Yang Yanhui, Wen Lu, Zhang Yi, Sun Yan, Niu Yue, Fu Yi, Lu Qiang, Luo Tao, Huang Zhijie, Hou Jing, Yu Xiaoping
Department of Diagnostic Radiology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University/Hunan Cancer Hospital, Changsha, China.
Department of Diagnostic Radiology, Graduate Collaborative Training Base of Hunan Cancer Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Quant Imaging Med Surg. 2025 Jun 6;15(6):4960-4971. doi: 10.21037/qims-24-1671. Epub 2025 May 27.
Anemia negatively affects an individual's overall prognosis and quality of life, and thus represents a significant health burden. Dual-layer computed tomography (DLCT) detector imaging enables substance differentiation. This study aimed to compare the performance of DLCT parameters for different blood vessels in detecting anemia.
DLCT parameter values [i.e., the computed tomography (CT) value, effective atomic number, and electron density] were retrospectively derived from the aortic arch, pulmonary artery, and portal vein of 240 patients. Differences in DLCT parameters between the anemia and normal groups were analyzed. Pearson correlation analysis and logistic regression models were employed to examine the relationships between the DLCT parameters and hemoglobin concentration. The diagnostic performance of DLCT parameters for anemia among different blood vessels was evaluated by receiver operating characteristic (ROC) analysis.
The anemia group (n=101) had significantly lower hemoglobin concentration than the normal group (n=139) (107.96±13.95 138.40±12.64 g/L, P<0.001), as well as significantly lower CT and electron density values for the three vessels (all P<0.05). The CT value and effective atomic number of the portal vein were significantly lower than those of the aortic arch and pulmonary artery (all P<0.05). The correlation of the CT value of the portal vein to hemoglobin concentration was significantly lower than that of the aortic arch (r=0.435 0.583, P=0.029) and slightly lower than that of the pulmonary artery (r=0.435 0.527, P=0.192). Regarding the correlation between electron density and hemoglobin concentration, there were no significant differences among the three blood vessels (all P>0.05). When using the CT value to detect anemia, the aortic arch had an area under the curve (AUC) value of 0.79, which was significantly higher than that of the portal vein (AUC =0.68, P=0.008) and slightly higher than that of the pulmonary artery (AUC =0.73, P=0.126). In relation to electron density, the aortic arch had an AUC value of 0.81, which was slightly higher than that of both the portal vein (AUC =0.77, P=0.239) and the pulmonary artery (AUC =0.75, P=0.095). Among the six CT predictors, the CT value of the portal vein had the lowest AUC value (AUC =0.68), and the value was significantly lower than that of the aortic arch (P=0.008), that of the electron density of the aortic arch (P=0.002), and that of electron density of the portal vein (P=0.007). The multivariable logistic regression showed that the CT value of the aortic arch, electron density of the pulmonary artery, and electron density of the portal vein were independent predictors of anemia. The logistic regression model that integrated the above three CT indicators showed the best performance (AUC =0.85) in predicting anemia, outperforming any single CT predictor of an individual vessel (all P<0.05).
DLCT may assist in the detection of anemia. The DLCT parameters of the aortic arch demonstrated higher performance than those of the pulmonary artery and portal vein. Additionally, integrating different DLCT parameters (i.e., the CT value and electron density) of multiple vessels may improve diagnostic performance.
贫血对个体的总体预后和生活质量产生负面影响，因此是一项重大的健康负担。双层计算机断层扫描（DLCT）探测器成像能够实现物质区分。本研究旨在比较不同血管的DLCT参数在检测贫血方面的性能。
回顾性获取240例患者主动脉弓、肺动脉和门静脉的DLCT参数值[即计算机断层扫描（CT）值、有效原子序数和电子密度]。分析贫血组与正常组之间DLCT参数的差异。采用Pearson相关性分析和逻辑回归模型来检验DLCT参数与血红蛋白浓度之间的关系。通过受试者操作特征（ROC）分析评估不同血管中DLCT参数对贫血的诊断性能。
贫血组（n = 101）的血红蛋白浓度显著低于正常组（n = 139）（107.96±13.95对138.40±12.64 g/L，P < 0.001），并且三根血管的CT值和电子密度值也显著更低（均P < 0.05）。门静脉的CT值和有效原子序数显著低于主动脉弓和肺动脉（均P < 0.05）。门静脉CT值与血红蛋白浓度的相关性显著低于主动脉弓（r = 0.435对0.583，P = 0.029），略低于肺动脉（r = 0.435对0.527，P = 0.192）。关于电子密度与血红蛋白浓度之间的相关性，三根血管之间无显著差异（均P > 0.05）。当使用CT值检测贫血时，主动脉弓的曲线下面积（AUC）值为0.79，显著高于门静脉（AUC = 0.68，P = 0.008），略高于肺动脉（AUC = 0.73，P = 0.126）。就电子密度而言，主动脉弓的AUC值为0.81，略高于门静脉（AUC = 0.77，P = 0.239）和肺动脉（AUC = 0.75，P = 0.095）。在六个CT预测指标中，门静脉的CT值AUC值最低（AUC = 0.68），该值显著低于主动脉弓（P = 0.008）、主动脉弓的电子密度值（P = 0.002）和门静脉的电子密度值（P = 0.007）。多变量逻辑回归显示，主动脉弓的CT值、肺动脉的电子密度和门静脉的电子密度是贫血的独立预测指标。整合上述三个CT指标的逻辑回归模型在预测贫血方面表现最佳（AUC = 0.85），优于任何单个血管的CT预测指标（均P < 0.05）。
DLCT可能有助于贫血的检测。主动脉弓的DLCT参数表现高于肺动脉和门静脉。此外，整合多根血管的不同DLCT参数（即CT值和电子密度）可能会提高诊断性能。
