Potvin Olivier, Dieumegarde Louis, Duchesne Simon
Centre de recherche CERVO Research Center, 2601, de la Canardière, Québec, Canada G1J 2G3.
Centre de recherche CERVO Research Center, 2601, de la Canardière, Québec, Canada G1J 2G3; Département de radiologie, Faculté de médecine, Université Laval, 1050, avenue de la Médecine, Québec, Canada G1V 0A6.
Neuroimage. 2017 Aug 1;156:315-339. doi: 10.1016/j.neuroimage.2017.05.019. Epub 2017 May 13.
Proper normative data of anatomical measurements of cortical regions, allowing to quantify brain abnormalities, are lacking. We developed norms for regional cortical surface areas, thicknesses, and volumes based on cross-sectional MRI scans from 2713 healthy individuals aged 18 to 94 years using 23 samples provided by 21 independent research groups. The segmentation was conducted using FreeSurfer, a widely used and freely available automated segmentation software. Models predicting regional cortical estimates of each hemisphere were produced using age, sex, estimated total intracranial volume (eTIV), scanner manufacturer, magnetic field strength, and interactions as predictors. The explained variance for the left/right cortex was 76%/76% for surface area, 43%/42% for thickness, and 80%/80% for volume. The mean explained variance for all regions was 41% for surface areas, 27% for thicknesses, and 46% for volumes. Age, sex and eTIV predicted most of the explained variance for surface areas and volumes while age was the main predictors for thicknesses. Scanner characteristics generally predicted a limited amount of variance, but this effect was stronger for thicknesses than surface areas and volumes. For new individuals, estimates of their expected surface area, thickness and volume based on their characteristics and the scanner characteristics can be obtained using the derived formulas, as well as Z score effect sizes denoting the extent of the deviation from the normative sample. Models predicting normative values were validated in independent samples of healthy adults, showing satisfactory validation R. Deviations from the normative sample were measured in individuals with mild Alzheimer's disease and schizophrenia and expected patterns of deviations were observed.
目前缺乏能够量化脑部异常的皮质区域解剖测量的适当规范数据。我们基于来自21个独立研究小组提供的23个样本中2713名年龄在18至94岁的健康个体的横断面MRI扫描，制定了区域皮质表面积、厚度和体积的规范。分割使用FreeSurfer进行，这是一款广泛使用且免费的自动分割软件。使用年龄、性别、估计的总颅内体积（eTIV）、扫描仪制造商、磁场强度以及它们之间的相互作用作为预测因子，建立了预测每个半球区域皮质估计值的模型。左/右皮质表面积的解释方差为76%/76%，厚度为43%/42%，体积为80%/80%。所有区域表面积的平均解释方差为41%，厚度为27%，体积为46%。年龄、性别和eTIV预测了表面积和体积的大部分解释方差，而年龄是厚度的主要预测因子。扫描仪特征通常预测的方差量有限，但这种影响对厚度的作用比对表面积和体积更强。对于新个体，可以使用推导公式获得基于其特征和扫描仪特征的预期表面积、厚度和体积估计值，以及表示与规范样本偏差程度的Z分数效应大小。预测规范值的模型在健康成年人的独立样本中得到验证，显示出令人满意的验证R值。在患有轻度阿尔茨海默病和精神分裂症的个体中测量了与规范样本的偏差，并观察到了预期的偏差模式。
