Qiu Lisa, Dillman Jonathan R, Sun Qin, Fei Lin, Abu-El-Haija Maisam, Trout Andrew T
Department of Radiology, MLC 5031, Cincinnati Children's Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA.
Department of Radiology, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
Pediatr Radiol. 2022 Dec;52(13):2568-2574. doi: 10.1007/s00247-022-05405-8. Epub 2022 May 30.
Pancreas volume might be a quantitative metric of pancreas health and function in children.
To establish normative pancreas volumes and determine factors associated with pancreas volume.
We conducted a retrospective study of 140 healthy children (balanced from 0 to 18 years, stratified by age and gender) who underwent contrast-enhanced CT of the abdomen. Pancreas volume was manually segmented by a single reviewer using 3D Slicer and corrected by a pediatric radiologist. We used Bland-Altman difference analysis to quantify differences in initial and refined segmented pancreas volume, and the Mann-Whitney U test to compare continuous variables. We used Pearson correlation for univariate associations. To determine predictors, we used multivariable regression. Finally, we generated quantile regression equations to determine pancreas volume based on age or body surface area (BSA).
Pancreas volume for the study sample ranged from 2 mL to 99 mL. Age (r=0.90, P<0.0001), body mass index (BMI) (r=0.66, P<0.0001), BSA (r=0.94, P<0.0001), height (r=0.91, P<0.0001) and weight (r=0.90, P<0.0001) were all positively correlated with pancreas volume on univariate analysis. On multivariable analysis, BSA (+36 mL/m, P<0.0001) and female gender (-2.8 mL, P=0.062) were significant independent predictors of pancreas volume. The mean difference between initial and refined segmentation was 0.80 mL (95% limits of agreement: -7.9 mL to 9.5 mL).
We report pancreas volumes for healthy children. We found that age, BMI, BSA, height and weight were each significantly, positively correlated with pancreas volume in univariate analyses, while BSA and female gender were significant independent predictive factors on multivariable analysis.
胰腺体积可能是儿童胰腺健康和功能的一项定量指标。
建立正常胰腺体积并确定与胰腺体积相关的因素。
我们对140名接受腹部增强CT的健康儿童(年龄从0到18岁均衡分布,按年龄和性别分层)进行了一项回顾性研究。由一名审阅者使用3D Slicer软件手动分割胰腺体积,并由一名儿科放射科医生进行校正。我们使用Bland-Altman差异分析来量化初始分割和精确分割的胰腺体积差异,并使用Mann-Whitney U检验来比较连续变量。我们使用Pearson相关性进行单变量关联分析。为了确定预测因素,我们使用多变量回归分析。最后,我们生成了分位数回归方程,以根据年龄或体表面积(BSA)确定胰腺体积。
研究样本的胰腺体积范围为2毫升至99毫升。单变量分析显示,年龄(r = 0.90,P < 0.0001)、体重指数(BMI)(r = 0.66,P < 0.0001)、体表面积(BSA)(r = 0.94,P < 0.0001)、身高(r = 0.91,P < 0.0001)和体重(r = 0.90,P < 0.0001)均与胰腺体积呈正相关。多变量分析显示,体表面积(每平方米增加36毫升,P < 0.0001)和女性性别(减少2.8毫升,P = 0.062)是胰腺体积的显著独立预测因素。初始分割和精确分割之间的平均差异为0.80毫升(95%一致性界限:-7.9毫升至9.5毫升)。
我们报告了健康儿童的胰腺体积。我们发现,在单变量分析中,年龄、BMI、BSA、身高和体重均与胰腺体积显著正相关,而在多变量分析中,BSA和女性性别是显著的独立预测因素。