Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Building 10, Room 1C370, 10 Center Drive, Bethesda, MA 20892, USA.
Tomography. 2023 May 20;9(3):1041-1051. doi: 10.3390/tomography9030085.
Reliable and objective measures of abdominal fat distribution across imaging modalities are essential for various clinical and research scenarios, such as assessing cardiometabolic disease risk due to obesity. We aimed to compare quantitative measures of subcutaneous (SAT) and visceral (VAT) adipose tissues in the abdomen between computed tomography (CT) and Dixon-based magnetic resonance (MR) images using a unified computer-assisted software framework.
This study included 21 subjects who underwent abdominal CT and Dixon MR imaging on the same day. For each subject, two matched axial CT and fat-only MR images at the L2-L3 and the L4-L5 intervertebral levels were selected for fat quantification. For each image, an outer and an inner abdominal wall regions as well as SAT and VAT pixel masks were automatically generated by our software. The computer-generated results were then inspected and corrected by an expert reader.
There were excellent agreements for both abdominal wall segmentation and adipose tissue quantification between matched CT and MR images. Pearson coefficients were 0.97 for both outer and inner region segmentation, 0.99 for SAT, and 0.97 for VAT quantification. Bland-Altman analyses indicated minimum biases in all comparisons.
We showed that abdominal adipose tissue can be reliably quantified from both CT and Dixon MR images using a unified computer-assisted software framework. This flexible framework has a simple-to-use workflow to measure SAT and VAT from both modalities to support various clinical research applications.
可靠和客观的腹部脂肪分布的测量方法对于各种临床和研究情况都至关重要，例如评估肥胖引起的心血管代谢疾病风险。我们旨在使用统一的计算机辅助软件框架，比较腹部 CT 和基于 Dixon 的磁共振（MR）图像在定量测量皮下（SAT）和内脏（VAT）脂肪组织方面的差异。
本研究纳入了 21 名同一天接受腹部 CT 和 Dixon MR 成像的受试者。对于每位受试者，在 L2-L3 和 L4-L5 椎间盘水平选择了两个匹配的轴向 CT 和仅含脂肪的 MR 图像进行脂肪定量。对于每个图像，我们的软件自动生成了一个外部和一个内部腹壁区域以及 SAT 和 VAT 像素掩模。计算机生成的结果随后由一位专家读者进行检查和修正。
在匹配的 CT 和 MR 图像之间，腹壁分割和脂肪组织定量都有极好的一致性。皮尔逊系数对于外腹壁和内腹壁分割分别为 0.97，对于 SAT 为 0.99，对于 VAT 定量为 0.97。Bland-Altman 分析表明所有比较的偏差最小。
我们表明，使用统一的计算机辅助软件框架，可以从 CT 和 Dixon MR 图像可靠地定量腹部脂肪组织。这种灵活的框架具有简单易用的工作流程，可以从两种模态测量 SAT 和 VAT，以支持各种临床研究应用。
