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Cancer Management and Research logoLink to Cancer Management and Research
. 2026 Oct 7;18:611348. doi: 10.2147/CMAR.S611348

MSCT Manifestations and Quantitative Dynamic Evolution of Lung Cancer Associated with Cystic Airspaces: A Retrospective Analysis of 102 Cases with Emphasis on Adenocarcinoma

Xiaoqin Luo 1,*, Shan Lan 1,*, Chengwen Tong 1,✉
PMCID: PMC13654261  PMID: 42861141

Abstract

Objective

Cystic lung cancer (CLC) refers to lung cancer associated with cystic airspaces. This study characterized the Multi-Slice Computed Tomography (MSCT) features of CLC, with subtype-specific and longitudinal analyses restricted to adenocarcinoma cases.

Methods

We retrospectively analyzed 102 patients with pathologically confirmed CLC at Renmin Hospital (2018–2025). Of these, 94 (92.2%) had adenocarcinoma, classified per the IASLC/ATS/ERS system; MSCT features were compared across subtypes using Chi-square tests. The 8 non-adenocarcinoma cases were described separately. A subgroup of 45 patients with serial CT (≥3-month interval), all with adenocarcinoma, was assessed for longitudinal changes.

Results

The cohort included 64 males and 38 females (mean age 64.2 ± 11.7 years). Histology showed adenocarcinoma in 94 cases (42 acinar, 28 lepidic, 14 papillary, 10 solid/micropapillary), 6 squamous cell carcinomas, and 2 sarcomatoid carcinomas. In the 8 non-adenocarcinoma cases, irregular shape and uneven wall thickness each occurred in 7/8 (87.5%), wall nodules in 6/8 (75.0%). Overall, 78/102 (76.5%) lesions were irregular and 74/102 (72.5%) showed uneven wall thickness. In adenocarcinoma, uneven wall thickness (P = 0.008) and internal septations (P = 0.001) were associated with lepidic/acinar subtypes, whereas solid/micropapillary subtypes showed thicker walls and more frequent wall nodules. In the dynamic group (n=45), solid-component growth rate (1.21 ± 0.29 mm/month) exceeded cystic-airspace growth (0.31 ± 0.11 mm/month, P < 0.001) and correlated with follow-up interval (r = 0.81, P < 0.001). In multivariable analysis restricted to adenocarcinoma, wall thickness >4 mm was independently associated with solid/micropapillary subtypes (OR = 5.78, 95% CI 1.28–26.02, P = 0.022); other variables were nonsignificant trends.

Conclusion

CLC exhibits MSCT features that correlate with adenocarcinoma subtypes, with progressive solid-component growth over time. These observations are descriptive; prospective multicenter studies including benign cystic lesions and more non-adenocarcinoma cases are needed before diagnostic application.

Keywords: lung neoplasms, lung adenocarcinoma, cystic airspaces, tomography, x-ray computed, diagnostic imaging, disease progression

Introduction

Lung cancer remains the leading cause of cancer-related mortality worldwide, necessitating early and accurate detection to improve survival rates.1 While the typical radiological presentations of lung cancer are well-established, “cystic lung cancer” (CLC), also termed lung cancer associated with cystic airspaces, represents a distinct and increasingly recognized morphological subtype that poses significant diagnostic challenges.2 CLC is defined as a lung cancer arising from or growing along the wall of a cystic airspace and encompasses a range of histologies, most commonly adenocarcinoma but also squamous cell carcinoma, sarcomatoid carcinoma, and other subtypes.2,3 Because these lesions closely mimic benign conditions such as pulmonary bullae or infectious cavities, they are frequently misdiagnosed or overlooked during screening, contributing to delayed treatment.3

The pathogenesis of cystic lung cancer (CLC) remains incompletely understood.4 Proposed mechanisms include the “check-valve” mechanism, where partial airway obstruction leads to distal air trapping and cyst formation,5 and the theory that tumors arise from or colonize pre-existing cystic lesions, such as emphysematous bullae.4,6 Cancers arising from bulla walls have been reported to include poorly differentiated carcinomas and non-adenocarcinoma histologies; however, adenocarcinoma—particularly lepidic, acinar, papillary, and solid-predominant subtypes—has been the most frequently described histology in recent surgical and imaging series.2,6 Recent advancements in the International Association for the Study of Lung Cancer (IASLC) classification of lung adenocarcinoma have highlighted significant tumor heterogeneity at the molecular and histological levels.7 However, there is a recognized paucity of literature specifically correlating the detailed CT features of cystic lung adenocarcinoma with these granular pathological subtypes (eg, lepidic vs acinar predominant patterns), indicating an area requiring further research.8

Furthermore, although static CT features such as irregular wall thickness and internal septations have been described in malignant cystic lung lesions,9 the longitudinal evolution of cystic lung adenocarcinoma remains under-characterized. Existing reports have largely emphasized qualitative changes, including progressive wall thickening, emergence of a mural nodule, enlargement of the solid component, and occasional reduction or disappearance of the cystic airspace.10,11 Quantitative characterization of these changes may improve recognition of morphologic progression and provide a basis for prospective validation.

Therefore, this retrospective, single-center study analyzed 102 patients with pathologically confirmed lung cancer associated with cystic airspaces over a 7-year period. Because 92.2% of the cohort had adenocarcinoma, the primary analyses focused on adenocarcinoma and included: (1) characterization of MSCT features across histologic patterns; and (2) quantitative assessment of longitudinal changes in cystic-airspace diameter and solid-component size in patients with serial pre-treatment CT. The 8 non-adenocarcinoma cases were retained for descriptive analysis, and no subtype-specific inference was made for these cases.

Materials and Methods

Study Population

This retrospective study was approved by the Ethics Committee of Renmin Hospital, Hubei University of Medicine (SY2026025). The study was performed in accordance with the Helsinki II declaration. The requirement for informed consent was waived by the Ethics Committee due to the retrospective nature of the analysis. We reviewed the medical records and imaging data of all consecutive patients with surgically resected or biopsy-confirmed primary lung cancer at our institution between January 2018 and June 2025. The inclusion criteria were modeled on prior studies investigating lung cancers associated with cystic airspaces:12,13 (1) Pathologically confirmed primary lung cancer; (2) Preoperative thin-section CT showing a cystic airspace within or associated with the tumor (cyst diameter >5 mm);12 (3) Availability of complete clinical and pathological data. Exclusion criteria were: (1) Cavitary lesions caused by tumor necrosis (thick-walled cavities with irregular inner margins and no septations); (2) Metastatic lung tumors; (3) Poor image quality affecting analysis.

A total of 102 patients met the inclusion criteria among 1450 consecutive patients screened. Pathological examination revealed adenocarcinoma in 94 patients (92.2%), squamous cell carcinoma in 6 (5.9%), and sarcomatoid carcinoma in 2 (2.0%). Among the 94 adenocarcinoma cases, 45 had at least two serial pre-treatment CT examinations separated by ≥3 months and constituted the dynamic observation group. The remaining 49 adenocarcinoma cases had a single eligible pre-treatment CT examination. The 8 non-adenocarcinoma cases did not enter the quantitative longitudinal analysis and were evaluated descriptively only.

CT Image Acquisition

Chest CT scans were performed using a Siemens Somatom Definition AS+ (64-slice) or a Philips Brilliance iCT (256-slice) scanner. The scanning parameters were: tube voltage 120 kV, automatic tube current modulation, matrix 512×512. Images were reconstructed with a slice thickness of 1.0 mm or 1.25 mm. Contrast-enhanced scans were available for 78 patients (76.5%), utilizing non-ionic iodinated contrast material (Iohexol, 350 mgI/mL) injected at 2.5–3.0 mL/s. Arterial and venous phase images were acquired at 25s and 60s post-injection, respectively.

Image Analysis

Two radiologists with over 10 years of experience in thoracic imaging reviewed the images independently on a PACS workstation, blinded to the pathological details. Discrepancies were resolved by consensus, a method commonly employed to assess interobserver agreement in imaging studies.14 The following MSCT features were evaluated using standardized terminology where applicable:15

Morphology: Shape (round/oval vs irregular), maximum diameter of the cyst, and maximum diameter of the solid component.

Wall Characteristics: Maximum wall thickness, uniformity (even vs uneven), and presence of wall nodules

Internal Features: Presence of septations (honeycombing), vascular convergence, and bronchial abnormalities (truncation or distortion).

External Features: Ground-glass opacity (GGO), spiculation, pleural indentation, and emphysematous changes in the surrounding lung.

For the dynamic observation group, the growth rate of cystic-airspace diameter and solid-component size was calculated as: (Final Diameter - Initial Diameter) / Interval (months).

Pathological Classification

Histological subtypes of the 94 lung adenocarcinomas were re-evaluated according to WHO classification criteria for thoracic tumors.16,17 Tumors were classified by their predominant pattern as lepidic, acinar, papillary, micropapillary, or solid. Because subgroup sizes were limited, solid- and micropapillary-predominant tumors were combined for statistical analysis. Non-adenocarcinoma cases (squamous cell carcinoma and sarcomatoid carcinoma) were not subclassified and were analyzed descriptively.

Statistical Analysis

Statistical analysis was performed using SPSS version 26.0 (IBM Corp, Armonk, NY) and Python 3.13 (statsmodels). Continuous variables were expressed as mean ± standard deviation (SD) and compared using the Student’s t-test or Mann–Whitney U-test. Categorical variables were presented as frequencies and percentages, compared using the chi-square test or Fisher’s exact test. Multivariable logistic regression analysis was performed among adenocarcinoma cases to identify imaging features associated with solid/micropapillary predominant subtypes. Non-adenocarcinoma cases were described separately owing to their small numbers. A P-value < 0.05 was considered statistically significant.

Results

Typical MSCT Manifestations

The morphological features of lung cancer associated with cystic airspaces in our cohort were diverse. The most common presentation was an irregular cystic airspace with uneven wall thickness. Figure 1A shows a lepidic-predominant adenocarcinoma with fine internal septations and surrounding ground-glass opacity (GGO). Figure 1B shows an acinar-predominant adenocarcinoma with convergence and distortion of adjacent vessels. Figure 1C illustrates longitudinal morphologic progression in adenocarcinoma, with reduction of the cystic airspace, marked wall thickening, and development of a solid component at 26 months.

Figure 1.

Three chest CT images (A, B, C) show dark lungs, bright chest wall and central mediastinal tissue.

Representative MSCT manifestations in adenocarcinoma associated with cystic airspaces. (A) A 58-year-old male with lepidic-predominant adenocarcinoma: axial CT shows an irregular cystic lesion in the right upper lobe with fine internal septations and surrounding ground-glass opacity (GGO). (B) A 64-year-old female with acinar-predominant adenocarcinoma: axial CT shows an oval cystic lesion in the right lower lobe with convergence and distortion of adjacent vessels. (C) A 71-year-old male with adenocarcinoma: follow-up CT at 26 months shows reduction of the cystic airspace, marked wall thickening, and development of a solid component.

Patient Selection and Demographics

The study enrollment process is detailed in the flowchart in Figure 2. Out of 1450 consecutive patients with primary lung cancer screened, 102 met the strict inclusion criteria for CLC. The baseline demographic and clinical characteristics of these 102 patients are summarized in Table 1. The mean age was 64.2 ± 11.7 years, and 58/102 (56.9%) were smokers. Adenocarcinoma was the dominant histological subtype (92.2%; n=94), followed by squamous cell carcinoma (5.9%; n=6) and sarcomatoid carcinoma (2.0%; n=2).

Figure 2.

A flowchart of lung cancer study enrollment and categorization process. The flowchart outlines the enrollment process for a lung cancer study. It starts with ′Consecutive patients with surgically resected or biopsy-confirmed primary lung cancer, January 2018-June 2025 (n equals 1450).′ These are narrowed down to ′Patients meeting inclusion criteria for lung cancer with cystic airspaces (n equals 102).′ This group is split into ′Adenocarcinoma (n equals 94)′ and ′Non-adenocarcinoma (n equals 8).′ The adenocarcinoma group is divided into ′Dynamic observation group (n equals 45)′ and ′Single-time-point group (n equals 49).′ The dynamic group undergoes ′Quantitative analysis of cystic-airspace and solid-component changes,′ while the single-time-point group has ′Static MSCT feature analysis.′ The non-adenocarcinoma group includes ′Squamous cell carcinoma (n equals 6)′ and ′Sarcomatoid carcinoma (n equals 2),′ with ′Descriptive analysis only.′ Supplementary Table S1 provides descriptive features.

Study flowchart. Consecutive patients with surgically resected or biopsy-confirmed primary lung cancer were screened (n=1450). Of these, 102 met the inclusion criteria for lung cancer associated with cystic airspaces and were categorized as adenocarcinoma (n=94) or non-adenocarcinoma (n=8). The adenocarcinoma cohort was divided into a dynamic observation group (n=45) and a single-time-point group (n=49). The non-adenocarcinoma cases were analyzed descriptively.

Abbreviations: CT, computed tomography; MSCT, multislice computed tomography.

Table 1.

Demographic and Clinical Characteristics of 102 Patients with Lung Cancer Associated with Cystic Airspaces

Characteristic n (%) or Mean ± SD Characteristic n (%) or Mean ± SD
Age (years) 64.2 ± 11.7 Sex
 <60 38 (37.3) Male 64 (62.7)
 ≥60 64 (62.7) Female 38 (37.3)
Smoking history Tumor location
 Smoker 58 (56.9) Right upper lobe 32 (31.4)
 Non-smoker 44 (43.1) Right middle lobe 8 (7.8)
Pathological type Right lower lobe 24 (23.5)
 Adenocarcinoma 94 (92.2) Left upper lobe 22 (21.6)
 Squamous cell carcinoma 6 (5.9) Left lower lobe 16 (15.7)
 Sarcomatoid carcinoma 2 (2.0) Dynamic observation group 45 (44.1)

Notes: Data are presented as n (%) unless otherwise indicated.

Abbreviation: SD, standard deviation.

Correlation Between Pathology and Imaging Features in Adenocarcinoma

We analyzed the frequency of selected MSCT features across adenocarcinoma subtypes. As shown in Figure 3 and Table 2, surrounding GGO was most frequent in lepidic-predominant tumors (23/28, 82.1%), whereas wall nodules were more frequent in acinar (21/42, 50.0%) and solid/micropapillary-predominant tumors (5/10, 50.0%) than in lepidic-predominant tumors (4/28, 14.3%). Internal septations were also most frequent in lepidic-predominant tumors (24/28, 85.7%) and least frequent in solid/micropapillary-predominant tumors (2/10, 20.0%). Uneven wall thickness increased across the subtype groups and was present in all solid/micropapillary-predominant tumors (10/10, 100.0%). Overall differences across subtypes were significant for uneven wall thickness (P=0.008), internal septations (P=0.001), surrounding GGO (P<0.001), and wall nodules (P=0.019).

Figure 3.

A grouped bar graph showing prevalence of surrounding ground glass opacity and wall nodule by subtype.

Distribution of surrounding ground-glass opacity and wall nodules across lung adenocarcinoma subtypes.

Abbreviations: GGO, ground-glass opacity; MSCT, multislice computed tomography.

Table 2.

Comparison of Selected MSCT Features Among Lung Adenocarcinoma Subtypes

MSCT feature Lepidic (n=28) Acinar (n=42) Papillary (n=14) Solid/Micropapillary (n=10) P value
Irregular shape 18/28 (64.3) 33/42 (78.6) 11/14 (78.6) 9/10 (90.0) 0.344
Uneven wall thickness 14/28 (50.0) 31/42 (73.8) 12/14 (85.7) 10/10 (100.0) 0.008
Internal septations 24/28 (85.7) 30/42 (71.4) 8/14 (57.1) 2/10 (20.0) 0.001
Surrounding GGO 23/28 (82.1) 12/42 (28.6) 3/14 (21.4) 2/10 (20.0) <0.001
Wall nodule 4/28 (14.3) 21/42 (50.0) 5/14 (35.7) 5/10 (50.0) 0.019
Vascular convergence 12/28 (42.9) 25/42 (59.5) 9/14 (64.3) 6/10 (60.0) 0.457

Notes: Values are n/N (%). P values were calculated using the chi-square test or Fisher exact test, as appropriate.

Abbreviations: GGO, ground-glass opacity; MSCT, multislice computed tomography.

Imaging Features of Non-Adenocarcinoma Cases

Among the 8 non-adenocarcinoma cases (6 squamous cell carcinomas and 2 sarcomatoid carcinomas), irregular shape and uneven wall thickness were each observed in 7/8 (87.5%), wall nodules in 6/8 (75.0%), vascular convergence in 5/8 (62.5%), surrounding GGO in 1/8 (12.5%), and internal septations in 2/8 (25.0%) (Supplementary Table S1). Given the small sample size, these findings are descriptive; no formal comparison with adenocarcinoma cases was performed.

Quantitative Analysis of Dynamic Changes

In the dynamic observation group (n=45), which comprised only adenocarcinoma cases, the mean solid-component growth rate (1.21 ± 0.29 mm/month) was significantly greater than the mean cystic-airspace diameter growth rate (0.31 ± 0.11 mm/month; P<0.001) (Figure 4A). Follow-up interval correlated positively with the absolute increase in solid-component size (r=0.81, P<0.001) (Figure 4B). The follow-up interval ranged from 8.3 to 42.0 months.

Figure 4.

Two plots comparing growth rates and follow up interval versus solid component growth. Image A features a box and whisker plot titled ′Comparison of Growth Rates.′ The x-axis is labeled ′Cystic Airspace Diameter and Solid Component Size,′ while the y-axis is ′Growth Rate (mm/month),′ ranging from 0.0 to 2.5. The cystic airspace diameter box is centered at 0.3, with whiskers from 0.1 to 0.5, noted as 0.31 plus or minus 0.11. The solid component size box is centered at 1.2, with whiskers from 0.9 to 1.7 and outliers at 1.9 and 2.3, noted as 1.21 plus or minus 0.29. Image B shows a scatter plot titled ′Follow-up Interval vs Solid Component Growth,′ with r equals 0.81, P less than 0.001. The x-axis is ′Follow-up Interval (months),′ ranging from 10 to 40 and the y-axis is ′Increase in Solid Component Size (mm),′ ranging from 10 to 40. A legend lists ′Dynamic Observation Group n equals 45′ and ′Linear Fit r equals 0.81.′ Points range from (10, 10) to (42, 35), with a dashed linear fit line from 14 at 10 months to 39 at 42 months.

Quantitative longitudinal changes in adenocarcinoma cases. (A) Comparison of growth rates for cystic-airspace diameter and solid-component size. Boxes indicate interquartile range (IQR) with horizontal median lines; whiskers extend to the most extreme values within 1.5 × IQR; circles beyond the whiskersrepresent individual patient outliers. (B) Scatter plot showing the association between follow-up interval and absolute increase in solid-component size. Each circle represents one patient in the dynamic observation group (n = 45, all adenocarcinoma); the dashed red line denotes the linear fit (r = 0.81, P < 0.001).

Multivariable Analysis of Solid/Micropapillary-Predominant Adenocarcinoma

To explore imaging features associated with solid/micropapillary-predominant adenocarcinoma, we performed multivariable logistic regression restricted to adenocarcinoma cases. Maximum wall thickness >4 mm was associated with the solid/micropapillary-predominant group (OR 5.78, 95% CI 1.28–26.02, P=0.022). Wall nodules (OR 1.76, 95% CI 0.41–7.61, P=0.451), absence of surrounding GGO (OR 3.83, 95% CI 0.68–21.65, P=0.129), and vascular convergence (OR 0.94, 95% CI 0.22–3.91, P=0.929) were not statistically significant (Table 3).

Table 3.

Multivariable Logistic Regression of Imaging Features Associated with Solid/Micropapillary-Predominant Adenocarcinoma

Imaging Feature Odds Ratio 95% CI P value
Maximum wall thickness >4 mm 5.78 1.28–26.02 0.022
Wall nodule 1.76 0.41–7.61 0.451
Absence of surrounding GGO 3.83 0.68–21.65 0.129
Vascular convergence 0.94 0.22–3.91 0.929

Note: The model was restricted to the 94 adenocarcinoma cases; the outcome was solid/micropapillary-predominant histology (n=10).

Abbreviations: CI, confidence interval; GGO, ground-glass opacity.

Discussion

This study characterized the MSCT appearance and longitudinal evolution of lung cancer associated with cystic airspaces in 102 patients. Because 94 cases were adenocarcinoma, the subtype-specific, longitudinal, and multivariable analyses were intentionally restricted to adenocarcinoma, while the 8 non-adenocarcinoma cases were reported descriptively. The principal contribution is the combination of a relatively large single-center cohort, quantitative longitudinal measurements, and correlation of selected imaging features with adenocarcinoma histologic patterns. The findings should be interpreted as descriptive and exploratory rather than as validated diagnostic criteria.

A key finding was the subtype-dependent distribution of imaging features within adenocarcinoma (Table 2). Lepidic-predominant tumors frequently showed surrounding GGO and internal septations, consistent with preservation of alveolar architecture and lepidic growth.18–20 Solid/micropapillary-predominant tumors showed the highest prevalence of uneven wall thickness, while wall nodules were frequent in both acinar and solid/micropapillary-predominant tumors. Thus, a wall nodule alone was not specific to the solid/micropapillary group. The greater prevalence of thick and irregular walls in higher-grade patterns is broadly consistent with prior studies linking solid tumor appearance and related CT characteristics with invasive histology.21–24 The cystic appearance in some high-grade tumors may reflect airway obstruction, remodeling, or necrotic change rather than lepidic growth.25

Longitudinal morphologic change is an important feature of lung cancer associated with cystic airspaces. Serial CT reports have described progressive wall thickening, emergence or enlargement of a solid component, and occasional reduction of the cystic airspace over time.10,11 In our adenocarcinoma subgroup, solid-component size increased more rapidly than cystic-airspace diameter, and the absolute increase in solid-component size correlated with follow-up duration. These findings support careful comparison with prior CT examinations when a cystic lung lesion develops focal wall thickening or a new mural component.2,3,9

The multivariable analysis in Table 3 showed an association between maximum wall thickness >4 mm and solid/micropapillary-predominant cystic lung adenocarcinoma. However, because the study included only pathologically confirmed malignant lesions and no benign cystic control group, this association should not be interpreted as a validated marker for distinguishing malignant from benign cystic lesions. In addition, only 10 patients had solid/micropapillary-predominant adenocarcinoma; therefore, the estimate was imprecise, as reflected by the wide confidence interval, and should be interpreted as exploratory.

The primary strengths of this study are the relatively large cohort for this uncommon radiologic presentation and the quantitative longitudinal analysis in 45 adenocarcinoma cases followed for up to 42 months. The study also provides a granular description of selected MSCT features across adenocarcinoma histologic patterns. Several limitations should be acknowledged. First, this was a retrospective, single-center study and is therefore susceptible to selection bias. The predominance of adenocarcinoma (92.2%) may reflect institutional referral and treatment patterns; consequently, the subtype-specific findings should not be generalized to squamous cell or sarcomatoid cancers associated with cystic airspaces. Second, the 8 non-adenocarcinoma cases were insufficient for comparative analysis and were therefore described only. Third, the solid/micropapillary group included only 10 patients, producing imprecise multivariable estimates with wide confidence intervals. Fourth, patients who underwent serial imaging may have had less immediately suspicious lesions, whereas more concerning lesions may have proceeded directly to treatment, potentially biasing growth-rate estimates. Fifth, measurements were manual and two-dimensional; future studies should evaluate three-dimensional volumetric measures. Finally, genomic data were incomplete, precluding radiogenomic analysis.

In conclusion, lung cancer associated with cystic airspaces shows heterogeneous MSCT features. Within adenocarcinoma, lepidic-predominant tumors more frequently showed surrounding GGO and internal septations, whereas solid/micropapillary-predominant tumors more frequently showed uneven wall thickness. In the longitudinal adenocarcinoma subgroup, the solid component enlarged more rapidly than the cystic airspace. Maximum wall thickness >4 mm was associated with solid/micropapillary-predominant histology, but the estimate was exploratory because of the small outcome group. Prospective multicenter studies that include benign cystic lesions and adequate numbers of non-adenocarcinoma cancers are required before these observations can be incorporated into diagnostic decision-making.

Funding Statement

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Abbreviations

CLC, Cystic Lung Cancer; MSCT, Multi-Slice Computed Tomography; IASLC, International Association for the Study of Lung Cancer; WHO, World Health Organization; GGO, Ground-Glass Opacity; SD, Standard Deviation; CI, Confidence Interval; OR, Odds Ratio.

Data Sharing Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

This retrospective study was approved by the Ethics Committee of Renmin Hospital, Hubei University of Medicine (SY2026025). The study was performed in accordance with the Helsinki II declaration. The requirement for informed consent was waived by the Ethics Committee due to the retrospective nature of the analysis.

Consent for Publication

Not applicable. All data were anonymized, and no identifying individual details or images of recognizable faces are included in this manuscript.

Author Contributions

Co-first authors: Xiaoqin Luo and Shan Lan contributed equally to this work. All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.


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