Introduction

Pulmonary ground-glass opacity (GGO) observed on computed tomography (CT) is widely regarded as a diagnostic feature of lung adenocarcinoma; however, a significant radiological predictive sign remains controversial. In this retrospective study, we conducted a comprehensive analysis of 206 patients with GGO to establish a correlation analysis model between CT images and diagnosis of GGO nodules.

Methods

Histopathologic specimens were obtained from 206 patients (130 women, 76 men; age range 24–77). The clinical data, pathologic findings, and thin-section CT features of solid, pure GGO (pGGO), and mixed GGO (mGGO) nodules were compared using rigorous statistical methods, such as t-test, Fisher’s exact test, or univariate logistic regression analysis.

Results

Significant differences were observed among the 3 groups in terms of patient demographics, including gender (P = 0.016), smoking history (P = 0.002), and nodule size (P = 0.002). Morphologic CT characteristics, such as the presence of spiculated sign, lobulated sign, vascular sign, bubble-lucency sign, or pleural retraction, exhibited significant differences among the solid nodule, pGGO, and mGGO groups. However, no significant differences were observed in terms of air-bronchogram sign. Notably, the incidence of malignancy was significantly higher in pGGO nodules (76.52%) than in solid (48.48%) and mGGO (73.86%) nodules. Patients with mGGO had up to 2.988 times higher hazard of malignant lesions than those with solid nodules [P = 0.036, hazard ratio (HR) = 2.988]. Similarly, the hazard of malignant lesions was 2.941 times higher in patients with pGGO than in those with solid nodules (P = 0.007, HR = 2.941).

Conclusion

Clinical, pathological, and thin-section CT features of solid, pGGO and mGGO nodules were found to be significantly different. Based on our comprehensive analysis, patients presenting with a mGGO or pGGO on CT scans were more likely to be diagnosed with lung cancer.

Recently, with the worldwide use of low-dose computed tomography (CT) in early lung cancer screening, more and more early lung adenocarcinoma or preinvasive lesions in the form of ground-glass opacity (GGO) are being identified.1,2  GGO is defined as hazy increased opacity of the lung with preservation of bronchial and vascular margin.3,4  According to the guidelines proposed by the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) system, early-stage lung adenocarcinomas can be classified into 3 histological subtypes namely, preinvasive lesions [i.e., adenocarcinoma in situ (AIS) and atypical adenomatous hyperplasia (AAH)], minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC), which could be observed as a persistent GGO nodule at CT.5,6  However, besides malignant lesions, some types of benign lesions also can be observed as similar hazy opacity manifestation, such as focal interstitial fibrosis, inflammation, and hemorrhage.7,8  Radiographic nondeterminacy makes GGO a nonspecific finding, and due to the malignant potential and heterogeneous characteristics, GGO nodule diagnosis is a challenging task for radiologists.

Many studies have reported that preoperative CT scan findings are related to pathological features and postoperative prognosis.9–12  By using quantitative imaging features and machine-learning classifiers, these studies built different models, which aims to determine the pathologic character of GGO nodules effectively in CT scan preoperatively.13  Some types of image features in CT scans are supposed to be strongly suggestive of a malignant early lung tumor, for example, spiculated sign, lobulated sign, vascular sign, bubble-lucency sign, air-bronchogram sign, and pleural retraction.14  However, whether these findings can be applied to classify between benign nodules and malignant GGO nodules is still controversial.15–17  Thus, it is necessary to develop a correlation analysis model between CT images and histopathological subtypes of GGO nodules.

Here, the purpose of our study was to retrospectively analyze the clinical, pathological, and high-resolution CT features of persistent solitary or multiple GGO nodules from 206 postoperative patients with pulmonary GGO and to provide some insight into the preoperative GGO diagnosis strategy.

Patients

A total of 235 patients with a solitary or multiple GGOs of maximum diameter <2 cm on chest CT including high-resolution CT (HRCT) at the Department of Thoracic Surgery of The First Affiliated Hospital of Xiamen University between January 2017 and December 2019 were enrolled. All pathology files and clinical information and radiology information system records from patients with pathology findings for at least 1 GGO nodule were collected, including solid nodules, mixed GGO (mGGO), and pure GGO (pGGO). Most patients were identified by low-dose CT screening for lung cancer. However, before our analysis, we excluded 29 patients still evaluated by follow-up or lack of information on radiologic-pathologic correlation and excluded another 126 patients detected with lung nodules by outpatient CT who declined to undergo inpatient surgery treatment in the knowledge of their condition and selected periodical monitoring by chest CT screening, which was thus performed on 206 patients (66 solid nodules, 52 pGGOs, and 88 mGGOs; 159 solitary GGOs and 47 multiple GGOs).

The demographic and clinical data of patients with GGO nodules were recorded (i.e., age and sex, smoking history, family history, and number of primary lung nodules).

This study was approved by the institutional review board of the hospitals involved; the requirement for patients’ informed consent was waived in this retrospective study.

CT Imaging Analysis

Chest CT images were obtained on a 256-slice Philips Brilliance iCT Elite FHD machine (Philips, Jiangsu, China) or Somatom Definition Flash dual-source CT scanner (Siemens, Shanghai, China). Images were obtained using a window level of 600 Hounsfield units (HU), a window width of 1500 HU (lung window), and a level of 30 HU and a width of 400 HU (mediastinal window). Conventional CT images were obtained from the thoracic inlet to the lung base using a 5-mm section thickness and a 5-mm section spacing, and HRCT images were obtained at a section thickness of 1 mm. Two pulmonologists and 2 radiologists identified GGO sizes and margins and decided on the presence of a solid portion. GGO lesions were classified as solid nodule, pGGO, or mGGO based on the presence of a solid component within a nodule on an HRCT image at a lung window level.

All CT images were reviewed by 2 chest radiologists with 8 and 7 years of experience of chest CT interpretation, respectively. Both were unaware of clinical information. Decisions on CT findings were reached by consensus. One radiologist measured lesion sizes and solid portions within GGO nodules. The following thin-section CT findings were recorded for each lesion: (1) lesion size, (2) percentage of GGO component, (3) shape (round or oval, polygonal, irregular), (4) margin (smooth, lobulated, spiculated), (5) border (well-defined, ill-defined), and (6) presence of air-bronchogram, bubble-lucency, or pleural retraction. Lesion size was defined as the longest lesion dimension. Percentage of GGO component was defined as the greatest diameter of the solid portion divided by the greatest diameter of the lesion including the GGO area.

In addition, 36 of all 206 samples preoperatively detected other concomitant separate lung primaries by HRCT. Among multiple pulmonary nodules with an individual patient, only the most predominant lung lesion (largest nodule diameter in pGGO or most solid component proportion in mGGO) on CT imaging or the most malignant lesion confirmed by pathologic diagnosis was included. For each individual patient, only a single lesion was included in the analysis.

Histopathology and Pathologic Diagnosis

All of the patients recruited obtained surgical resection at the Department of Thoracic Surgery of The First Affiliated Hospital of Xiamen University after primary diagnosis and preoperative CT scan. Pathologic specimens were obtained by lobectomy in 144, segmentectomy in 18, and wedge resection in 44 nodules. Fresh tissues were immediately snap-frozen and stored at −80°C or fixed and embedded in paraffin. Samples were formalin-fixed, paraffin-embedded, and then diagnosed and confirmed by at least 2 lung cancer pathologists.

All 206 patients included in our study were postoperatively diagnosed and had not undergone any pathological biopsy preoperatively.

Statistical Analysis

Comparisons between the imaging and histopathological findings of the preinvasive lung adenocarcinomas were analyzed using SPSS 20.0 software (SPSS Inc., Chicago, IL). The χ2 and Fisher tests were used for comparison analyses. All possible factors including clinical and radiologic characteristics were used with the logistic regression method to make a differential diagnosis among solid, pGGO, and mGGO nodules. Two-tailed P values of less than 0.01 were considered to indicate statistical significance.

Demographic Findings of Patients With GGO

Of the 206 patients with pulmonary GGO lesions, 66 had solid nodules, 52 had pGGOs, and 88 mGGOs. Regarding patient demographics, gender (P = 0.016), smoking history (P = 0.002), and nodule size (P = 0.002) were significantly different among the 3 groups. According to the results, the patients with pGGOs showed the highest female-to-male ratio (75.0%) and lowest smoking ratio (3.8%). Mean pulmonary GGO nodule diameter showed 12.76 ± 6.87 mm in the solid nodule group, 8.24 ± 3.02 mm in the pGGO group, and 11.45 ± 6.91 mm in the mGGO group. However, because of the heterogeneity of variance, it is unavailable to use 1-way analysis of variance test. Additionally, the significant difference in pulmonary GGO mean diameter was revealed again under univariate logistic regression analysis.

Besides, no significant differences were observed in terms of age stratification or the presence of lung cancer family history (P = 0.051, P = 0.323, respectively), or in mode of detection for multiple and solitary GGO nodules (P = 0.739) (Table 1).

Table 1

Clinicopathologic characteristics of the patients with ground-glass opacity

Clinicopathologic characteristics of the patients with ground-glass opacity
Clinicopathologic characteristics of the patients with ground-glass opacity

Comparisons of the Solid Nodule, pGGO, and mGGO Groups in Terms of HRCT Features

The results showed that a significant difference in morphologic CT characteristics (e.g., spiculated sign, lobulated sign, vascular sign, bubble-lucency sign, or pleural retraction) was found among the solid nodule, pGGO, and mGGO groups (P = 0.001, 0.007, 0.010, 0.005, 0.001, respectively, Table 2). However, no significant differences were observed in terms of air-bronchogram sign (P = 0.097, Table 2). Based on our data, solid nodules of 66 patients were more frequently observed to have a spiculated margin, lobulated shape, or pleural retraction at thin-section CT scan (positive rate = 74.24%, 75.76%, 56.06, respectively), whereas the mGGO nodules more frequently showed a micrangium vascular sign or bubble-lucency sign in the CT manifestation (positive rate= 94.31%, 40.91%, respectively). Compared with the other 2 groups, pGGO nodules showed few specific features at thin-section CT scan, presence of a smooth margin, intact constitute or a nummular shape were more frequent for pGGO nodules. The lowest positive rate of spiculated sign (44.23%), lobulated sign (51.92%), air-bronchogram sign (9.62%), and pleural retraction (20.00%) was detected in the pGGO nodules group.

Table 2

Comparisons of the solid nodule, pGGO, and mGGO groups in terms of HRCT features

Comparisons of the solid nodule, pGGO, and mGGO groups in terms of HRCT features
Comparisons of the solid nodule, pGGO, and mGGO groups in terms of HRCT features

Pathologic Findings of Patients With GGO

Pathologic diagnoses of solid, pGGO, and mGGO nodules are summarized in Table 3. After postoperative pathologic diagnosis, AAH or other benign lesions (e.g., inflammation, calcification, or tuberculosis) were regarded as the benign group, whereas AIS, MIA, IAC, or other early-stage lung cancer were included in the malignant group. Of the 206 pulmonary nodules, 137 (66.50%) were diagnosed as lung cancer. From the results, a significant difference in the nodule histologic character among solid, pGGO, or mGGO groups was detected (P = 0.001, Table 3). The percentage of malignant nodules diagnosed in each group is 48.48% (solid), 76.52% (pGGO), and 73.86% (mGGO). The highest malignant rate was observed in the pGGO group, whereas the solid nodules come out as the most benign radiologic implication.

Table 3

Pathologic findings of patients with GGO

Pathologic findings of patients with GGO
Pathologic findings of patients with GGO

Univariate Logistic Regression Analysis of Patient Demographics and Radiologic Features of Patients With GGO

The univariate logistic regression analysis proceeded to reveal the hazard ratio (HR) of the demographics and radiologic features of 206 included pathologic diagnosed patients; the results are shown in Table 4. Based on our analysis, patients who were found with a mGGO or pGGO at CT scan were more likely to be diagnosed with lung cancer. The hazard of a malignant lesion was as high as 2.988-fold higher for patients with mGGO compared with those with solid nodules (P = 0.036; HR = 2.988; Table 4). Similarly, the hazard of a malignant lesion was as high as 2.941-fold higher for patients with pGGO compared with those with solid nodules (P = 0.007; HR = 2.941; Table 4). The results showed that the higher nodule diameters should be regarded as another significant risk factor for patients with GGOs. Along with every 1-mm diameter of pulmonary nodules increasing, the hazard of a malignant diagnostic would be increased 9.2% (P = 0.014; HR = 1.092; Table 4). However, the vascular sign of GGO at CT scan was more likely to be regarded as a benign sign. Compared with the pulmonary nodules without a vascular sign, a patient with a vascular sign GGO had 0.287-fold lower HR to be diagnosed as a malignant lesion. In addition, there was no significant difference in the age, gender, smoking, family history, presence of solitary or multiple nodules, and other radiologic implications (e.g., spiculated sign, lobulated sign, air-bronchogram sign, bubble-lucency sign, or pleural retraction) (P > 0.05) (Table 4).

Table 4

Univariate logistic regression analysis of patient demographics and radiologic features of patients with GGO

Univariate logistic regression analysis of patient demographics and radiologic features of patients with GGO
Univariate logistic regression analysis of patient demographics and radiologic features of patients with GGO

Recently, the use of chest CT for lung cancer screening and early-stage adenocarcinoma detection has increased, with a subsequent increase in the detection of pulmonary GGO.1,2,18  Several studies have shown that persistent GGO confers a high risk of malignancy, and created considerable interest in the relation between the CT feature of GGO and lung cancer tentative diagnostic.19,20  For small or faint lung lesions such as one showing GGOs on thin-section CT scan, it is not rare for physicians to speculate histological diagnoses before surgery.21  It also makes a difference on a patient’s decision to receive surgery. Thus, it is necessary to treat such lesions by nonsurgical modalities to accurately speculate their histological characteristics. Here, we attempted to elucidate the association of demographic findings, CT features of patients with GGO, and its diagnostic.

Based on our data, female patients predominated (63.11%) in this study, which may have been associated with a higher lung cancer screening rate compared with men, because GGO cases were almost asymptomatic and were detected by routine screening by low-dose chest CT. However, the results showed that female sex and nonsmoker status were significantly more frequently associated with pGGO nodules. Several studies have reported that gender and smoking history make no difference among pGGO and mGGO groups.22–24  Another study reported by Kim et al14  reveals that female sex, nonsmoker status, and multiple primary lung cancers were significantly more frequently associated with multiple GGO nodules, whereas they did not make a distinction between nodule manifestation on CTs. The difference among conclusions may be due to the various patient cases analyzed. In the present study, we provide partial evidence between demographic findings and presence of pulmonary GGO, an enlarged range of cases would be further analyzed.

Another interest when we undertook this study was to investigate the nodule size of GGOs and to identify whether the GGO size could predict benignity or malignancy. As the results show in Table 1, we first observed that pulmonary GGO sizes among solid nodules, pGGOs, and mGGOs were significantly different. Solid nodule groups were found to have the highest mean pulmonary diameter (12.76 ± 6.87 mm) compared with others. Furthermore, from our univariate logistic regression analysis results, we had determined that higher nodule diameter was a significant risk factor for the hazard of a malignant GGO lesion. In addition, with every 1-mm diameter of pulmonary nodules increasing, the hazard of a malignant diagnostic would be increased 9.2% (P = 0.014; HR = 1.092; Table 4). However, in present relevant studies, the value of the size of GGO for the diagnosis of lung cancer has been controversial, and no standard has been confirmed to date.25  Naidich et al26  suggested that a detected pGGO smaller than 5 mm in diameter was more likely to be diagnosed as benign, which was similar to the aforementioned results. In other studies, the size of GGO lesions proved to be a significant predictive factor.27,28  Indeed, we were not able to identify whether the nodule size we found on thin-section CT should be a significantly independent predictive radiologic factor without survival analysis, but we did reveal that the size of GGO lesions should be considered as a key risk factor for preoperative screening of patients.

Several conflicting reports have been issued regarding the predilections of malignant pulmonary lesions for mGGOs and pGGOs.15–17  However, whether the classification of GGOs can be applied to identify between benign nodules and malignant GGO nodules is still unknown. Thus, in the present study, we developed a univariate logistic regression analysis to reveal the HR of the radiologic features of 206 patients with GGOs. Our results have determined that patients found with an mGGO or pGGO at CT scan were more likely to be diagnosed with lung cancer compared with patients with solid pulmonary nodules. As the control group, solid nodules had the lowest positive rate for the incidence of lung cancer based on our cases. In addition, the hazard of a malignant lesion was as high as 2.988-fold and 2.941-fold higher for patients with mGGOs and pGGOs, respectively. Consistent with our results, Moon et al23  have reported that the pGGO on chest CT should be considered as a significant predictive factor for invasive adenocarcinoma. Another study reported by Oh et al24  demonstrated that the malignancy rate for mGGOs (30.2%) appeared higher than that of pGGOs (19.4%), but the conclusion was without significance unfortunately, which may have been because of the limited cases of pGGOs analyzed. In addition, several studies have provided evidence that a hazy increased opacity that appears as part-solid GGO nodules on thin-section CT was more frequently associated with early-stage invasive lung adenocarcinoma,29,30  and anatomic resection has been recommended over lobectomy for treating these tumors. However, because it is difficult to differentiate the part-solid GGO from mGGO nodules on CTs, we still considered that clinical surgeons should be on the alert for an mGGO nodule appearing on CT scan.

Lobulation and spiculation were regarded as specific signs of malignant tumors traditionally. The lobulation and spiculation margin are generated when a portion of the lesion’s surface formed a wavy or scalloped configuration and the presence of stranding extended from the nodule margin into the lung parenchyma.20,31  In the present study, solid nodules of 66 patients were more frequently observed to have a spiculated margin, lobulated shape, whereas the pGGO nodules showed the lowest positive rate of spiculated sign and lobulated sign. Interestingly, the results also showed that lobulation and speculation were not significantly associated with early-stage lung adenocarcinoma. After consideration, we raise a hypothesis that lobulation and spiculation would occur only when the primary lung tumor enters the invasion stage, whereas these 2 signs were more likely to indicate a benign state on the early-stage nodules. In fact, the focal fibrous connective tissue proliferations of several benign lesions were frequently regarded as tumor lobulation and speculation, such as interstitial fibrosis, inflammation, or even tuberculosis, which are morphologically similar. Another study reported by Xing et al32  revealed that the rate of lobulation and speculation showed no significant difference between AIS and AAH in the mGGO groups, whereas AIS exhibited a higher rate of lobulation and speculation in the pGGO group. The results suggested that more data about analyzing morphological differences between mGGO and pGGO should be considered in the future studies.

It is widely known that angiogenesis, the formation of new blood vessels, is essential for tumor growth and metastasis.33  The immature tumor vessels also display high vascular permeability, thus the tumor tissue is edematous, containing extravasated plasma components. In addition to edema, the expansion of cancer tissue results in increased interstitial pressure, causing impaired tumor blood flow.34  Based on our data, the pGGO nodules showed the highest positive rate of vascular sign, compared with other 2 groups. However, the cases in our logistic regression analysis showed that the vascular sign of GGO at CT scan was significantly associated with benign lesions. In our opinion, the opposite results may have been due to the inevitable boundedness of bidimensional CT scanning. Different from vascular sign, the vessel convergence sign of isolated pulmonary nodules may more precisely detect the angiogenesis of malignancy. Two indispensable conditions, the 3-dimensional reconstruction and enhanced vessel development, were required for the detection of vessel convergence sign, which may increase the cost of CT imaging. However, several studies have reported that vessel convergence signs were identified as independent predictors of malignant pulmonary focal GGO,35–37  which is suggested to be regarded as a significant sign in future examination. Another possible inevitable limitation of our data may be due to the recognition of the vascular sign. Different transparency and vague margin of pGGO, mGGO, and solid nodules greatly affects the detection and discrimination of vascular signs, which may result in bias of our statistics. Future studies with more tridimensional radiological imaging and with assessment of vessel convergence sign may provide more accurate results.

A recent study reported that patients with invasion lung adenocarcinoma and GGO lesions have a higher incidence of pleural retraction than those with AIS/MIA.38  In the present study, although pleural retraction could be observed in all groups of patients with GGO, the highest incidence of pleural retraction was observed in solid nodules, and the pGGO and mGGO groups showed a relatively low incidence. Even the logistic regression analysis showed no significant association between pleural retraction and malignant lung tumor. The negative results may be due to the limited cases collected in studies; however, our results may suggest that people should pay more attention to an unknown pGGO/mGGO nodule without pleural retraction.

Several limitations of the present study require consideration. First, a retrospective study design was used. Second, the data were collected from a single institution and the number of cases was relatively limited. However, all data in this study are recent, since 2017, and bias should be relatively low because management was performed according to the same protocol. Third, the postoperative follow-up was deficient, therefore we were unable to evaluate patient survival or disease recurrence. Last, our study was restricted to surgical patients. More comprehensive analysis might proceed if pathologic analysis of patients with pGGO who did not undergo surgery was made, which was not practically possible in the present study; we still consider our results to be significant.

In conclusion, our present study demonstrated significantly different radiological signs among 206 patients with solid, pGGO, or mGGO nodules. Based on our data, pGGO nodules have significantly the highest malignant incidence compared with solid and mGGO nodules, whereas the solid nodules exhibited the most benign tendency. Compared with solid nodules, mGGOs and pGGOs had nearly 3-fold higher hazard diagnosed as malignant lesions. In patients with these findings, lobectomy is preferable to limited resection. However, future studies that collect data from larger sample sizes are needed to confirm these findings.

Author contributions: Concept and design: S.F. and S.E.S.; data collection: X.L.Z., H.L., and L.T.L.; drafting of the article: S.F.; critical revision of the article for important intellectual content: S.E.S.; study supervision: X.L.Z. All the authors approved the final article. This work was supported by the Fujian Provincial Nature Science Foundation of China, grant number 2020J0122. The authors declare that they have no potential conflicts of interest. All data that supportthe findings of this study are included in this manuscript and its supplementary information files.

1.
Henschke
 
CI.
Early lung cancer action project: overall design and findings from baseline screening
.
Cancer
2000
;
89
:
2474
2482
.
2.
Sone
 
S,
Takashima
 
S,
Li
 
F,
Yang
 
Z,
Honda
 
T,
Maruyama
 
Y,
et al
Mass screening for lung cancer with mobile spiral computed tomography scanner
.
Lancet
1998
;
351
:
1242
1245
.
3.
Park
 
CM,
Goo
 
JM,
Lee
 
HJ,
Lee
 
CH,
Kim
 
HC,
Chung
 
DH,
et al
CT findings of atypical adenomatous hyperplasia in the lung
.
Korean J Radiol
2006
;
7
:
80
86
.
4.
Travis
 
WD,
Garg
 
K,
Franklin
 
WA,
Wistuba
 
II,
Sabloff
 
B,
Noguchi
 
M,
et al
Evolving concepts in the pathology and computed tomography imaging of lung adenocarcinoma and bronchioloalveolar carcinoma
.
J Clin Oncol
2005
;
23
:
3279
3287
.
5.
Austin
 
JH,
Garg
 
K,
Aberle
 
D,
Yankelevitz
 
D,
Kuriyama
 
K,
Lee
 
HJ,
et al
Radiologic implications of the 2011 classification of adenocarcinoma of the lung
.
Radiology
2013
;
266
:
62
71
.
6.
Travis
 
WD,
Brambilla
 
E,
Noguchi
 
M,
Nicholson
 
AG,
Geisinger
 
KR,
Yatabe
 
Y,
et al
International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary classification of lung adenocarcinoma
.
J Thorac Oncol
2011
;
6
:
244
285
.
7.
Park
 
CM,
Goo
 
JM,
Lee
 
HJ,
Lee
 
CH,
Chun
 
EJ,
Im
 
JG.
Nodular ground-glass opacity at thin-section CT: histologic correlation and evaluation of change at follow-up
.
Radiographics
2007
;
27
:
391
408
.
8.
Suzuki
 
K,
Watanabe
 
S,
Mizusawa
 
J,
Moriya
 
Y,
Yoshino
 
I,
Tsuboi
 
M,
et al
Japan Lung Cancer Surgical Study, predictors of non-neoplastic lesions in lung tumours showing ground-glass opacity on thin-section computed tomography based on a multi-institutional prospective study
.
Interact Cardiovasc Thorac Surg
2015
;
21
:
218
223
.
9.
Avanzo
 
M,
Stancanello
 
J,
El Naqa
 
I.
Beyond imaging: the promise of radiomics
.
Phys Med
2017
;
38
:
122
139
.
10.
Chae
 
HD,
Park
 
CM,
Park
 
SJ,
Lee
 
SM,
Kim
 
KG,
Goo
 
JM.
Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas
.
Radiology
2014
;
273
:
285
293
.
11.
Fan
 
L,
Fang
 
M,
Li
 
Z,
Tu
 
W,
Wang
 
S,
Chen
 
W,
et al
Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule
.
Eur Radiol
2019
;
29
:
889
897
.
12.
Li
 
F,
Sone
 
S,
Abe
 
H,
Macmahon
 
H,
Doi
 
K.
Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings
.
Radiology
2004
;
233
:
793
798
.
13.
Kim
 
H,
Park
 
CM,
Goo
 
JM,
Wildberger
 
JE,
Kauczor
 
HU.
Quantitative computed tomography imaging biomarkers in the diagnosis and management of lung cancer
.
Invest Radiol
2015
;
50
:
571
583
.
14.
Kim
 
TJ,
Goo
 
JM,
Lee
 
KW,
Park
 
CM,
Lee
 
HJ.
Clinical, pathological and thin-section CT features of persistent multiple ground-glass opacity nodules: comparison with solitary ground-glass opacity nodule
.
Lung Cancer
2009
;
64
:
171
178
.
15.
Kitami
 
A,
Kamio
 
Y,
Hayashi
 
S,
Suzuki
 
K,
Uematsu
 
S,
Gen
 
R,
et al
One-dimensional mean computed tomography value evaluation of ground-glass opacity on high-resolution images
.
Gen Thorac Cardiovasc Surg
2012
;
60
:
425
430
.
16.
Li
 
S,
Yu
 
J,
Meng
 
X,
Liu
 
L,
Xu
 
L,
Liu
 
L,
et al
The feasibility of non-contrast enhanced plus contrast-enhanced computed tomography in discriminating invasive pure ground-glass opacity from pre-invasive pure ground-glass opacity
.
J Cardiothorac Surg
2020
;
15
:
162
.
17.
Mirtcheva
 
RM,
Vazquez
 
M,
Yankelevitz
 
DF,
Henschke
 
CI.
Bronchioloalveolar carcinoma and adenocarcinoma with bronchioloalveolar features presenting as ground-glass opacities on CT
.
Clin Imaging
2002
;
26
:
95
100
.
18.
National Lung Screening Trial Research
,
Aberle
 
DR,
Adams
 
AM,
Berg
 
CD,
Black
 
WC,
Clapp
 
JD,
et al
Reduced lung-cancer mortality with low-dose computed tomographic screening
.
N Engl J Med
2011
;
365
:
395
409
.
19.
Henschke
 
CI,
Yankelevitz
 
DF,
Mirtcheva
 
R,
McGuinness
 
G,
McCauley
 
D,
Miettinen
 
OS,
et al
CT screening for lung cancer: frequency and significance
.
Of Part-Solid and Nonsolid Nodules. AJR Am J Roentgenol
2002
;
178
:
1053
1057
.
20.
Kim
 
HY,
Shim
 
YM,
Lee
 
KS,
Han
 
J,
Yi
 
CA,
Kim
 
YK.
Persistent pulmonary nodular ground-glass opacity at thin-section CT: histopathologic comparisons
.
Radiology
2007
;
245
:
267
275
.
21.
Yoshida
 
J,
Nagai
 
K,
Yokose
 
T,
Nishimura
 
M,
Kakinuma
 
R,
Ohmatsu
 
H,
et al
Limited resection trial for pulmonary ground-glass opacity nodules: fifty-case experience
.
J Thorac Cardiovasc Surg
2005
;
129
:
991
996
.
22.
Ichinose
 
J,
Kohno
 
T,
Fujimori
 
S,
Harano
 
T,
Suzuki
 
S,
Fujii
 
T.
Invasiveness and malignant potential of pulmonary lesions presenting as pure ground-glass opacities
.
Ann Thorac Cardiovasc Surg
2014
;
20
:
347
352
.
23.
Moon
 
Y,
Sung
 
W,
Lee
 
KY,
Sim
 
SB,
Park
 
JK.
Pure ground-glass opacity on chest computed tomography: predictive factors for invasive adenocarcinoma
.
J Thorac Dis
2016
;
8
:
1561
1570
.
24.
Oh
 
JY,
Kwon
 
SY,
Yoon
 
HI,
Lee
 
SM,
Yim
 
JJ,
Lee
 
JH,
et al
Clinical significance of a solitary ground-glass opacity (GGO) lesion of the lung detected by chest CT
.
Lung Cancer
2007
;
55
:
67
73
.
25.
Kim
 
KG,
Goo
 
JM,
Kim
 
JH,
Lee
 
HG,
Min
 
BG,
Bae
 
KT,
et al
Computer-aided diagnosis of localized ground-glass opacity in the lung at CT: initial experience
.
Radiology
2005
;
237
:
657
661
.
26.
Naidich
 
DP,
Bankier
 
AA,
MacMahon
 
H,
Schaefer-Prokop
 
CM,
Pistolesi
 
M,
Goo
 
JM,
et al
Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society
.
Radiology
2013
;
266
:
304
317
.
27.
Jin
 
X,
Zhao
 
SH,
Gao
 
J,
Wang
 
DJ,
Wu
 
J,
Wu
 
CC,
et al
CT characteristics and pathological implications of early stage (T1N0M0) lung adenocarcinoma with pure ground-glass opacity
.
Eur Radiol
2015
;
25
:
2532
2540
.
28.
Liu
 
LH,
Liu
 
M,
Wei
 
R,
Jin
 
EH,
Liu
 
YH,
Xu
 
L,
et al
CT findings of persistent pure ground glass opacity: can we predict the invasiveness
?
Asian Pac J Cancer Prev
2015
;
16
:
1925
1928
.
29.
Eguchi
 
T,
Kadota
 
K,
Park
 
BJ,
Travis
 
WD,
Jones
 
DR,
Adusumilli
 
PS.
The new IASLC-ATS-ERS lung adenocarcinoma classification: what the surgeon should know
.
Semin Thorac Cardiovasc Surg
2014
;
26
:
210
222
.
30.
Takahashi
 
M,
Shigematsu
 
Y,
Ohta
 
M,
Tokumasu
 
H,
Matsukura
 
T,
Hirai
 
T.
Tumor invasiveness as defined by the newly proposed IASLC/ATS/ERS classification has prognostic significance for pathologic stage IA lung adenocarcinoma and can be predicted by radiologic parameters
.
J Thorac Cardiovasc Surg
2014
;
147
:
54
59
.
31.
Lim
 
HJ,
Ahn
 
S,
Lee
 
KS,
Han
 
J,
Shim
 
YM,
Woo
 
S,
et al
Persistent pure ground-glass opacity lung nodules >/= 10 mm in diameter at CT scan: histopathologic comparisons and prognostic implications
.
Chest
2013
;
144
:
1291
1299
.
32.
Xing
 
Y,
Li
 
Z,
Jiang
 
S,
Xiang
 
W,
Sun
 
X.
Analysis of pre-invasive lung adenocarcinoma lesions on thin-section computerized tomography
.
Clin Respir J
2015
;
9
:
289
296
.
33.
Birau
 
A,
Ceausu
 
RA,
Cimpean
 
AM,
Gaje
 
P,
Raica
 
M,
Olariu
 
T.
Assessment of angiogenesis reveals blood vessel heterogeneity in lung carcinoma
.
Oncol Lett
2012
;
4
:
1183
1186
.
34.
Carmeliet
 
P,
Jain
 
RK.
Angiogenesis in cancer and other diseases
.
Nature
2000
;
407
:
249
257
.
35.
Jiang
 
L,
Situ
 
D,
Lin
 
Y,
Su
 
X,
Zheng
 
Y,
Zhang
 
Y,
et al
Clinical model to estimate the pretest probability of malignancy in patients with pulmonary focal ground-glass opacity
.
Thorac Cancer
2013
;
4
:
380
384
.
36.
Ma
 
J,
Yang
 
YL,
Wang
 
Y,
Zhang
 
XW,
Gu
 
XS,
Wang
 
ZC.
Relationship between computed tomography morphology and prognosis of patients with stage I non-small cell lung cancer
.
Onco Targets Ther
2017
;
10
:
2249
2256
.
37.
Yu
 
L,
Zhang
 
H,
Wang
 
X.
The value of “blood vessel convergency” sign in the diagnosis of small peripheral lung cancer
.
Zhonghua Zhong Liu Za Zhi
1999
;
21
:
453
454
.
38.
Cohen
 
JG,
Reymond
 
E,
Lederlin
 
M,
Medici
 
M,
Lantuejoul
 
S,
Laurent
 
F,
et al
Differentiating pre- and minimally invasive from invasive adenocarcinoma using CT-features in persistent pulmonary part-solid nodules in Caucasian patients
.
Eur J Radiol
2015
;
84
:
738
744
.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Noncommercial License which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is noncommercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0