Firouznia Marjan, Molnar David, Edin Carl, Hjelmgren Ola, Östgren Carl-Johan, Lundberg Peter, Henningsson Markus, Bergström Göran, Carlhäll Carl-Johan
Division of Diagnostics and Specialist Medicine, Department of Health, Medicine and Caring Sciences, Linköping University, 58183 Linköping, Sweden.
Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Radiol Cardiothorac Imaging. 2025 Aug;7(4):e240531. doi: 10.1148/ryct.240531.
Purpose To systematically compare MRI- and CT-based measurements of both the volume and quality of epicardial adipose tissue (EAT). Materials and Methods This prospective study included participants from a subset of the Swedish CArdioPulmonary bioImage Study (SCAPIS) who underwent MRI and CT between November 2017 and July 2018. Dixon fat-water separation MR images were manually segmented, and a threshold-based approach based on a fat signal fraction (FSF) map was used to obtain the EAT volume. Within this EAT volume, the mean FSF was quantified as a measure of fat quality. EAT segmentation from CT images was performed using deep learning techniques, and the EAT volume and its mean attenuation were quantified. Correlation between MRI- and CT-based measurements of EAT volume and quality was assessed using the Pearson correlation coefficient. Results Ninety-two participants (mean age, 59 years ± 5 [SD]; 60 male participants) were included. The intermodality correlation for EAT volume was very strong ( = 0.92, < .001), with systematically larger values for CT versus MRI ( < .001). There was a strong negative correlation between MRI FSF and CT attenuation ( = -0.72, < .001). Repeatability analysis for assessment of MRI EAT volume showed good interreader agreement (intraclass correlation coefficient, 0.86) and excellent intrareader agreement (intraclass correlation coefficient, 0.96). Conclusion Correlation between MRI and CT was very strong for EAT volume and strong for EAT quality. Cardiac, Adipose Tissue (Obesity Studies), Epicardial Fat, Heart, Tissue Characterization, Comparative Studies, Magnetic Resonance Imaging, Computed Tomography, Fat Signal Fraction, Fat Attenuation Published under a CC BY 4.0 license.
目的 系统比较基于MRI和CT测量的心外膜脂肪组织(EAT)的体积和质量。材料与方法 这项前瞻性研究纳入了瑞典心肺生物影像研究(SCAPIS)子集中在2017年11月至2018年7月期间接受MRI和CT检查的参与者。对狄克逊脂肪-水分离MR图像进行手动分割,并使用基于脂肪信号分数(FSF)图的阈值法获取EAT体积。在该EAT体积内,将平均FSF量化为脂肪质量的指标。使用深度学习技术对CT图像进行EAT分割,并对EAT体积及其平均衰减进行量化。采用Pearson相关系数评估基于MRI和CT测量的EAT体积和质量之间的相关性。结果 纳入92名参与者(平均年龄59岁±5[标准差];60名男性参与者)。EAT体积的不同模态间相关性非常强(r = 0.92,P <.001),CT测量值系统性地大于MRI测量值(P <.001)。MRI FSF与CT衰减之间存在很强的负相关性(r = -0.72,P <.001)。评估MRI EAT体积的重复性分析显示,读者间一致性良好(组内相关系数,0.86),读者内一致性极佳(组内相关系数,0.96)。结论 MRI和CT在心外膜脂肪组织体积方面相关性非常强,在脂肪质量方面相关性较强。心脏、脂肪组织(肥胖研究)、心外膜脂肪、心脏、组织特征、对比研究、磁共振成像、计算机断层扫描、脂肪信号分数、脂肪衰减 以知识共享署名4.0许可协议发布。