Figure 1.
DFS curves for AIS, MIA and invasive adenocarcinoma (IA) groups.
Table 1.
Characteristics of lung adenocarcinoma with little solid component on CT in reference to invasion status (n = 191).
Figure 2.
CT image, histogram distribution of CT attenuation value, and photomicrograph (hematoxylin-eosin stain; original magnification, X 40).
(A) is a case of AIS, (B) is a case of MIA, (C) and (D) are cases of invasive adenocarcinoma. First three cases show pure GGNs without a solid component, whereas (D) shows GGN with 2 mm-solid component on CT image. As for histogram distribution, the vertical axis in each histogram shows the number of pixels in the segmented tumor. The red and blue lines indicate the values for 75th and 97.5th percentile. The horizontal axis shows the CT attenuation values. As compared with histograms of (A) AIS and (B) MIA, those of (B) MIA and (C) invasive adenocarcinoma show increased values in the 75th and 97.5th percentile. Tumor density was also increased, whereas tumor mass showed no difference. Histogram of MIA demonstrates a flat peak with high entropy as compared with that of AIS. Histogram graph of (D) shows two peaks, which is different from one peak of (A),(B), and (C). In a photomicrograph of (A) AIS, this circumscribed nonmucinous tumor grows purely with a lepidic pattern. No foci of invasion or scarring are seen. A photomicrograph of (B) MIA consists primarily of lepidic growth with a small (4.8 mm) upper area of acinar invasion. A photomicrograph of (C) invasive acinar adenocarcinoma consists of round to oval-shaped malignant glands invading a fibrous stroma 7 mm in length and a smaller area of lepidic growth only at the tumor periphery. Another photomicrograph of invasive acinar adenocarcinoma (D) shows centrally located bronchus, which is the main cause of solid component of CT image.
Table 2.
Multivariate analysis for stratification among AIS, MIA and invasive adenocarcinoma.
Table 3.
Correlation of imaging biomarker features with extent of invasion on pathology.
Figure 3.
Receiver operating characteristic (ROC) curve for predicting invasive adenocarcinoma with imaging parameters.
For invasive adenocarcinoma prediction, ROC curve based on the combination of the 75th percentile CT attenuation value and entropy also shows significant diagnostic accuracy (AUC, 0.780).