Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India.
Department of Neurology, Cardiothoracic and Neurosciences Centre, All India Institute of Medical Sciences, New Delhi, India.
Neurol India. 2019 Sep-Oct;67(5):1310-1317. doi: 10.4103/0028-3886.271245.
Metabolic patterns on brain F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) can predict the decline in amnestic mild cognitive impairment (aMCI) to Alzheimer's disease dementia (AD) or other dementias.
This study was undertaken to evaluate the diagnostic accuracy of baseline F-18 FDG-PET in aMCI for predicting conversion to AD or other dementias on follow-up.
A total of 87 patients with aMCI were enrolled in the study. Each patient underwent a detailed clinical and neuropsychological examination and FDG-PET at baseline. Each PET scan was visually classified based on predefined dementia patterns. Automated analysis of FDG PET was performed using Cortex ID (GE Healthcare). The mean follow-up duration was 30.4 ± 9.3 months (range: 18-48 months). Diagnosis of dementia at follow-up (obtained using clinical diagnostic criteria) constituted the reference standard, and all the included aMCI patients were divided into two groups: the aMCI converters (MCI-C) and MCI nonconverters (MCI-NC). Diagnostic accuracy of FDG PET was calculated using this reference standard.
There were 23 MCI-C and 64 MCI-NC. Of the 23 MCI-C, 19 were diagnosed as probable AD, 1 as frontotemporal demetia (FTD), and 3 as vascular dementia (VD). Of the 64 MCI-NC, 9 had subjective improvement in cognition, and 55 remained stable. The conversion rate for all types of dementia in our series was 26.4% (23/87) and for Alzheimer's type dementia was 21.8% (19/87). The of PET-based visual interpretation was 91.9%. Sensitivity, specificity, positive predictive value, and negative predictive value for FDG-PET-based prediction of dementia conversion were 86.9% [confidence interval (CI) 66.4%-97.2%)], 93.7% (CI 84.7%-98.2%), 83.3% (CI 65.6%-92.9%), and 95.2% (CI 87.4%-98.9%), respectively. Kappa for agreement between visual and Cortex ID was 0.94 indicating excellent agreement. In the three aMCI patients progressing to VD, no specific abnormality in metabolic pattern was noted; however, there was marked cortical atrophy on computed tomography.
FDG-PET-based visual and cortex ID classification has a good accuracy in predicting progression to dementia including AD in the prodromal aMCI phase. Absence of typical metabolic patterns on FDG-PET can play an important exclusionary role for progression to dementia. Vascular cognitive impairment with cerebral atrophy needs further studies to confirm and uncover potential mechanisms.
脑 F-18 氟脱氧葡萄糖（FDG）正电子发射断层扫描（PET）的代谢模式可预测遗忘型轻度认知障碍（aMCI）向阿尔茨海默病痴呆（AD）或其他痴呆的下降。
本研究旨在评估基线 F-18 FDG-PET 在 aMCI 中的诊断准确性，以预测随访时向 AD 或其他痴呆的转化。
共纳入 87 例 aMCI 患者。每位患者均在基线时接受详细的临床和神经心理学检查和 FDG-PET。根据预先定义的痴呆模式对每个 PET 扫描进行视觉分类。使用 Cortex ID（GE Healthcare）对 FDG PET 进行自动分析。平均随访时间为 30.4±9.3 个月（范围：18-48 个月）。随访时的痴呆诊断（使用临床诊断标准获得）构成参考标准，所有纳入的 aMCI 患者分为两组：aMCI 转化者（MCI-C）和 MCI 非转化者（MCI-NC）。使用该参考标准计算 FDG-PET 的诊断准确性。
有 23 例 MCI-C 和 64 例 MCI-NC。在 23 例 MCI-C 中，19 例诊断为可能的 AD，1 例为额颞叶痴呆（FTD），3 例为血管性痴呆（VD）。在 64 例 MCI-NC 中，9 例认知主观改善，55 例稳定。我们系列中所有类型痴呆的转化率为 26.4%（23/87），阿尔茨海默病型痴呆的转化率为 21.8%（19/87）。基于 PET 的视觉解释的准确率为 91.9%。基于 FDG-PET 的痴呆转化预测的敏感性、特异性、阳性预测值和阴性预测值分别为 86.9%（置信区间 66.4%-97.2%）、93.7%（置信区间 84.7%-98.2%）、83.3%（置信区间 65.6%-92.9%）和 95.2%（置信区间 87.4%-98.9%）。视觉和 Cortex ID 之间的一致性kappa 值为 0.94，表明一致性极好。在进展为 VD 的 3 例 aMCI 患者中，未发现代谢模式的特定异常；然而，CT 显示明显的皮质萎缩。
基于 FDG-PET 的视觉和皮质 ID 分类在预测前驱期 aMCI 向痴呆（包括 AD）的进展方面具有良好的准确性。FDG-PET 上缺乏典型的代谢模式可对向痴呆的进展起到重要的排除作用。伴有脑萎缩的血管性认知障碍需要进一步研究来证实并揭示潜在的机制。
