增强CT直方图分析鉴别甲状腺良恶性结节

Contrast-enhanced CT histogram analysis in differentiating benign and malignant thyroid nodules

目的观察基于CT平扫和增强图像直方图特征鉴别诊断甲状腺良恶性结节的价值。方法回顾性分析经手术后病理证实的甲状腺结节患者132例,共140个结节。选取轴位病灶最大层面,采用Mazda软件沿病灶边缘勾画ROI并进行直方图分析,获取9个参数,比较良恶性结节的差异,并以ROC曲线分析差异有显著统计学意义的灰度直方图参数对甲状腺良恶性结节的鉴别诊断效能。结果CT平扫恶性结节均值及第10、50、90百分位数高于良性结节(P均<0.05);增强后恶性结节均值及第1、10、50、90百分位数高于良性结节(P均<0.05),良性结节方差高于恶性结节(P<0.05)。两者偏度、峰度、第99百分位数在CT平扫和增强中差异均无显著统计学意义(P均>0.05)。CT平扫和增强直方图参数中,第10百分位数AUC最高,为0.68,鉴别甲状腺良恶性结节的敏感度和特异度分别为74.32%和62.12%。结论CT直方图分析可作为鉴别甲状腺良恶性结节的重要辅助手段。

Objective To explore the value of histogram features based on plain and enhanced CT for differential diagnosis of benign and malignant thyroid nodules.Methods A total of 132 patients with 140 thyroid nodules confirmed by postoperative pathology were retrospectively analyzed.The level with the largest axial focus was selected,and then Mazda software was used to sketch ROI along the edge of focus and perform histogram analysis to obtain 9 parameters.The parameters were compared between benign and malignant nodules,and then statistically significant gray-scale histogram parameters were used to analyze their value of differentiating benign and malignant thyroid nodules.Results On plain CT,the mean value,the 10th,50th and 90th percentiles of malignant nodules were higher than those of benign ones(all P<0.05),while on enhanced CT,the mean value,variance,and the first,10th,50th and 90th percentiles of malignant nodules were all higher than those of benign ones(all P<0.05).The average value of malignant nodules was higher than that of benign ones by the first,10th,50th and 90th percentage points,and the variance of benign group was higher than that of malignant group(all P>0.05).Among the parameters of CT plain and enhanced histogram,the 10th percentile AUC was the highest of 0.68,and the sensitivity of identifying benign and malignant thyroid nodules was 74.32%,and specificity was 62.12%.Conclusion CT histogram analysis can be used as an important auxiliary means to identify benign and malignant thyroid nodules.