Hu Dacheng, Zhen Tao, Ruan Mei, Wu Linyu
Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine.
Department of Radiology, the First Affiliated Hospital of Zhejiang Chinese Medical University.
Medicine (Baltimore). 2020 Nov 6;99(45):e23114. doi: 10.1097/MD.0000000000023114.
To investigate the value of percentile base on computed tomography (CT) histogram analysis for distinguishing invasive adenocarcinoma (IA) from adenocarcinoma in situ (AIS) or micro invasive adenocarcinoma (MIA) appearing as pure ground-glass nodules.A total of 42 cases of pure ground-glass nodules that were surgically resected and pathologically confirmed as lung adenocarcinoma between January 2015 and May 2019 were included. Cases were divided into IA and AIS/MIA in the study. The percentile on CT histogram was compared between the 2 groups. Univariate and multivariate logistic regression were used to determine which factors demonstrated a significant effect on invasiveness. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) was used to evaluate the predictive ability of individual characteristics and the combined model.The 4 histogram parameters (25th percentile, 55th percentile, 95th percentile, 97.5th percentile) and the combined model all showed a certain diagnostic value. The combined model demonstrated the best diagnostic performance. The AUC values were as follows: 25th percentile = 0.693, 55th percentile = 0.706, 95th percentile = 0.713, 97.5th percentile = 0.710, and combined model = 0.837 (all P < .05).The percentile of histogram parameters help to improve the ability to radiologically determine the invasiveness of lung adenocarcinoma appearing as pure ground-glass nodules.
探讨基于计算机断层扫描(CT)直方图分析的百分位数在鉴别表现为纯磨玻璃结节的浸润性腺癌(IA)与原位腺癌(AIS)或微浸润腺癌(MIA)中的价值。纳入2015年1月至2019年5月期间手术切除并经病理证实为肺腺癌的42例纯磨玻璃结节病例。研究中病例分为IA组和AIS/MIA组。比较两组CT直方图上的百分位数。采用单因素和多因素逻辑回归确定哪些因素对浸润性有显著影响。采用受试者操作特征(ROC)曲线和曲线下面积(AUC)评估个体特征和联合模型的预测能力。4个直方图参数(第25百分位数、第55百分位数、第95百分位数、第97.5百分位数)及联合模型均显示出一定诊断价值。联合模型诊断性能最佳。AUC值如下:第25百分位数=0.693,第55百分位数=0.706,第95百分位数=0.713,第97.5百分位数=0.710,联合模型=0.837(均P<0.05)。直方图参数的百分位数有助于提高对表现为纯磨玻璃结节的肺腺癌进行放射学判断浸润性的能力。