PDF(Pubmed)
Abstract：
Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject\'s sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure.
摘要：
临床研究强调严格和可重复的研究设计的实施，依赖于组间匹配或控制生物变异的来源，如受试者的性别和年龄。然而,在临床神经影像学设计中，对身体尺寸（即身高和体重）的校正大多缺乏。这项研究调查了体型参数与脊髓（SC）和脑磁共振成像（MRI）指标的关系的重要性。数据来自267名健康成年人的国际化人群（年龄30.1±6.6岁，125名女性)。我们发现身高与脑灰质（GM）体积强烈或中度相关，皮质GM体积，小脑总体积,脑干体积,和宫颈SC白质的横截面积（CSA）（CSA-WM；0.44≤r≤0.62）。相比之下,年龄与皮质GM体积弱相关，前中央GM体积，皮质厚度（-0.21≥r≥-0.27）。体重与SCWM中的磁化强度转移比弱相关，背柱,和外侧皮质脊髓束（-0.20≥r≥-0.23）。体重与SCWM（r=-0.20）和背柱（-0.21）中扩散张量成像（DTI）得出的平均扩散率进一步弱相关，但只有男性。CSA-WM与脑容量强烈或中度相关（0.39≤r≤0.64），SC背柱和SC外侧皮质脊髓束的中央前回厚度和基于DTI的分数各向异性较弱（-0.22≥r≥-0.25）。性别和年龄的线性混合解释了脑容量和SCCSA数据差异的26±10％。当将身高添加到混合物模型中时，解释的方差增加了33±11％。年龄本身只能解释这种差异的2±2%。总之,体型是一个重要的生物学变量。随着性别和年龄，因此,在设计检查SC和脑结构的临床神经影像学研究时,应将体型作为强制性变量.
