McEvoy Linda K, Fennema-Notestine Christine, Roddey J Cooper, Hagler Donald J, Holland Dominic, Karow David S, Pung Christopher J, Brewer James B, Dale Anders M
Department of Radiology, University of California, San Diego, 9500 Gilman Dr, La Jolla, CA 92093-0841, USA.
Radiology. 2009 Apr;251(1):195-205. doi: 10.1148/radiol.2511080924. Epub 2009 Feb 6.
To use structural magnetic resonance (MR) images to identify a pattern of regional atrophy characteristic of mild Alzheimer disease (AD) and to investigate whether presence of this pattern prospectively can aid prediction of 1-year clinical decline and increased structural loss in mild cognitive impairment (MCI).
The study was conducted with institutional review board approval and compliance with HIPAA regulations. Written informed consent was obtained from each participant. High-throughput volumetric segmentation and cortical surface reconstruction methods were applied to MR images from 84 subjects with mild AD, 175 with MCI, and 139 healthy control (HC) subjects. Stepwise linear discriminant analysis was used to identify regions that best can aid discrimination of HC subjects from subjects with AD. A classifier trained on data from HC subjects and those with AD was applied to data from subjects with MCI to determine whether presence of phenotypic AD atrophy at baseline was predictive of clinical decline and structural loss.
Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%. Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not).
Semiautomated, individually specific quantitative MR imaging methods can be used to identify a pattern of regional atrophy in MCI that is predictive of clinical decline. Such information may aid in prediction of patient prognosis and increase the efficiency of clinical trials.
利用结构磁共振(MR)图像识别轻度阿尔茨海默病(AD)特有的区域萎缩模式,并研究这种模式的存在是否能前瞻性地辅助预测轻度认知障碍(MCI)患者1年的临床衰退情况及结构损伤增加情况。
本研究经机构审查委员会批准并符合健康保险流通与责任法案(HIPAA)规定。获得了每位参与者的书面知情同意书。采用高通量容积分割和皮质表面重建方法,对84例轻度AD患者、175例MCI患者及139例健康对照(HC)者的MR图像进行分析。采用逐步线性判别分析来识别最有助于区分HC者与AD患者的区域。将基于HC者和AD患者数据训练的分类器应用于MCI患者的数据,以确定基线时表型AD萎缩的存在是否可预测临床衰退和结构损伤。
内侧和外侧颞叶、扣带回峡部及眶额叶区域的萎缩有助于区分HC者与AD患者,完全交叉验证的敏感度为83%,特异度为93%。有表型AD萎缩的MCI患者1年的临床衰退和结构损伤明显大于无萎缩者,且更有可能进展为可能的AD(有AD萎缩的MCI患者年进展率为29%,无萎缩者为8%)。
半自动化、个体化的定量MR成像方法可用于识别MCI患者中预测临床衰退的区域萎缩模式。此类信息可能有助于预测患者预后并提高临床试验效率。