Department of Orthopedic Surgery, Busan Medical Center, Busan, Republic of Korea.
School of Biomedical Convergence Engineering, Pusan National University, Yangsan, Republic of Korea.
BMC Musculoskelet Disord. 2023 Feb 4;24(1):94. doi: 10.1186/s12891-023-06159-6.
Bone mineral content (BMC) values in certain bones and changes in BMC over time are key features for diagnosing osteoporosis. This study examined those features using morphometric texture analysis in chest computational tomography (CT) by comparing a dual-energy X-ray absorptiometry (DXA)-based BMC. An accessible approach for screening osteoporosis was suggested by accessing BMC using only Hounsfield units (HU).
The study included a total of 510 cases (255 patients) acquired between May 6, 2012, and June 30, 2020, at a single institution. Two cases were associated with two chest CT scans from one patient with a scan interval of over two years, and each scan was followed soon after by a DXA scan. Axial cuts of the first lumbar vertebra in CT and DXA-based L1 BMC values were corrected for each case. The maximum trabecular area was selected from the L1 spine body, and 45 texture features were extracted from the region using gray-level co-occurrence matrices. A regression model was employed to estimate the absolute BMC value in each case using 45 features. Also, an additional regression model was used to estimate the change in BMC between two scans for each patient using 90 features from the corresponding cases.
The correlation coefficient (CC) and mean absolute error (MAE) between estimates and DXA references were obtained for the evaluation of regressors. In the case of the BMC estimation, CC and MAE were 0.754 and 1.641 (g). In the case of the estimation of change in BMC, CC and MAE were 0.680 and 0.528 (g).
The modality using morphometric texture analysis with CT HUs can indirectly help screening osteoporosis because it provides estimates of BMC and BMC change that show moderate positive correlations with DXA measures.
某些骨骼的骨矿物质含量 (BMC) 值和随时间的 BMC 变化是诊断骨质疏松症的关键特征。本研究通过比较基于双能 X 射线吸收法 (DXA) 的 BMC,使用胸部计算机断层扫描 (CT) 的形态纹理分析来检查这些特征。通过仅使用亨氏单位 (HU) 访问 BMC,提出了一种用于骨质疏松症筛查的便捷方法。
该研究共纳入了 2012 年 5 月 6 日至 2020 年 6 月 30 日期间在一家医疗机构采集的 510 例(255 例患者)。有两例是一名患者的两次胸部 CT 扫描,两次扫描的时间间隔超过两年,且每次扫描后不久都进行了 DXA 扫描。对 CT 中的第一腰椎的轴向切片和基于 DXA 的 L1 BMC 值进行了校正。从 L1 脊柱体中选择最大的小梁区域,并使用灰度共生矩阵从该区域中提取 45 个纹理特征。使用 45 个特征的回归模型估计每个病例的绝对 BMC 值。还使用来自相应病例的 90 个特征的回归模型,估计每个患者两次扫描之间的 BMC 变化。
评估回归量时,获得了估计值与 DXA 参考值之间的相关系数 (CC) 和平均绝对误差 (MAE)。在 BMC 估计的情况下,CC 和 MAE 分别为 0.754 和 1.641(g)。在 BMC 变化的估计中,CC 和 MAE 分别为 0.680 和 0.528(g)。
使用 CT HU 进行形态纹理分析的方法可以间接帮助筛选骨质疏松症,因为它提供的 BMC 和 BMC 变化估计值与 DXA 测量值呈中度正相关。