Helen Wills Neuroscience Institute, University of California, Berkeley2Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany3German Center for Neurodegenerative Diseases, Magdeburg.
Helen Wills Neuroscience Institute, University of California, Berkeley4Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.
JAMA Neurol. 2015 Oct;72(10):1183-90. doi: 10.1001/jamaneurol.2015.1633.
The applicability of β-amyloid peptide (Aβ) positron emission tomography (PET) as a biomarker in clinical settings to aid in selection of individuals at preclinical and prodromal Alzheimer disease (AD) will depend on the practicality of PET image analysis. In this context, visual-based Aβ PET assessment seems to be the most feasible approach.
To determine the agreement between visual and quantitative Aβ PET analysis and to assess the ability of both techniques to predict conversion from mild cognitive impairment (MCI) to AD.
DESIGN, SETTING, AND PARTICIPANTS: A longitudinal study was conducted among the Alzheimer's Disease Neuroimaging Initiative (ADNI) sites in the United States and Canada during a 1.6-year mean follow-up period. The study was performed from September 21, 2010, to August 11, 2014; data analysis was conducted from September 21, 2014, to May 26, 2015. Participants included 401 individuals with MCI receiving care at a specialty clinic (219 [54.6%] men; mean [SD] age, 71.6 [7.5] years; 16.2 [2.7] years of education). All participants were studied with florbetapir F 18 [18F] PET. The standardized uptake value ratio (SUVR) positivity threshold was 1.11, and one reader rated all images, with a subset of 125 scans rated by a second reader.
Sensitivity and specificity of positive and negative [18F] florbetapir PET categorization, which was estimated with cerebrospinal fluid Aβ1-42 as the reference standard. Risk for conversion to AD was assessed using Cox proportional hazards regression models.
The frequency of Aβ positivity was 48.9% (196 patients; visual analysis), 55.1% (221 patients; SUVR), and 64.8% (166 patients; cerebrospinal fluid), yielding substantial agreement between visual and SUVR data (κ = 0.74) and between all methods (Fleiss κ = 0.71). For approximately 10% of the 401 participants in whom visual and SUVR data disagreed, interrater reliability was moderate (κ = 0.44), but it was very high if visual and quantitative results agreed (κ = 0.92). Visual analysis had a lower sensitivity (79% vs 85%) but higher specificity (96% vs 90%), respectively, compared with SUVR. The conversion rate was 15.2% within a mean of 1.6 years, and a positive [18F] florbetapir baseline scan was associated with a 6.91-fold (SUVR) or 11.38-fold (visual) greater hazard for AD conversion, which changed only modestly after covariate adjustment for apolipoprotein ε4, concurrent fludeoxyglucose F 18 PET scan, and baseline cognitive status.
Visual and SUVR Aβ PET analysis may be equivalently used to determine Aβ status for individuals with MCI participating in clinical trials, and both approaches add significant value for clinical course prognostication.
β-淀粉样蛋白肽(Aβ)正电子发射断层扫描(PET)作为一种生物标志物在临床中的应用,以帮助选择临床前和前驱期阿尔茨海默病(AD)患者,这将取决于 PET 图像分析的实用性。在这种情况下,基于视觉的 Aβ PET 评估似乎是最可行的方法。
确定视觉和定量 Aβ PET 分析之间的一致性,并评估这两种技术预测从轻度认知障碍(MCI)向 AD 转化的能力。
设计、地点和参与者:这是一项在美国和加拿大的阿尔茨海默病神经影像学倡议(ADNI)站点进行的纵向研究,平均随访时间为 1.6 年。该研究于 2010 年 9 月 21 日至 2014 年 8 月 11 日进行;数据分析于 2014 年 9 月 21 日至 2015 年 5 月 26 日进行。参与者包括在专门诊所接受治疗的 401 名 MCI 患者(219 [54.6%]名男性;平均[标准差]年龄为 71.6 [7.5]岁;受教育年限为 16.2 [2.7]年)。所有参与者均接受氟比他滨 F 18 [18F] PET 检查。标准摄取值比(SUVR)阳性阈值为 1.11,一名读者对所有图像进行评分,其中 125 份扫描由第二名读者进行评分。
以脑脊液 Aβ1-42 为参考标准,估计阳性和阴性[18F]氟比他滨 PET 分类的敏感性和特异性。使用 Cox 比例风险回归模型评估向 AD 转化的风险。
Aβ 阳性率为 48.9%(196 例患者;视觉分析)、55.1%(221 例患者;SUV)和 64.8%(166 例患者;脑脊液),视觉和 SUV 数据之间存在高度一致性(κ=0.74),以及所有方法之间的一致性(Fleiss κ=0.71)。在 401 名参与者中,约有 10%的视觉和 SUV 数据不一致,两名评分者之间的可靠性为中度(κ=0.44),但如果视觉和定量结果一致,则可靠性非常高(κ=0.92)。与 SUVR 相比,视觉分析的敏感性较低(79%比 85%),但特异性较高(96%比 90%)。平均 1.6 年内的转化率为 15.2%,阳性[18F]氟比他滨基线扫描与 AD 转化率增加 6.91 倍(SUV)或 11.38 倍(视觉)相关,这一风险在调整载脂蛋白 E4、同时进行的氟脱氧葡萄糖 F 18 PET 扫描和基线认知状态等混杂因素后变化不大。
视觉和 SUVR Aβ PET 分析可用于确定参与临床试验的 MCI 患者的 Aβ 状态,这两种方法都为临床病程预测提供了重要价值。