGIONS: PRELIMINARY FINDINGS BASED ON THE DEEP LEARNING 3D CONVOLUTIONAL NEURAL NETWORK APPROACH [J] . Ye Yuan, Zhangyang Wang, Wendy Lee, Alzheimer’s & dementia: the journal of the Alzheimer’s Association . 2018,第7期

机译：不使用目标和参考区域的氟玻璃宠物的淀粉样蛋白负荷的定量：基于深度学习3D卷积神经网络方法的初步调查
4. Deep Learning-Based Estimation of Non-Specific Uptake in Amyloid-PET Images from Structural MRI for Improved Quantification of Amyloid Load in Alzheimer's Disease [C] . Haohui Liu, Ying-Hwey Nai, Christopher Chen, IEEE International Symposium on Computer-Based Medical Systems . 2020

机译：基于深度学习的结构性MRI对非特异性摄取淀粉样PET图像的估计，以改善量化阿尔茨海默氏病的淀粉样负荷
5. Improving quantification and detection in PET imaging: Methods for image generation, analysis, and consequential clinical considerations. [D] . Kesner, Adam Leon. 2008

机译：改进PET成像中的定量和检测：图像生成，分析和相应的临床考虑的方法。
6. Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment [O] . V. Camus, P. Payoux, L. Barré, -1

机译：将PET与18F-AV-45（florbetapir）结合使用以量化临床环境中的脑淀粉样蛋白负荷
7. Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment [O] . V. Camus, P. Payoux, L. Barré, 2012

机译：将PET与18F-AV-45（florbetapir）结合使用以量化临床环境中的脑淀粉样蛋白负荷

Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment

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