Correlation between HRCT features of pulmonary pure ground-glass nodules and the new pathologic classification of lung adenocarcinoma
10.12025/j.issn.1008-6358.2016.20160411
- VernacularTitle:高分辨率CT肺纯磨玻璃结节影像特征与肺腺癌病理新分类的相关性
- Author:
Jin-Dong GUO
1
;
Xi-Wen SUN
Author Information
1. 同济大学医学院
- Keywords:
lung neoplasm;
adenocarcinoma;
pathology;
tomography;
ground-glass nodule
- From:
Chinese Journal of Clinical Medicine
2016;23(4):449-453
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the correlation between high resolution CT (HRCT ) features of pulmonary pure ground‐glass nodules (PGGN ) including early invasive pulmonary adenocarcinomas and preinvasive lesions and the new pathologic classification of lung adenocarcinoma ,and to evaluate the predictive values of HRCT in the pathologic classification of lung adenocarcinoma with PGGN .Methods:The data of 123 patients hospitalized from January 2014 to June 2014 in a single central and diagnosed by HRCT as early peripheral lung adenocarcinoma or atypical adenoma with PGGN were retrospectively analyzed .The correlation between HRCT morphological characteristics ,size ,and density of PGGN and the 2015‐edition new classification of lung adenocarcinoma were analyzed ,the best predictors were screened out ,and a model was constructed and verified .Results:All of nine image morphological features were significantly correlated with the new pathological classification (Pearson correlation test , P< 0 .05 ) . Among them , eight morphological features including lobulation , spiculation , air/bronchial inflation ,pleural indentation ,edge regularity ,shape regularity ,density uniformity and vessel convergence had a positive linear correlation with the new pathological classification (P<0 .01) .Futhermore ,four continuous variables describing the size and density of the lesion including maximum cross‐sectional area ,lesion length in cranial‐caudal direction ,average actual density of PGGN and the relative average density were significantly correlated with the new pathological classification (P<0 .05) .Multinomial logistic regression analysis was adopted to screen out the seven best predictors :spiculation ,lesion lgenth in cranial‐caudal direction ,average actual density ,clear demarcation of tumor ,gender ,age ,and vessel convergence . After the model was constructed ,and the likelihood ratio test showed that the overall matching rate was 70 .7% ,while the matching rate of atypical adenomatous hyperplasia (AAH ) was up to 92 .9% .Conclusions:The HRCT characteristics of PGGN were significantly correlated with the new 2015‐edition WHO pathologic classification of lung adenocarcinoma .The new pathological classification of PGGN can be predicted by HRCT ,and the best predictors were spiculation ,lesion length in cranial‐caudal direction ,average actual density ,clear demarcation of tumor ,gender ,age ,and vessel convergence .
