Walhovd K B, Fjell A M, Amlien I, Grambaite R, Stenset V, Bjørnerud A, Reinvang I, Gjerstad L, Cappelen T, Due-Tønnessen P, Fladby T
Center for the Study of Human Cognition, Department of Psychology, University of Oslo, Norway.
Neuroimage. 2009 Mar 1;45(1):215-23. doi: 10.1016/j.neuroimage.2008.10.053. Epub 2008 Nov 13.
This study compared sensitivity of FDG-PET, MR morphometry, and diffusion tensor imaging (DTI) derived fractional anisotropy (FA) measures to diagnosis and memory function in mild cognitive impairment (MCI). Patients (n=44) and normal controls (NC, n=22) underwent FDG-PET and MRI scanning yielding measures of metabolism, morphometry and FA in nine temporal and parietal areas affected by Alzheimer's disease and involved in the episodic memory network. Patients also underwent memory testing (RAVLT). Logistic regression analysis yielded 100% diagnostic accuracy when all methods and ROIs were combined, but none of the variables then served as unique predictors. Within separate ROIs, diagnostic accuracy for the methods combined ranged from 65.6% (parahippocampal gyrus) to 73.4 (inferior parietal cortex). Morphometry predicted diagnostic group for most ROIs. PET and FA did not uniquely predict group, but a trend was seen for the precuneus metabolism. For the MCI group, stepwise regression analyses predicting memory scores were performed with the same methods and ROIs. Hippocampal volume and FA of the retrosplenial WM predicted learning, and hippocampal metabolism and parahippocampal cortical thickness predicted 5 minute recall. No variable predicted 30 minute recall independently of learning. In conclusion, higher diagnostic accuracy was achieved when multiple methods and ROIs were combined, but morphometry showed superior diagnostic sensitivity. Metabolism, morphometry and FA all uniquely explained memory performance, making a multi-modal approach superior. Memory variation in MCI is likely related to conversion risk, and the results indicate potential for improved predictive power by the use of multimodal imaging.
本研究比较了氟代脱氧葡萄糖正电子发射断层扫描（FDG-PET）、磁共振形态测量学以及扩散张量成像（DTI）衍生的分数各向异性（FA）测量值对轻度认知障碍（MCI）的诊断及记忆功能的敏感性。44例患者和22例正常对照（NC）接受了FDG-PET和MRI扫描，得出了9个受阿尔茨海默病影响且参与情景记忆网络的颞叶和顶叶区域的代谢、形态测量学和FA测量值。患者还接受了记忆测试（雷伊听觉词语学习测验）。当所有方法和感兴趣区（ROI）相结合时，逻辑回归分析得出的诊断准确率为100%，但此时没有一个变量可作为唯一预测指标。在单独的ROI内，联合方法的诊断准确率在65.6%（海马旁回）至73.4%（顶下小叶）之间。形态测量学可预测大多数ROI的诊断分组。PET和FA不能唯一预测分组，但楔前叶代谢存在一种趋势。对于MCI组，使用相同的方法和ROI进行逐步回归分析以预测记忆分数。海马体积和压后白质的FA可预测学习情况，海马代谢和海马旁回皮质厚度可预测5分钟回忆情况。没有变量能独立于学习情况预测30分钟回忆情况。总之，当多种方法和ROI相结合时可获得更高的诊断准确率，但形态测量学显示出更高的诊断敏感性。代谢、形态测量学和FA均能唯一解释记忆表现，多模态方法更具优势。MCI中的记忆变异可能与转化风险相关，结果表明使用多模态成像有可能提高预测能力。
