已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Liver Fat Content Measurement with Quantitative CT Validated against MRI Proton Density Fat Fraction: A Prospective Study of 400 Healthy Volunteers

医学 接收机工作特性 核医学 四分位间距 前瞻性队列研究 协议限制 曲线下面积 放射科 平淡——奥特曼情节 磁共振成像 病理 内科学
作者
Zhe Guo,Glen M. Blake,Kai Li,Liang Wei,Wei Zhang,Yong Zhang,Li Xu,Ling Wang,J.K. Brown,Xiaoguang Cheng,Perry J. Pickhardt
出处
期刊:Radiology [Radiological Society of North America]
卷期号:294 (1): 89-97 被引量:117
标识
DOI:10.1148/radiol.2019190467
摘要

Background Although chemical shift–encoded (CSE) MRI proton density fat fraction (PDFF) is the current noninvasive reference standard for liver fat quantification, the liver is more frequently imaged with CT. Purpose To validate quantitative CT measurements of liver fat against the MRI PDFF reference standard. Materials and Methods In this prospective study, 400 healthy participants were recruited between August 2015 and July 2016. Each participant underwent same-day abdominal unenhanced quantitative CT with a calibration phantom and CSE 3.0-T MRI. CSE MRI liver fat measurements were used to calibrate an equation to adjust CT fat measurements and put them on the PDFF measurement scale. CT and PDFF liver fat measurements were plotted as histograms, medians, and interquartile ranges compared; scatterplots and Bland-Altman plots obtained; and Pearson correlation coefficients calculated. Receiver operating characteristic curves including areas under the curve were evaluated for mild (PDFF, 5%) and moderate (PDFF, 14%) steatosis thresholds for both raw and adjusted CT measurements. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated. Results Four hundred volunteers (mean age, 52.6 years ± 15.2; 227 women) were evaluated. MRI PDFF measurements of liver fat ranged between 0% and 28%, with 41.5% (166 of 400) of participants with PDFF greater than 5%. Both raw and adjusted quantitative CT values correlated well with MRI PDFF (r2 = 0.79; P < .001). Bland-Altman analysis of adjusted CT values showed no slope or bias. Both raw and adjusted CT had areas under the receiver operating characteristic curve of 0.87 and 0.99, respectively, to identify participants with mild (PDFF, >5%) and moderate (PDFF, >14%) steatosis, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for unadjusted CT was 75.9% (126 of 166), 85.0% (199 of 234), 78.3% (126 of 161), and 83.3% (199 of 239), respectively, for PDFF greater than 5%; and 84.8% (28 of 33), 98.4% (361 of 367), 82.4% (28 of 34), and 98.6% (361 of 366), respectively, for PDFF greater than 14%. Results for adjusted CT were mostly identical. Conclusion Quantitative CT liver fat exhibited good correlation and accuracy with proton density fat fraction measured with chemical shift–encoded MRI. © RSNA, 2019 Online supplemental material is available for this article.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
抠抠小手完成签到,获得积分10
2秒前
Pami发布了新的文献求助10
3秒前
散人发布了新的文献求助10
3秒前
Essence应助Pami采纳,获得10
4秒前
冷静的石头完成签到,获得积分10
4秒前
leeSongha完成签到 ,获得积分0
4秒前
6秒前
7秒前
陈小鱼完成签到 ,获得积分10
7秒前
9秒前
9秒前
669209352完成签到 ,获得积分10
9秒前
仓鼠香香完成签到,获得积分10
11秒前
12秒前
12秒前
唐磊完成签到,获得积分10
12秒前
辣辣啦发布了新的文献求助10
13秒前
Chuu♡发布了新的文献求助10
14秒前
木子木公完成签到,获得积分10
15秒前
赏金猎人John_Wang完成签到,获得积分10
15秒前
17秒前
传奇3应助负责的问雁采纳,获得10
17秒前
Owen应助老实的水蜜桃采纳,获得10
17秒前
17秒前
顾矜应助y9gyn_37采纳,获得10
18秒前
like完成签到,获得积分10
19秒前
小小牛马应助科研通管家采纳,获得10
19秒前
19秒前
19秒前
领导范儿应助科研通管家采纳,获得10
20秒前
bkagyin应助科研通管家采纳,获得10
20秒前
张欢馨应助科研通管家采纳,获得10
20秒前
Anonymous应助科研通管家采纳,获得20
20秒前
21秒前
活力鑫磊发布了新的文献求助10
23秒前
魁123完成签到 ,获得积分10
23秒前
科研通AI6.4应助rachel采纳,获得10
24秒前
24秒前
Chuu♡完成签到,获得积分10
24秒前
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7633095
求助须知:如何正确求助?哪些是违规求助? 9207493
关于积分的说明 19747443
捐赠科研通 7202089
什么是DOI,文献DOI怎么找? 3274916
关于科研通互助平台的介绍 2436834
邀请新用户注册赠送积分活动 2271744