Department of Orthopedic Surgery, Orthopedic Surgeon, Busan Medical Center, Busan, Republic of Korea.
BMC Musculoskelet Disord. 2022 Dec 26;23(1):1130. doi: 10.1186/s12891-022-06076-0.
As the radiomics technique using texture features in CT is adopted for accessing DXA-equivalent bone mineral density (BMD), this study aims to compare BMD by DXA and predicted BMD to investigate the impact of obesity and central obesity in general patients.
A total of 710 cases (621 patients) obtained from May 6, 2012, to June 30, 2021, were used in the study. We focused both their abdomen & pelvis CT's first lumbar vertebrae axial cuts to predict estimated BMD and bone mineral content (BMC). In each patient's CT, we extracted the largest trabecular region of the L1 vertebral body as a region of interest (ROI) using the gray-level co-occurrence matrices (GLCM) technique, and linear regression was applied to predict the indices. Cases were divided by central obesity/overall obesity and normal group by body mass index (BMI), waist circumference (WC), or index of central obesity (ICO) standard.
The coefficients were all above 0.73, respectively. P-values from ICO were over 0.05 when the measures were Hip BMD and Hip BMC. In contrast, those from ICO were 0.0131 and 0.0351 when the measures were L1 BMD and L1 BMC, respectively, which show a difference between the two groups.
The CT HU texture analysis method was an effective and economical method for measuring estimated BMD and BMC and evaluating the impact of obesity. We found that central obesity especially exerted an effect on the disturbance of the clinical BMD measurements since groups were significantly different under the ICO standard.
由于 CT 纹理特征的放射组学技术可用于评估与 DXA 相当的骨密度(BMD),本研究旨在比较 DXA 和预测的 BMD,以探讨肥胖和中心性肥胖对一般患者的影响。
本研究共纳入 2012 年 5 月 6 日至 2021 年 6 月 30 日期间的 710 例(621 例患者)。我们关注了他们腹部和骨盆 CT 的第一腰椎轴向切片,以预测估计的 BMD 和骨矿物质含量(BMC)。在每位患者的 CT 中,我们使用灰度共生矩阵(GLCM)技术提取 L1 椎体最大的小梁区域作为感兴趣区域(ROI),并应用线性回归预测指标。根据 BMI、腰围(WC)或中心性肥胖指数(ICO)标准将病例分为中心性肥胖/总体肥胖组和正常组。
各项系数分别在 0.73 以上。当指标为髋部 BMD 和髋部 BMC 时,ICO 的 P 值均大于 0.05。相比之下,当指标为 L1 BMD 和 L1 BMC 时,ICO 的 P 值分别为 0.0131 和 0.0351,表明两组之间存在差异。
CT HU 纹理分析方法是一种有效且经济的测量估计 BMD 和 BMC 以及评估肥胖影响的方法。我们发现,中心性肥胖尤其会对临床 BMD 测量的干扰产生影响,因为在 ICO 标准下,各组之间存在显著差异。