Azari N P, Pettigrew K D, Schapiro M B, Haxby J V, Grady C L, Pietrini P, Salerno J A, Heston L L, Rapoport S I, Horwitz B
Laboratory of Neurosciences/National Institute on Aging/National Institutes of Health, Bethesda, Maryland 20892.
J Cereb Blood Flow Metab. 1993 May;13(3):438-47. doi: 10.1038/jcbfm.1993.58.
Correlational analysis of regional cerebral glucose metabolism (rCMRglc) obtained by high-resolution positron emission tomography (PET) has demonstrated reduced neocortical rCMRglc interactions in mildly/moderately demented patients with probable Alzheimer's disease (AD). Thus, identification of individual differences in patterns of rCMRglc interactions may be important for the early detection of AD, particularly among individuals at greater risk for developing AD (e.g., those with a family history of AD). Recently, a statistical procedure, using multiple regression and discriminant analysis, was developed to assess individual differences in patterns of rCMRglc interdependencies. We applied this new statistical procedure to resting rCMRglc PET data from mildly/moderately demented patients with probable AD and age/sex-matched controls. The aims of the study were to identify a discriminant function that would (a) distinguish patients from controls and (b) identify an AD pattern in an individual at risk for AD with isolated memory impairment whose initial PET scan showed minor abnormalities, but whose second scan showed parietal hypometabolism, coincident with further cognitive decline. Two discriminant functions, reflecting interactions involving regions most involved in reduced correlations in probable AD, correctly classified 87% of the patients and controls, and successfully identified the first scan of the at-risk individual as AD (probability > 0.70). The results suggest that this statistical approach may be useful for the early detection of AD.
通过高分辨率正电子发射断层扫描（PET）获得的局部脑葡萄糖代谢（rCMRglc）的相关性分析表明，轻度/中度痴呆的可能阿尔茨海默病（AD）患者的新皮质rCMRglc相互作用降低。因此，识别rCMRglc相互作用模式的个体差异对于AD的早期检测可能很重要，特别是在患AD风险较高的个体中（例如，有AD家族史的个体）。最近，开发了一种使用多元回归和判别分析的统计程序，以评估rCMRglc相互依存模式的个体差异。我们将这种新的统计程序应用于轻度/中度痴呆的可能AD患者和年龄/性别匹配的对照组的静息rCMRglc PET数据。该研究的目的是确定一个判别函数，该函数将（a）区分患者和对照组，以及（b）在有孤立记忆障碍且初始PET扫描显示轻微异常但第二次扫描显示顶叶代谢减退且与进一步认知衰退一致的AD风险个体中识别出AD模式。两个判别函数反映了可能AD中相关性降低最相关区域的相互作用，正确分类了87%的患者和对照组，并成功将风险个体的第一次扫描识别为AD（概率>0.70）。结果表明，这种统计方法可能有助于AD的早期检测。
