Teune Laura K, Strijkert Fijanne, Renken Remco J, Izaks Gerbrand J, de Vries Jeroen J, Segbers Marcel, Roerdink Jos B T M, Dierckx Rudi A J O, Leenders Klaus L
Department of Neurology, University Medical Center Groningen, Hanzeplein 1, Postbus 30.001, 9700 RB Groningen, The Netherlands.
Curr Alzheimer Res. 2014;11(8):725-32. doi: 10.2174/156720501108140910114230.
[(18)F]fluorodeoxyglucose (FDG) PET imaging of the brain can be used to assist in the differential diagnosis of dementia. Group differences in glucose uptake between patients with dementia and controls are well-known. However, a multivariate analysis technique called scaled subprofile model, principal component analysis (SSM/PCA) aiming at identifying diagnostic neural networks in diseases, have been applied less frequently. We validated an Alzheimer's Disease-related (AD) glucose metabolic brain pattern using the SSM/PCA analysis and applied it prospectively in an independent confirmation cohort.
We used FDG-PET scans of 18 healthy controls and 15 AD patients (identification cohort) to identify an AD-related glucose metabolic covariance pattern. In the confirmation cohort (n=15), we investigated the ability to discriminate between probable AD and non-probable AD (possible AD, mild cognitive impairment (MCI) or subjective complaints).
The AD-related metabolic covariance pattern was characterized by relatively decreased metabolism in the temporoparietal regions and relatively increased metabolism in the subcortical white matter, cerebellum and sensorimotor cortex. Receiver-operating characteristic (ROC) curves showed at a cut-off value of z=1.23, a sensitivity of 93% and a specificity of 94% for correct AD classification. In the confirmation cohort, subjects with clinically probable AD diagnosis showed a high expression of the AD-related pattern whereas in subjects with a non-probable AD diagnosis a low expression was found.
The Alzheimer's disease-related cerebral glucose metabolic covariance pattern identified by SSM/PCA analysis was highly sensitive and specific for Alzheimer's disease. This method is expected to be helpful in the early diagnosis of Alzheimer's disease in clinical practice.
脑[（18）F]氟脱氧葡萄糖（FDG）PET成像可用于辅助痴呆的鉴别诊断。痴呆患者与对照组之间葡萄糖摄取的组间差异是众所周知的。然而，一种称为缩放子剖面模型主成分分析（SSM/PCA）的多变量分析技术，旨在识别疾病中的诊断神经网络，应用较少。我们使用SSM/PCA分析验证了一种与阿尔茨海默病相关（AD）的葡萄糖代谢脑模式，并将其前瞻性地应用于一个独立的验证队列中。
我们使用18名健康对照者和15名AD患者（识别队列）的FDG-PET扫描来识别与AD相关的葡萄糖代谢协方差模式。在验证队列（n = 15）中，我们研究了区分可能的AD与非可能的AD（可能的AD、轻度认知障碍（MCI）或主观症状）的能力。
与AD相关的代谢协方差模式的特征是颞顶叶区域代谢相对降低，皮质下白质、小脑和感觉运动皮质代谢相对增加。受试者工作特征（ROC）曲线显示，在z = 1.23的临界值时，正确AD分类的灵敏度为93%，特异性为94%。在验证队列中，临床诊断为可能AD的受试者显示出与AD相关模式的高表达，而在非可能AD诊断的受试者中发现低表达。
通过SSM/PCA分析确定的与阿尔茨海默病相关的脑葡萄糖代谢协方差模式对阿尔茨海默病具有高度敏感性和特异性。该方法有望在临床实践中有助于阿尔茨海默病的早期诊断。
