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3T 磁共振全身脂肪-水成像与双能 X 射线吸收法在肥胖女性中体脂测量的比较。

Comparison of gross body fat-water magnetic resonance imaging at 3 Tesla to dual-energy X-ray absorptiometry in obese women.

机构信息

Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA.

出版信息

Obesity (Silver Spring). 2013 Apr;21(4):765-74. doi: 10.1002/oby.20287.

Abstract

OBJECTIVE

Improved understanding of how depot-specific adipose tissue mass predisposes to obesity-related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three-dimensional (3D) contiguous "fat-water" MR imaging (FWMRI) covering the majority of a whole-body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type, and distribution of adipose and lean soft tissue would show great promise in body composition methodology.

DESIGN AND METHODS

Precision of adipose and lean soft tissue measurements in body and trunk regions were assessed for 3T FWMRI and compared to dual-energy X-ray absorptiometry (DXA). Anthropometric, FWMRI, and DXA measurements were obtained in 12 women with BMI 30-39.9 kg/m(2) .

RESULTS

Test-retest results found coefficients of variation (CV) for FWMRI that were all under 3%: gross body adipose tissue (GBAT) 0.80%, total trunk adipose tissue (TTAT) 2.08%, visceral adipose tissue (VAT) 2.62%, subcutaneous adipose tissue (SAT) 2.11%, gross body lean soft tissue (GBLST) 0.60%, and total trunk lean soft tissue (TTLST) 2.43%. Concordance correlation coefficients between FWMRI and DXA were 0.978, 0.802, 0.629, and 0.400 for GBAT, TTAT, GBLST, and TTLST, respectively.

CONCLUSIONS

While Bland-Altman plots demonstrated agreement between FWMRI and DXA for GBAT and TTAT, a negative bias existed for GBLST and TTLST measurements. Differences may be explained by the FWMRI FOV length and potential for DXA to overestimate lean soft tissue. While more development is necessary, the described 3T FWMRI method combined with fully-automated segmentation is fast (<30-min total scan and post-processing time), noninvasive, repeatable, and cost-effective.

摘要

目的

深入了解脂肪组织在特定部位的堆积如何导致肥胖相关合并症,这可能为肥胖的发病机制和治疗提供新的见解,以及体重减轻带来的代谢益处。我们假设,在 3 特斯拉(3T)下获得的覆盖全身视野(FOV)大部分的三维(3D)连续“脂肪-水”磁共振成像(FWMRI),结合自动分割和量化脂肪和瘦软组织的数量、类型和分布,将在人体成分方法学中具有广阔的前景。

设计与方法

对 3T FWMRI 的体部和躯干部位脂肪和瘦软组织测量的精密度进行了评估,并与双能 X 射线吸收法(DXA)进行了比较。在 BMI 为 30-39.9 kg/m²的 12 名女性中,获得了人体测量学、FWMRI 和 DXA 测量值。

结果

测试-重测结果发现 FWMRI 的变异系数(CV)均低于 3%:总体身体脂肪组织(GBAT)0.80%、总躯干脂肪组织(TTAT)2.08%、内脏脂肪组织(VAT)2.62%、皮下脂肪组织(SAT)2.11%、总体身体瘦软组织(GBLST)0.60%和总躯干瘦软组织(TTLST)2.43%。FWMRI 与 DXA 之间的一致性相关系数分别为 0.978、0.802、0.629 和 0.400,用于 GBAT、TTAT、GBLST 和 TTLST。

结论

虽然 Bland-Altman 图显示 FWMRI 与 DXA 对 GBAT 和 TTAT 的一致性,但 GBLST 和 TTLST 测量存在负偏倚。差异可能是由于 FWMRI FOV 长度和 DXA 高估瘦软组织的潜在因素所致。尽管还需要进一步发展,但所描述的 3T FWMRI 方法结合全自动分割是快速的(<30 分钟总扫描和后处理时间)、非侵入性的、可重复的和具有成本效益的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f778/3500572/b6c9223c374e/nihms383731f1.jpg

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