-
Diagnostic value of unenhanced and enhanced CT images in ground glass pulmonary nodules
- GAO Lin, GU Hui, KANG Bing, YU Xinxin, ZHANG Shuai, WANG Ruopeng, WANG Ximing
-
Journal of Shandong University (Health Sciences). 2021, 59(10):
70-76.
doi:10.6040/j.issn.1671-7554.0.2021.0774
-
Abstract
(
2057 )
PDF (3562KB)
(
245
)
Save
-
References |
Related Articles |
Metrics
Objective To explore the predictive value of unenhanced CT scan and contrast-enhanced CT scan in benign, malignant and invasive ground glass pulmonary nodules(GGN). Methods The CT images of 480 patients with 540 GGNs who underwent lung curative resection during Jan. 2018 and Dec. 2020 were retrospectively analyzed, including 57 GGNs in the benign group, 310 in the non-invasive group(AAH+AIS+MIA), and 173 in the invasive group(MIA). The general data(age, gender, smoking history, family history of lung cancer, site), percentage of ground glass component, morphology, boundary, lobulation, burr, vacuolar sign, bronchial abnormality sign, internal vessel sign, pleural traction sign, longest diameter, shortest diameter, unenhanced CT value, CT values on enhancement in arterial phase, CT values on enhancement in venous phase, and degree of enhancement(ΔCTA-N, ΔCTV-N)were analyzed with one-way ANOVA, Kruskal-Wallis H test and Pearson χ2 test. Intra-group correlation coefficient(ICC)was used to evaluate the repeatability of measurement. Logistic regression analysis was performed by taking the nature of GGN(tumor or not)or invasiveness as the dependent variables, relative factors as independent variables. ROC curve analysis and the area under the curve(AUC)were calculated and the diagnostic criteria(including critical value, sensitivity and specificity)were evaluated based on the gold standard of pathological diagnosis. Results There were significant differences in the qualitative and quantitative parameters of nodules among the three groups(P<0.001). Logistic regression analysis showed statistically significant differences in the proportion of ground glass components, internal vessel sign, unenhanced CT values and degree of enhancement ΔCTV-N(P<0.001). ROC curve showed AUC, sensitivity and specificity of ΔCTV-N were 0.874, 0.747, and 0.877, respectively. There were significant differences in the longest diameter, lobulation, boundary and vascular abnormality of the nodules between the invasive and non-invasive groups. ROC curve showed that the longest diameter was an independent predictor(AUC=0.851, sensitivity=0.746, specificity=0.813). Conclusion Unenhanced CT scan combined with enhanced CT scan is of great significance in predicting benign, malignant and invasive GGNs. The enhancement degree of GGN(ΔCTV-N)is very effective in predicting benign and malignant GGNs, and the longest diameter is very effective in predicting invasiveness.
