Jones Terence A, Wayte Sarah C, Reddy Narendra L, Adesanya Oludolapo, Dimitriadis George K, Barber Thomas M, Hutchinson Charles E
University of Warwick, Clinical Sciences Research Laboratories, Clifford Bridge Road, Coventry CV2 2DX, UK; Department of Radiology, University Hospitals Coventry and Warwickshire, Clifford Bridge Road, Coventry CV2 2DX, UK.
Medical Physics, University Hospitals Coventry and Warwickshire, Clifford Bridge Road, Coventry CV2 2DX, UK.
Magn Reson Imaging. 2018 Sep;51:61-68. doi: 10.1016/j.mri.2018.04.013. Epub 2018 Apr 26.
Lower fat fraction (FF) in brown adipose tissue (BAT) than white adipose tissue (WAT) has been exploited using Dixon-based Magnetic Resonance Imaging (MRI) to differentiate these tissues in rodents, human infants and adults. We aimed to determine whether an optimal FF threshold could be determined to differentiate between BAT and WAT in adult humans in vivo.
Sixteen volunteers were recruited (9 females, 7 males; 44.2 ± 19.2 years) based on BAT uptake on F-FDG PET/CT. Axial 3-echo TSE IDEAL sequences were acquired (TR(ms)/TE(ms)/matrix/NEX/FoV(cm) = 440/10.7-11.1/512 × 512/3/30-40), of the neck/upper thorax on a 3T HDxt MRI scanner (GE Medical Systems, Milwaukee, USA), and FF maps generated from the resulting water- and fat-only images. BAT depots were delineated on PET/CT based on standardized uptake values (SUV) >2.5 g/ml, and transposed onto FF maps. WAT depots were defined manually within subcutaneous fat. Receiver operating characteristic (ROC) analyses were performed, and optimal thresholds for differentiating BAT and WAT determined for each subject using Youden's J statistic.
There was large variation in optimal FF thresholds to differentiate BAT and WAT between subjects (0.68-0.85), with great variation in sensitivity (0.26-0.84) and specificity (0.62-0.99). FF was excellent or good at separating BAT and WAT in four cases (area under the curve [AUC] 0.84-0.92), but poor in 10 (AUC 0.25-0.68).
Although this technique was effective at differentiating BAT and WAT in some cases, no universal cut-off could be identified to reliably differentiate BAT and WAT in vivo in adult humans on the basis of FF.
利用基于狄克逊法的磁共振成像(MRI)技术,已发现棕色脂肪组织(BAT)中的脂肪分数(FF)低于白色脂肪组织(WAT),以此来区分啮齿动物、人类婴儿和成人中的这些组织。我们旨在确定是否可以确定一个最佳的FF阈值,以在成年人体内区分BAT和WAT。
根据F-FDG PET/CT上的BAT摄取情况招募了16名志愿者(9名女性,7名男性;44.2±19.2岁)。在一台3T HDxt MRI扫描仪(美国通用医疗系统公司,密尔沃基)上采集颈部/上胸部的轴向3回波TSE IDEAL序列(TR(ms)/TE(ms)/矩阵/NEX/FoV(cm)=440/10.7 - 11.1/512×512/3/30 - 40),并从所得的仅含水和脂肪的图像生成FF图。基于标准化摄取值(SUV)>2.5 g/ml在PET/CT上勾勒出BAT储存部位,并将其转绘到FF图上。在皮下脂肪内手动定义WAT储存部位。进行了受试者操作特征(ROC)分析,并使用尤登指数J统计量为每个受试者确定区分BAT和WAT的最佳阈值。
受试者之间区分BAT和WAT的最佳FF阈值差异很大(0.68 - 0.85),敏感性(0.26 - 0.84)和特异性(0.62 - 0.99)也有很大差异。在4例中,FF在区分BAT和WAT方面表现优异或良好(曲线下面积[AUC]为0.84 - 0.92),但在10例中表现较差(AUC为0.25 - 0.68)。
尽管该技术在某些情况下能有效区分BAT和WAT,但无法确定一个通用的临界值,以便基于FF在成年人体内可靠地区分BAT和WAT。