Pulmonary ground-glass opacity associated with cystic airspace: clinicopathological features and aggressiveness

Introduction

Early-stage lung cancer commonly manifests as ground-glass opacity (GGO) on computed tomography (CT) images (1). GGOs with a diameter less than 5 mm are usually benign lesions or atypical adenomatous hyperplasia (AAH) (2,3). Studies have shown that only 1% of GGOs smaller than 5 mm will progress to minimally invasive adenocarcinoma (MIA) or invasive adenocarcinoma (IA) (4). Therefore, thoracic surgeons rarely perform operations on GGOs smaller than 5 mm. Conversely, GGOs larger than 20 mm, particularly those with solid components, are more likely to be IAs (5), requiring timely intervention. However, GGOs ranging from 5 mm to 20 mm may represent AAH, adenocarcinoma in situ (AIS), MIA, or IA (5). Previous studies have shown that AIS and MIA have nearly 100% 5-year overall survival rates, while IA has a 5-year overall survival rate ranging from 58% to 93%, depending on pathological subtypes (6,7). On one hand, conservative observation is superior to surgery for low-risk lesions due to the postoperative complications and mortality of surgical procedures (8). On the other hand, it is particularly noteworthy that micropapillary and solid predominant adenocarcinomas have only nearly 60% 5-year overall survival rates (6,7). Therefore, there is a significant need to differentiate between low-risk and high-risk lesions. In recent years, many studies have been conducted to explore better interventions for GGOs smaller than 20 mm (9,10), meaning the great significance of investigating the aggressiveness of lung cancers ranging from 5 to 20 mm.

The Fleischner Society first defined cystic airspace as an enlarged unit of peripheral air-containing lung surrounded by a wall of variable thickness in 1996 (11). This definition was later updated in 2008 (12), supplementing that being used in conjunction with consolidation, opacity and nodule to designate the filling of airspace with the product of disease. In the past, lesions with cystic airspaces were generally considered benign. However, with the development of radiology, many lung cancers associated with cystic airspaces (LCCA) have been identified. In 2012, the International Early Lung Cancer Action Program reported that 3.7% of lung cancers presented as LCCA on CT images (13). According to the Nederlands-Leuvens Longkanker Screenings Onderzoek lung cancer screening trial, 22.7% of missed carcinomas were associated with cystic airspaces (14).

Previous studies had revealed that the majority of solitary LCCAs were adenocarcinomas (15-17). Besides, morphological patterns and wall components were reported as two important predictors for determining the pathological invasiveness of LCCAs (18). But few studies provided detail on the malignancy of pulmonary GGO associated with cystic airspace (GGO-A). Therefore, to contribute to better medical decision-making, we conducted a study to investigate the clinicopathological features and aggressiveness of GGO-A. This study aimed to compare the clinicopathological features and aggressiveness of GGO-A with GGO-nA. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0027/rc).

Methods

Patients

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (No. ES-2023-206-01), and all participants provided written informed consent. A retrospective and comparative study was conducted at the First Affiliated Hospital of Guangzhou Medical University to investigate the clinicopathological features and aggressiveness of GGO-A. We reviewed patients who received CT scans at our center from January 1st, 2017 to July 30th, 2021. Data, such as age, sex, family history of cancer, smoking status and history of common chronic lung diseases (emphysema pulmonum, chronic bronchitis, pulmonary tuberculosis, asthma, and bronchiectasis) were extracted from medical records. The study included patients with GGOs highly suspected of being lung cancers based on CT images, with lesion size from 0.5 to 2.0 cm and consolidation-to-tumor ratio (CTR) ≤50%. The exclusion criteria were followed (Figure 1):

• Lesion with diameter <0.5 or >2.0 cm.
• Benign lesion diagnosed by radiologists based on its morphology and modification (disappearance, reduction, and density diminishing of lesions during following up) on CT images.
• Benign lesion diagnosed by pathologists based on surgical pathology.
• Patient who received anti-tumor therapy (except surgery) during follow-up.

Figure 1 Patient flowchart. Among 2,096 GGOs, 818 met inclusion (0.5–2.0 cm, CTR ≤50%) and were divided into GGO‑A (n=266) and GGO‑nA (n=552). CT, computed tomography; CTR, consolidation-to-tumor ratio; GGO, ground-glass opacity; GGO-A, ground-glass opacity associated with cystic airspace; GGO-nA, ground-glass opacity associated without cystic airspace.

Radiological assessment

We extracted initial CT images of enrolled patients in our center. The radiological characteristics of these lesions were recorded, including location, the largest diameter, margin (lobulated, spiculated) (19,20), pleural retraction, vascular penetration, GGO types (pure, mixed) and pulmonary bullae. The CTR was calculated as the maximum diameter of the solid component divided by the maximum diameter of the whole nodule (CTR = solid diameter/total nodule diameter). Measurements were performed on thin-section CT images (1–2.00 mm slice thickness) using both lung window and mediastinal window settings. For GGO-As, the ‘tumor size’ was defined as the maximum diameter of the whole lesion including the GGO component and the cystic wall, while the ‘consolidation size’ was defined as the maximum diameter of the solid component exclusive of the intranodular ground-glass component or cystic space. All CT images were assessed and reviewed by two experienced radiologists in our center.

Based on previous studies about LCCA (16,18,21,22), we classified GGO-As into 4 types according to the cystic airspaces. Type I (thin-walled type) referred to single cystic airspace with a mean wall thickness of <0.2 cm. Type II (thick-walled type) was related to single cystic airspace with an average wall thickness of ≥0.2 cm. Type III (mural-nodule type) indicated single cystic airspace with an endophytic or exophytic mural nodule. Type IV (mixed type) denoted clusters of multiple cystic airspaces inside or around GGO. For better understanding, we showed typical CT images of these 4 types in supplemental material (Figure S1).

Besides, we reviewed follow-up CT scans of enrolled patients up to December 31, 2022. Lesions meeting the following criteria on CT images were considered as grown GGOs: (I) Increasing in lesion size: lesion’s sizes increased more than 0.2 cm (23). (II) Increasing in lesion mass: solid components emerged or increased in GGO, or GGO’s density increased (23,24). (III) Appearances of malignant signs: malignant signs appeared, including pleural retraction, lobulated margin and spiculated margin (19). The follow-up time was defined as the time interval from the date of initial CT scanning showing the GGO to the last CT scanning date of GGO presence. The time from baseline to GGO growth was defined as the time interval from the date of initial CT scanning showing the GGO to the date when GGO growth was first observed.

Based on previous studies (25,26), volume doubling time (VDT) is a prognostic factor, with longer VDTs being associated with better prognosis. Therefore, we calculated VDTs of grown GGOs increasing in lesion size. GGO volume was calculated using the formula “V=π/6*ab²”, where “a” represented the maximum diameter of the GGO and “b” represented the perpendicular dimension of the GGO. VDT was then calculated using the formula “VDT=(t*log2)/log(V_t/V₀)”, where “t” represented the interval between the initial CT scan and the CT scan showing GGO growth, “V₀” represented the GGO volume at the initial CT scan and “V_t” represented GGO volume at the CT scanning when GGO growth was observed.

Surgical and pathological assessment

Based on the guideline of the National Comprehensive Cancer Network, American College of Chest Physicians (27) and European Society for Medical Oncology (28), in comprehensive consideration of patients’ pulmonary function, comorbidity and willingness, clinical thoracic surgeons decided the treatment and surgical method. Surgical indications for GGOs in our study were established in accordance with current clinical guidelines, as follows: (I) a nodule diameter of ≥15–20 mm with persistence on follow-up imaging; (II) an increase in nodule diameter of ≥2 mm during follow-up; (III) a solid component persisting at ≥6 mm after 3–6 months of follow-up; (IV) the emergence of a new solid component during follow-up, or a marked increase in the existing solid component; (V) the presence of malignant morphological features, including spiculation, lobulation, or pleural retraction; (VI) histopathological confirmation of IA or high-risk histological subtypes on preoperative biopsy; and (VII) severe patient anxiety adversely affecting quality of life, in which case surgical intervention may be considered following thorough counseling and shared decision-making. Surgical methods included lobar resection and sublobar resection, with sublobar resection comprising wedge resection and segmentectomy. For peripheral lesions with a CTR ≤0.25, wedge resection or segmentectomy was preferred. For peripheral lesions with 0.25< CTR ≤0.5, segmentectomy was the preferred approach. Lobectomy was reserved for cases with inadequate margins after sublobar resection, confirmed nodal involvement, lesions located too deep to permit adequate sublobar resection, or the presence of multiple suspicious malignant nodules within the same lobe.

The pathological records of lesions, diagnosed independently by two experienced pathologists in our center, were reviewed. All lesions were classified into AIS, MIA and IA (AAH and lesions with mucinous adenocarcinomas were excluded). Pathological subtypes of IAs, including lepidic, acinar, papillary, solid and micropapillary, were recorded, since they were related to aggressiveness and prognosis (7,29). Based on the new grading system for invasive lung adenocarcinoma proposed by the International Association for the Study of Lung Cancer (IASLC) pathology committee, IAs were also classified into three groups (well-differentiated, moderately-differentiated and poorly-differentiated) (30).

Mutation test

Genetic alternations were assessed by targeted next-generation sequencing to cover critical mutations associated with individualized clinical medication in 11 genes (EGFR, KRAS, BRAF, ERBB2, DDR2, MET, PIK3CA, NRAS, ALK, ROS1, RET). deoxyribonucleic acid (DNA) was extracted from formalin-fixed paraffin-embedded samples using the Qiagen DNeasy Tissue Kit (Qiagen, Hilden, Germany) and quantified by using Qubit fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturers’ instructions. The products were then captured and sequenced on the MGISEQ-2000 Sequencer (BGI Genomics Co., Ltd., Shenzhen, China). The data obtained were processed using a customized bioinformatics pipeline (Otype). Somatic alterations, including single-nucleotide variations and insertions or deletions for 9 genes (ALK, EGFR, KRAS, BRAF, ERBB2, DDR2, MET, PIK3CA, NRAS), as well as fusions for 3 genes (ALK, ROS1, RET) (31), were identified.

Statistical analysis

Data including ages and diameters of lesions were summarized as mean ± standard deviation (SD); follow-up time, time from baseline to GGO growth and VDT were presented as median and quartiles or 95% confidence interval. Chi-squared test, Mann-Whitney test, Kaplan-Meier analysis and Logistic regression analysis were used for statistical analysis. The relative effect of Logistic regression analysis was presented as odds ratio (OR). Two-tailed P values of less than 0.05 is considered significant. Data were analyzed using SPSS version 25.0 (SPSS Inc., Chicago, IL, USA).

Results

Clinical characteristics of patients

This study included 818 eligible patients (266 with GGO-As and 552 with GGO-nAs). The clinical characteristics of patients were summarized and analyzed in Table 1.

Compared with the patients with GGO-nAs, there were more males (72.9% vs. 28.3%), more patients with smoking history (33.1% vs. 15.0%), emphysema pulmonum (16.5% vs. 2.0%) and pulmonary bullae (31.2% vs. 9.4%) in patients with GGO-As. However, there were fewer patients with family history of cancer (7.9% vs. 35.0%) and chronic bronchitis (1.9% vs. 5.6%) in the group of GGO-A than in the group of GGO-nA. Logistic regression analysis (Figure 2, Hosmer-Lemeshow test P=0.93) showed positive associations between GGO-A and male (OR =5.588, P<0.001), patients without family history of lung cancer (OR =5.121, P<0.001), patient with emphysema pulmonum (OR =3.228, P=0.003) and patients with pulmonary bullae (OR =2.634, P<0.001), while no significant association was observed between GGO-A and patients with smoking history (OR =0.728, P=0.18) and patients without chronic bronchitis (OR =2.495, P=0.09).

Figure 2 Clinical characteristics, classification and aggressiveness. (A) Clinical characteristic: logistic regression analysis showed positive associations between GGO-A and male, without family history of cancer, with emphysema pulmonum and with pulmonary bullae. (B) Classification of GGO-As. (C) Pathological invasiveness: n_GGO-A=178, n_GGO-nA=89. (D) Micropapillary components in IAs: n_GGO-A=135, n_GGO-nA=35. (E) Recurrence-free survival. (F) Disease-free survival. (G) Frequency of GGO growth: n_GGO-A=76, n_GGO-nA=370. (H) Time from baseline to GGO growth: GGO-As had a shorter median time from baseline to GGO growth than GGO-nAs (24.0 months vs. not reached, P<0.001, n_GGO-A=76, n_GGO-nA=370). (I) Pathological invasiveness of GGO-A subtypes: n_{Type I}=73, n_{Type II}=7, n_{Type III}=12, n_{Type IV}=86, P=0.293. (J) Micropapillary components in IAs in GGO-A subtypes: n_{Type I}=51, n_{Type II}=7, n_{Type III}=10, n_{Type IV}=67, P=0.26. AIS, adenocarcinoma in situ; CI, confidence interval; GGO, ground-glass opacity; GGO-A, ground-glass opacity associated with cystic airspace; GGO-nA, ground-glass opacity associated without cystic airspace; IA, invasive adenocarcinoma; MIA, minimally invasive adenocarcinoma; OR, odds ratio.

Among patients with GGO-As, 76 underwent CT follow-up, and 181 underwent surgical resection (sublobar resection: 47.0%, 85/181; lobar resection: 53.0%, 96/181). Among these, 84 patients received gene testing after surgery.

Radiological characteristics of lesions

As Table 1 showed, there was no difference in the location between GGO-As and GGO-nAs (P=0.26). The mean largest diameter of GGO-As was larger than that of GGO-nAs (1.4±0.4 vs. 0.8±0.3 cm). Notably, all GGO-As had cystic airspaces larger than 5 mm, which may introduce a tumor size bias.

There were more mixed-GGOs (45.1% vs. 25.2%) in the group of GGO-A than in the group of GGO-nA. Besides, more lesions were observed with lobulated margin (19.9% vs. 5.6%), spiculated margin (13.5% vs. 4.0%), pleural retraction (20.3% vs. 6.9%), vascular penetration (25.9% vs. 11.8%) in the group of GGO-As than the group of GGO-nAs. The most common subtypes of GGO-As were type I (thin-walled type, 42.9%) and type IV (mixed type, 46.6%), while type II (thick-walled type, 3.8%) and type III (mural-nodule type, 6.8%) were only observed in a small number of cases (Figure 2).

Pathological features

There were 181 patients with GGO-As and 90 patients with GGO-nAs receiving surgical resection. All specimens were obtained through video-assisted thoracic surgery and confirmed pathologically as lung adenocarcinoma. Based on the pathological diagnosis, a total of 178 patients with GGO-As (three with mucinous adenocarcinoma were excluded) and 89 patients with GGO-nAs (one AAH was excluded) were further investigated (Table 2). According to the TNM 8th Edition, no patient was in the state of T3, T4, M1 and stage IV.

In GGO-As, 1.7% were AIS, 22.5% were MIA, and 75.8% were IAs. However, in GGO-nAs, 10.1% were AIS, 50.6% were MIA, and 39.3% were IAs.

In IAs of GGO-As, there were 95.6% lesions with lepidic subtypes, 85.9% with acinar subtypes, 65.2% with papillary subtypes, and 17.0% with micropapillary subtypes. In comparison, in IAs of GGO-nAs, there were 91.4% lesions with lepidic subtypes, 97.1% with acinar subtypes, 37.1% with papillary subtypes, and 5.7% with micropapillary subtypes. Solid subtypes appeared in no lesions. According to the 2020 IASLC grading system, among IAs in GGO-As, 36.3% of lesions were well-differentiated, 62.2% were moderately-differentiated, and 1.5% were poorly-differentiated. However, the proportion of these histological grades in GGO-nAs was 28.6%, 71.4%, and 0, respectively.

Driver-gene mutation

Among patients who received surgical resection, there were 84 GGO-As and 40 GGO-nAs who received gene testing (Table 1). The most frequent driver-gene mutation was EGFR in both GGO-As and GGO-nAs (60.7% vs. 62.5%, P=0.85). Although there was no significant difference, KRAS mutated more frequently in GGO-As than GGO-nAs (15.5% vs. 2.5%, P=0.07).

Radiological progression during follow-up by CT scanning

Among 446 patients followed up by CT scans (76 with GGO-As and 370 with GGO-nAs), GGO growth appeared in 28.9% and 17.0% lesions in GGO-As and GGO-nAs, respectively (Table 3).

The mean largest diameters of grown lesions were 1.2±0.4 and 0.9±0.4 cm in GGO-As and GGO-nAs, while the mean largest diameters of stabile lesions were 1.4±0.4 and 0.8±0.3 cm in these two groups. Though there was no significant difference in the median follow-up time between grown GGO-As and grown GGO-nAs (26.0 vs. 31.0 months, P=0.27), the median time from baseline to GGO growth of grown GGO-As was shorter than grown GGO-nAs (14.5 vs. 22.0 months, P=0.07).

As Table 3 showed, there was no significant difference in the appearance of growth in CT images between grown GGO-As and GGO-nAs. Additionally, among 70 grown lesions presented as increasing in lesion sizes (21 GGO-As and 49 GGO-nAs), the median VDT of GGO-As was shorter than that of GGO-nAs (485 vs. 667 days, P=0.26).

Figure 3 showed consecutive CT images of 2 patients with grown GGO-As. GGO-A of patient A was a pure-GGO at baseline and then gradually increased in size and mass (density) during 43 months. It’s finally confirmed as IA pathologically. GGO-A of patient B grew during 20 months, accompanied by the appearance of malignant sign (pleural retraction). It’s confirmed as IA pathologically, with 10% micropapillary subtypes.

Figure 3 Consecutive CT images of 2 patients with grown GGO-As. Red circles indicate the location of the lesions. GGO-As of patient A was a pure-GGO at baseline and then gradually increased in size and mass (density) during 43 months. It is finally confirmed as IA pathologically. GGO-A of patient B grew during 20 months, accompanied by the appearance of malignant sign (pleural retraction). It is confirmed as IA pathologically, with 10% micropapillary subtypes. The pathological images are stained with hematoxylin and eosin (HE); for each patient, the upper image is shown at ×10 magnification, and the lower image at ×20 magnification. CT, computed tomography; GGO, ground-glass opacity; GGO-A, ground-glass opacity associated with cystic airspace; GGO-nA, ground-glass opacity associated without cystic airspace; IA, invasive adenocarcinoma.

GGO-A was associated with higher aggressiveness

Analysis of pathological performance and radiological progression showed GGO-As were associated with higher aggressiveness, compared GGO-nAs (Figure 2C-2F).

Among patients in analysis of pathological performance, there were more IAs in GGO-As than GGO-nAs (75.8% vs. 39.3%, P<0.001, Figure 2C). Focusing on the micropapillary subtype, more IAs with micropapillary subtypes were observed in GGO-As than GGO-nAs (17.0% vs. 5.7%, P=0.09, Figure 2D). Although the difference did not reach statistical significance, the GGO-A group had lower 5-year recurrence-free survival (RFS, 98.2% vs. 100%, P=0.13, Figure 2E) and disease-free survival (DFS, 96.4% vs. 98.8%, P=0.08, Figure 2F) rates compared with the GGO-nA group, suggesting a trend toward worse outcomes for GGO-A.

Among patients followed up by CT scans, there was a significant difference in the frequency of GGO growth between GGO-As and GGO-nAs (28.9% vs. 17.0%, P=0.02, Figure 2G). Besides, GGO-As had a shorter median time from baseline to GGO growth than GGO-nAs (24.0 months vs. not reached, log-rank P<0.001, Figure 2H).

Furthermore, analysis of pathological aggressiveness for the four subtypes of GGO-As showed no significant difference in the proportion of IAs (P=0.29, Figure 2I) and micropapillary components in IAs (P=0.26, Figure 2J).

Further analysis for GGO types and smoking status

To investigate the potential influence of GGO type for GGO-As’ higher aggressiveness, we classified lesions into pure-GGOs and mixed-GGOs, and then analyzed the aggressiveness of GGO-A and GGO-nA in pathological performance and radiological progression (Table S1).

In pure-GGOs, compared to GGO-nAs, GGO-As had a higher proportion of IAs (61.5% vs. 20.8%, P<0.001), a higher frequency of GGO growth (30.2% vs. 16.4%, P=0.02), and a shorter median time from baseline to GGO growth (25.0 months vs. not achieved, P<0.001). However, in mixed-GGOs, GGO-A was only with a higher proportion of IAs than GGO-nA (90.8% vs. 66.7%, P=0.001).

Similarly, for smoking status, we classified patients into non-smokers and smokers, and then analyzed the aggressiveness (Table S2). For non-smokers, compared to GGO-nAs, GGO-As had a higher proportion of IAs (72.4% vs. 37.2%, P<0.001), a higher frequency of GGO growth (28.8% vs. 17.1%, P=0.044), and a shorter median time from baseline to GGO growth (23.0 months vs. not achieved, P<0.001). However, for smokers, GGO-As only had a shorter median time from baseline to GGO growth (32.0 vs. 43.0 months, P=0.001) than GGO-nAs.

Discussion

Previous studies have suggested two hypotheses about LCCA’s pathogenesis (Figure S2): (I) Proliferation of tumor cells lead to the cystic airspaces (13,22). Specifically, tumor cells grow along the alveolar wall and form a small nodule, contributing to the unidirectional bronchiolar valve in the lung. This increases the pressure of the alveoli, leading to the expansion and fusion of the alveoli and the formation of cystic airspaces. (II) Tumor cells develop secondary to the existing cystic airspaces in the lung (21,32). The existing cystic airspaces interfere with ventilation and self-clearance of the lung, leading to the deposition of microbial and carcinogens on the cavity wall, recurrent infection of the lesion, the formation of fibrous scars, and the induction of cancer. Our results supported the second hypothesis, as there was a strong association between GGO-As and emphysema pulmonum and pulmonary bullae.

In our study, GGO-A lesions were significantly larger than GGO-nA lesions on both CT imaging and pathological assessment. Notably, all GGO-As had cystic airspaces larger than 5 mm, which may introduce a potential tumor size bias. However, larger lesion size may influence surgical decision-making by making it more challenging to achieve adequate margins with sublobar resection, thereby contributing to the higher frequency of lobectomy in this group. This may explain why the proportion of lobectomy was higher in the GGO-A group compared to the GGO-nA group.

The higher rate of lobectomy observed in GGO-A patients reflects both preoperative suspicion and intraoperative findings of more invasive disease. Given the higher proportion of IA and rapid radiological progression in GGO-A, a more cautious approach to sublobar resection may be warranted. For GGO-A lesions, particularly those with solid components or concerning cystic morphology, intraoperative frozen section analysis is critical to guide the extent of resection, and surgeons should maintain a low threshold for lobectomy when invasive disease is confirmed.

Previous studies have shown that KRAS was associated with LCCA. Fintelmann et al. reported KRAS mutation was the predominant genetic alteration in LCCAs (16), while Shen reported EGFR mutations was the predominant genetic alteration in LCCAs (16). We considered this conflict is due to the varying landscape of driver-gene mutation between Asians and Europeans. In our study, EGFR was the predominant genetic alteration in both GGO-As and GGO-nAs, while KRAS mutated more frequently in GGO-As than GGO-nAs. Compared to previous studies, our study included a more significant number of patients, as well as conducted a comparative analysis between the two groups, making a convincing conclusion. As reported (33,34), KRAS mutations are known drivers of lung adenocarcinoma associated with aggressive biological behavior and poorer survival outcomes when compared to EGFR mutations. This molecular finding may partially explain the more aggressive clinicopathological features of GGO-A, such as higher rates of IA and rapid radiological progression. From a translational perspective, if confirmed in larger cohorts, KRAS mutation status could serve as a complementary biomarker for postoperative risk stratification in GGO-A patients, potentially identifying those who may benefit from more intensive surveillance.

Since whether the aggressiveness of GGO-A differs from that of GGO-nA remains unknown, we compared the two groups in terms of pathological features and radiological progression. Our results consistently showed that GGO-A was associated with higher aggressiveness, suggesting more proactive treatment or shorter follow-up intervals for patients with GGO-As. Additionally, although the difference did not reach statistical significance, GGO-A showed worse recurrence outcomes than GGO-nA, with a consistent trend toward inferior prognosis. A very recent large-cohort study by Wang et al. (35) also demonstrated that LCCA exhibited worse 5-year overall survival compared with non-cystic lung cancers, further supporting the clinical significance of this entity. In contrast, while Wang’s study examined a broader LCCA population, our study focuses specifically on GGO-dominant lesions (size ≤2.0 cm, CTR ≤50%) and provides a more detailed characterization of their aggressive features. Specifically, we demonstrated that GGO-A lesions harbored a higher proportion of IA, a higher frequency of KRAS mutations, and faster radiological progression compared with GGO-nA. Additionally, we explored the implications of these findings for surgical decision-making, an aspect not addressed in the prior study.

Previous studies classified LCCAs into four subtypes according to the morphology of cystic airspaces but ignored the solid components in CT images (16,18,21,22,36). One previous study (18) found that type III of LCCA was associated with moderately/poorly differentiated tumors. However, our further analysis of pathological aggressiveness of 4 subtypes of GGO-As showed no significant difference, which may be attributed to the small sample sizes in type II (n=7) and type III (n=12). According to the definition of subtypes of LCCA in previous studies, type II and III may contain more solid components in CT images, which are associated with higher aggressiveness and worse prognosis (5,37,38). We consider this may also be the reason for the different conclusions between our study and previous studies, which emphasized the importance to distinguish GGOs from all lesions suspected as LCCAs.

In our research, GGO-As had a higher proportion of mixed-GGOs than GGO-nAs. Therefore, we categorized lesions into pure-GGOs and mixed-GGOs and then analyzed. In pure-GGOs, compared to GGO-nAs, GGO-As were associated with higher aggressiveness in different aspects. However, this association was less significant when pure-GGO developed into mixed-GGO, as the solid components in mixed-GGO already indicated higher aggressiveness, no matter in GGO-A or GGO-nA. Similar results were observed in non-smokers and smokers, suggesting that GGO-As were associated with higher aggressiveness for non-smokers. And the association was less significant for smokers, as smoking was a risk factor for exacerbating lung cancer progression (39,40) and associated with higher aggressiveness, no matter in GGO-As or GGO-nAs.

However, we did not provide data on prognosis in this study. As the good prognoses of small-size GGO after an operation, data on prognosis need longer time for following up. Nonetheless, by comparing with GGO-nA, this study provided critical information for clinical oncologists, especially for thoracic surgeons.

Conclusions

In our study, compared to patients with GGO-nAs, we observed distinct clinical characteristics in patients with GGO-As, including being male, without family history of cancer, with emphysema pulmonum and with pulmonary bullae. As confirmed by pathological performance and radiological progression, our analysis also revealed that GGO-As were associated with higher aggressiveness, compared to GGO-nAs, especially for pure-GGOs and non-smokers, suggesting more proactive decision-making for clinicians when managing GGO-As. Furthermore, we found a higher frequency of KRAS mutations in GGO-As, which may be of significance in developing further exploration for GGO-As and LCCAs.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0027/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0027/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0027/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2026-1-0027/coif). W.L. serves as an unpaid Associate Editor-in-Chief of Translational Lung Cancer Research from May 2025 to April 2026. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (No. ES-2023-206-01), and all participants provided written informed consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Hashizume T, Yamada K, Okamoto N, et al. Prognostic significance of thin-section CT scan findings in small-sized lung adenocarcinoma. Chest 2008;133:441-7. [Crossref] [PubMed]
2. Travis WD, Brambilla E, Noguchi M, 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;6:244-85. [Crossref] [PubMed]
3. Pan X, Yang X, Li J, et al. Is a 5-mm diameter an appropriate cut-off value for the diagnosis of atypical adenomatous hyperplasia and adenocarcinoma in situ on chest computed tomography and pathological examination? J Thorac Dis 2018;10:S790-6. [Crossref] [PubMed]
4. Kakinuma R, Muramatsu Y, Kusumoto M, et al. Solitary Pure Ground-Glass Nodules 5 mm or Smaller: Frequency of Growth. Radiology 2015;276:873-82. [Crossref] [PubMed]
5. Travis WD, Asamura H, Bankier AA, et al. The IASLC Lung Cancer Staging Project: Proposals for Coding T Categories for Subsolid Nodules and Assessment of Tumor Size in Part-Solid Tumors in the Forthcoming Eighth Edition of the TNM Classification of Lung Cancer. J Thorac Oncol 2016;11:1204-23.
6. Tsuta K, Kawago M, Inoue E, et al. The utility of the proposed IASLC/ATS/ERS lung adenocarcinoma subtypes for disease prognosis and correlation of driver gene alterations. Lung Cancer 2013;81:371-6. [Crossref] [PubMed]
7. Yoshizawa A, Motoi N, Riely GJ, et al. Impact of proposed IASLC/ATS/ERS classification of lung adenocarcinoma: prognostic subgroups and implications for further revision of staging based on analysis of 514 stage I cases. Mod Pathol 2011;24:653-64. [Crossref] [PubMed]
8. Boffa DJ, Allen MS, Grab JD, et al. Data from The Society of Thoracic Surgeons General Thoracic Surgery database: the surgical management of primary lung tumors. J Thorac Cardiovasc Surg 2008;135:247-54. [Crossref] [PubMed]
9. Saji H, Okada M, Tsuboi M, et al. Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): a multicentre, open-label, phase 3, randomised, controlled, non-inferiority trial. Lancet 2022;399:1607-17. [Crossref] [PubMed]
10. Altorki N, Wang X, Kozono D, et al. Lobar or Sublobar Resection for Peripheral Stage IA Non-Small-Cell Lung Cancer. N Engl J Med 2023;388:489-98. [Crossref] [PubMed]
11. Austin JH, Müller NL, Friedman PJ, et al. Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society. Radiology 1996;200:327-31. [Crossref] [PubMed]
12. Hansell DM, Bankier AA, MacMahon H, et al. Fleischner Society: glossary of terms for thoracic imaging. Radiology 2008;246:697-722. [Crossref] [PubMed]
13. Farooqi AO, Cham M, Zhang L, et al. Lung cancer associated with cystic airspaces. AJR Am J Roentgenol 2012;199:781-6. [Crossref] [PubMed]
14. Scholten ET, Horeweg N, de Koning HJ, et al. Computed tomographic characteristics of interval and post screen carcinomas in lung cancer screening. Eur Radiol 2015;25:81-8. [Crossref] [PubMed]
15. Tan Y, Gao J, Wu C, et al. CT Characteristics and Pathologic Basis of Solitary Cystic Lung Cancer. Radiology 2019;291:495-501. [Crossref] [PubMed]
16. Fintelmann FJ, Brinkmann JK, Jeck WR, et al. Lung Cancers Associated With Cystic Airspaces: Natural History, Pathologic Correlation, and Mutational Analysis. J Thorac Imaging 2017;32:176-88. [Crossref] [PubMed]
17. Snoeckx A, Reyntiens P, Carp L, et al. Diagnostic and clinical features of lung cancer associated with cystic airspaces. J Thorac Dis 2019;11:987-1004. [Crossref] [PubMed]
18. Shen Y, Xu X, Zhang Y, et al. Lung cancers associated with cystic airspaces: CT features and pathologic correlation. Lung Cancer 2019;135:110-5. [Crossref] [PubMed]
19. Snoeckx A, Reyntiens P, Desbuquoit D, et al. Evaluation of the solitary pulmonary nodule: size matters, but do not ignore the power of morphology. Insights Imaging 2018;9:73-86. [Crossref] [PubMed]
20. Erasmus JJ, Connolly JE, McAdams HP, et al. Solitary pulmonary nodules: Part I. Morphologic evaluation for differentiation of benign and malignant lesions. Radiographics 2000;20:43-58.
21. Sheard S, Moser J, Sayer C, et al. Lung Cancers Associated with Cystic Airspaces: Underrecognized Features of Early Disease. Radiographics 2018;38:704-17. [Crossref] [PubMed]
22. Mascalchi M, Attinà D, Bertelli E, et al. Lung cancer associated with cystic airspaces. J Comput Assist Tomogr 2015;39:102-8. [Crossref] [PubMed]
23. Hiramatsu M, Inagaki T, Inagaki T, et al. Pulmonary ground-glass opacity (GGO) lesions-large size and a history of lung cancer are risk factors for growth. J Thorac Oncol 2008;3:1245-50. [Crossref] [PubMed]
24. de Hoop B, Gietema H, van de Vorst S, et al. Pulmonary ground-glass nodules: increase in mass as an early indicator of growth. Radiology 2010;255:199-206. [Crossref] [PubMed]
25. Usuda K, Saito Y, Sagawa M, et al. Tumor doubling time and prognostic assessment of patients with primary lung cancer. Cancer 1994;74:2239-44. [Crossref] [PubMed]
26. Hasegawa M, Sone S, Takashima S, et al. Growth rate of small lung cancers detected on mass CT screening. Br J Radiol 2000;73:1252-9. [Crossref] [PubMed]
27. Howington JA, Blum MG, Chang AC, et al. Treatment of stage I and II non-small cell lung cancer: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143:e278S-313S.
28. Postmus PE, Kerr KM, Oudkerk M, et al. Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2017;28:iv1-21. [Crossref] [PubMed]
29. Warth A, Muley T, Meister M, et al. The novel histologic International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification system of lung adenocarcinoma is a stage-independent predictor of survival. J Clin Oncol 2012;30:1438-46. [Crossref] [PubMed]
30. Moreira AL, Ocampo PSS, Xia Y, et al. A Grading System for Invasive Pulmonary Adenocarcinoma: A Proposal From the International Association for the Study of Lung Cancer Pathology Committee. J Thorac Oncol 2020;15:1599-610. [Crossref] [PubMed]
31. Takeuchi K, Soda M, Togashi Y, et al. RET, ROS1 and ALK fusions in lung cancer. Nat Med 2012;18:378-81. [Crossref] [PubMed]
32. Hurley P, Corbishley C, Pepper J. Bronchioloalveolar carcinoma arising in longstanding lung cysts. Thorax 1985;40:960. [Crossref] [PubMed]
33. Abolfathi H, Kordahi M, Armero VS, et al. Clinicopathologic characteristics, co-mutation landscape, and survival outcomes of KRAS-G12D mutant lung adenocarcinoma in comparison to KRAS-G12C and EGFR-mutated subtypes. Lung Cancer 2025;205:108596. [Crossref] [PubMed]
34. Ji X, Liu M, Zhang T, et al. KRAS/PI3K axis driven GTF3C6 expression and promotes LUAD via FAK pathway. J Adv Res 2025;70:243-54. [Crossref] [PubMed]
35. Wang K, Yi H, Wu S, et al. Prognostic heterogeneity of lung cancer associated with cystic airspaces and identification of novel imaging subtypes: a multi-center cohort study. Int J Surg 2026;112:7435-44.
36. Shen Y, Zhang Y, Guo Y, et al. Prognosis of lung cancer associated with cystic airspaces: A propensity score matching analysis. Lung Cancer 2021;159:111-6. [Crossref] [PubMed]
37. Nakamura S, Fukui T, Taniguchi T, et al. Prognostic impact of tumor size eliminating the ground glass opacity component: modified clinical T descriptors of the tumor, node, metastasis classification of lung cancer. J Thorac Oncol 2013;8:1551-7. [Crossref] [PubMed]
38. Liu Y, Sun H, Zhou F, et al. Imaging features of TSCT predict the classification of pulmonary preinvasive lesion, minimally and invasive adenocarcinoma presented as ground glass nodules. Lung Cancer 2017;108:192-7. [Crossref] [PubMed]
39. Alberg AJ, Samet JM. Epidemiology of lung cancer. Chest 2003;123:21S-49S. [Crossref] [PubMed]
40. Jiang YJ, Chao CC, Chang AC, et al. Cigarette smoke-promoted increases in osteopontin expression attract mesenchymal stem cell recruitment and facilitate lung cancer metastasis. J Adv Res 2022;41:77-87. [Crossref] [PubMed]