Lee Scott J, Liu Jiamin, Yao Jianhua, Kanarek Andrew, Summers Ronald M, Pickhardt Perry J
1 Department of Radiology, University of Wisconsin School of Medicine and Public Health , Madison, WI , USA.
2 Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, National Institutes of Health Clinical Center , Bethesda, MD , USA.
Br J Radiol. 2018 Sep;91(1089):20170968. doi: 10.1259/bjr.20170968. Epub 2018 Mar 28.
To investigate a fully automated CT-based adiposity tool, applying it to a longitudinal adult screening cohort.
A validated automated adipose tissue segmentation algorithm was applied to non-contrast abdominal CT scans in 8852 consecutive asymptomatic adults (mean age, 57.1 years; 3926 M/4926 F) undergoing colonography screening. The tool was also applied to follow-up CT scans in a subset of 1584 individuals undergoing longitudinal surveillance (mean interval, 5.6 years). Visceral and subcutaneous adipose tissue (VAT and SAT) volumes were segmented at levels T12-L5. Primary adipose results are reported herein for the L1 level as mean cross-sectional area. CT-based adipose measurements at initial CT and change over time were analyzed.
Mean VAT values were significantly higher in males (205.8 ± 107.5 vs 108.1 ± 82.4 cm; p < 0.001), whereas mean SAT values were significantly higher in females (171.3 ± 111.3 vs 124.3 ± 79.7 cm; p < 0.001). The VAT/SAT ratio at L1 was three times higher in males (1.8 ± 0.7 vs 0.6 ± 0.4; p < 0.001). At longitudinal follow-up CT, mean VAT/SAT ratio change was positive in males, but negative in females. Among the 502 individuals where the VAT/SAT ratio increased at follow-up CT, 333 (66.3%) were males. Half of patients (49.6%; 786/1585) showed an interval increase in both VAT and SAT at follow-up CT.
This robust, fully automated CT adiposity tool allows for both individualized and population-based assessment of visceral and subcutaneous abdominal fat. Such data could be automatically derived at abdominal CT regardless of the study indication, potentially allowing for opportunistic cardiovascular risk stratification. Advances in knowledge: The CT-based adiposity tool described herein allows for fully automated measurement of visceral and subcutaneous abdominal fat, which can be used for assessing cardiovascular risk, metabolic syndrome, and for change over time.
研究一种基于CT的全自动肥胖测量工具，并将其应用于一个成年纵向筛查队列。
将一种经过验证的自动脂肪组织分割算法应用于8852名连续接受结肠造影筛查的无症状成年人（平均年龄57.1岁；男性3926名/女性4926名）的非增强腹部CT扫描。该工具还应用于1584名接受纵向监测的个体（平均间隔时间5.6年）的随访CT扫描。在T12-L5水平分割内脏和皮下脂肪组织（VAT和SAT）体积。本文报告L1水平的主要脂肪测量结果为平均横截面积。分析了初始CT时基于CT的脂肪测量值及其随时间的变化。
男性的平均VAT值显著高于女性（205.8±107.5 vs 108.1±82.4 cm；p<0.001），而女性的平均SAT值显著高于男性（171.3±111.3 vs
124.3±79.7 cm；p<0.001）。L1水平的VAT/SAT比值男性是女性的三倍（1.8±0.7 vs 0.6±0.4；p<0.001）。在纵向随访CT中，男性的平均VAT/SAT比值变化为正，而女性为负。在随访CT中VAT/SAT比值升高的502名个体中，333名（66.3%）为男性。一半的患者（49.6%；786/1585）在随访CT时VAT和SAT均有间隔期增加。
这种强大的、基于CT的全自动肥胖测量工具能够对内脏和皮下腹部脂肪进行个体化和基于人群的评估。无论研究目的如何，此类数据均可在腹部CT时自动获取，这可能有助于进行机会性心血管风险分层。知识进展：本文所述的基于CT的肥胖测量工具能够对内脏和皮下腹部脂肪进行全自动测量，可用于评估心血管风险、代谢综合征以及随时间的变化情况。
