Tanpitukpongse T P, Mazurowski M A, Ikhena J, Petrella J R
From the Department of Radiology (T.P.T., M.A.M., J.R.P.), Duke University Medical Center, Durham, North Carolina.
Duke University School of Medicine (J.I.), Durham, North Carolina.
AJNR Am J Neuroradiol. 2017 Mar;38(3):546-552. doi: 10.3174/ajnr.A5061. Epub 2017 Jan 5.
Alzheimer disease is a prevalent neurodegenerative disease. Computer assessment of brain atrophy patterns can help predict conversion to Alzheimer disease. Our aim was to assess the prognostic efficacy of individual-versus-combined regional volumetrics in 2 commercially available brain volumetric software packages for predicting conversion of patients with mild cognitive impairment to Alzheimer disease.
Data were obtained through the Alzheimer's Disease Neuroimaging Initiative. One hundred ninety-two subjects (mean age, 74.8 years; 39% female) diagnosed with mild cognitive impairment at baseline were studied. All had T1-weighted MR imaging sequences at baseline and 3-year clinical follow-up. Analysis was performed with NeuroQuant and Neuroreader. Receiver operating characteristic curves assessing the prognostic efficacy of each software package were generated by using a univariable approach using individual regional brain volumes and 2 multivariable approaches (multiple regression and random forest), combining multiple volumes.
On univariable analysis of 11 NeuroQuant and 11 Neuroreader regional volumes, hippocampal volume had the highest area under the curve for both software packages (0.69, NeuroQuant; 0.68, Neuroreader) and was not significantly different ( > .05) between packages. Multivariable analysis did not increase the area under the curve for either package (0.63, logistic regression; 0.60, random forest NeuroQuant; 0.65, logistic regression; 0.62, random forest Neuroreader).
Of the multiple regional volume measures available in FDA-cleared brain volumetric software packages, hippocampal volume remains the best single predictor of conversion of mild cognitive impairment to Alzheimer disease at 3-year follow-up. Combining volumetrics did not add additional prognostic efficacy. Therefore, future prognostic studies in mild cognitive impairment, combining such tools with demographic and other biomarker measures, are justified in using hippocampal volume as the only volumetric biomarker.
阿尔茨海默病是一种常见的神经退行性疾病。脑萎缩模式的计算机评估有助于预测向阿尔茨海默病的转化。我们的目的是评估两款市售脑容积软件包中个体与联合区域容积测量法在预测轻度认知障碍患者向阿尔茨海默病转化方面的预后效果。
数据通过阿尔茨海默病神经影像倡议获取。研究了192名基线时被诊断为轻度认知障碍的受试者(平均年龄74.8岁;39%为女性)。所有受试者在基线和3年临床随访时均有T1加权磁共振成像序列。使用NeuroQuant和Neuroreader进行分析。通过单变量方法使用个体区域脑容积以及两种多变量方法(多元回归和随机森林)结合多个容积来生成评估每个软件包预后效果的受试者操作特征曲线。
对11个NeuroQuant区域容积和11个Neuroreader区域容积进行单变量分析时,海马体容积在两个软件包中曲线下面积最高(NeuroQuant为0.69;Neuroreader为0.68),且两个软件包之间无显著差异(P>.05)。多变量分析未增加任何一个软件包的曲线下面积(NeuroQuant的逻辑回归为0.63,随机森林为0.60;Neuroreader的逻辑回归为0.65,随机森林为0.62)。
在FDA批准的脑容积软件包中可用的多种区域容积测量方法中,海马体容积在3年随访时仍然是轻度认知障碍向阿尔茨海默病转化的最佳单一预测指标。结合容积测量法并未增加额外的预后效果。因此,未来在轻度认知障碍中的预后研究,将此类工具与人口统计学和其他生物标志物测量相结合,有理由将海马体容积作为唯一的容积生物标志物。