CHEST RADIOLOGY / ORIGINAL PAPER
Figure from article: Analysis of risk factors...
 
KEYWORDS
TOPICS
ABSTRACT
Purpose:
This study aims to compare the clinical, imaging, and pathological characteristics of benign and malignant solitary pulmonary cystic nodules, and identify key indicators associated with malignant risk and invasion depth, assisting clinicians in early detection and assessment of tumour invasiveness.

Material and methods:
This study conducted a retrospective analysis of patients with pulmonary cystic nodules who underwent surgical treatment, and it classified them into benign and malignant groups based on postoperative pathological results. We collected patients’ clinical data, serum biomarkers, and CT imaging data and compared them using univariate analysis of variance. We included statistically significant indicators in a multivariate regression model to identify independent predictive factors for early malignant transformation of cystic lung cancer. Additionally, we collected the pathological types and tissue infiltration grades of the malignant group and further explored the relationship between imaging features and pathological grading by comparing the imaging characteristics corresponding to different pathological infiltration degrees, and visualised the results using a forest plot.

Results:
Following multifactorial Cox analysis age, CA199, homogeneity of cyst wall thickness, cystic wall finish, number of cystic cavities, ground glass sign, and the nodule’s relationship to surrounding tissues (burr, pleural indentation sign) had a significant effect on the evolution of cystic malignant nodules. Finally, in the malignant nodule group, the presence or absence of the ground glass sign was statistically significant concerning the different pathologic grades.

Conclusions:
Our multivariate predictive study indicates that certain imaging features of pulmonary cystic nodules may suggest malignant progression and are associated with different levels of pathological invasion.
REFERENCES (30)
1.
Zhou J, Xu X, Liu J, Feng L, Yu J, Chen D. Global burden of lung cancer in 2022 and projections to 2050: Incidence and mortality estimates from GLOBOCAN. Cancer Epidemiol 2024; 93: 102693. DOI: 10.1016/j.canep.2024.102693.
 
2.
Sheard S, Moser J, Sayer C, Stefanidis K, Devaraj A, Vlahos I. Lung cancers associated with cystic airspaces: underrecognized features of early disease. Radiographics 2018; 38: 704-717.
 
3.
Byrne D, English JC, Atkar-Khattra S, Lam S, Yee J, Myers R, et al. Cystic primary lung cancer: evolution of computed tomography imaging morphology over time. J Thorac Imaging 2021; 36: 373-381.
 
4.
Farooqi AO, Cham M, Zhang L, Beasley MB, Austin JHM, Miller A, et al. Lung cancer associated with cystic airspaces. AJR Am J Roentgenol 2012; 199: 781-786.
 
5.
Mendoza DP, Heeger A, Mino-Kenudson M, Lanuti M, Shepard JO, Sequist LV, et al. Clinicopathologic and longitudinal imaging features of lung cancer associated with cystic airspaces: a systematic review and meta-analysis. AJR Am J Roentgenol 2021; 216: 318-329.
 
6.
Wang K, Leng X, Yi H, Zhang G, Hu Z, Mao Y. Lung cancer associated with cystic airspaces: current insights into diagnosis, pathophy­siology, and treatment strategies, Cancers (Basel) 2024; 16: 3930. DOI: 10.3390/cancers16233930.
 
7.
Christensen J, Prosper AE, Wu CC, Chung J, Lee E, Elicker B, et al. ACR Lung-RADS v2022: assessment categories and management recommendations. Chest 2024; 165: 738-753.
 
8.
An SH, You S, Kim YN, Sun JS. Atypical pulmonary cysts in lung cancer screening: prevalence, outcomes, and clinical implications, Eur Radiol 2025; 35: 4873-4881.
 
9.
Zhao B, Dercle L, Yang H, Riely GJ, Kris MG, Schwartz LH. Annotated test-retest dataset of lung cancer CT scan images reconstructed at multiple imaging parameters. Sci Data 2024; 11: 1259. DOI: 10.1038/s41597-024-04085-3.
 
10.
Nair A, Bartlett EC, Walsh SLF, Wells AU, Navani N, Hardavella G, et al. Variable radiological lung nodule evaluation leads to divergent management recommendations. Eur Respir J 2018; 52: 1801359. DOI: 10.1183/13993003.01359-2018.
 
11.
Bankier AA, MacMahon H, Colby T, Gevenois PA, Goo JM, Leung ANC, et al. Fleischner Society: Glossary of terms for thoracic imaging. Radiology 2024; 310: e232558. DOI: 10.1148/radiol.232558.
 
12.
Wong LY, Choudhary S, Kapula N, Lin M, Elliott IA, Guenthart BA, et al. Barriers to completing low dose computed tomography scan for lung cancer screening. Clin Lung Cancer 2024; 25: 424-430.
 
13.
Scholten ET, Horeweg N, de Koning HJ, Vliegenthart R, Oudkerk M, Mali WPTM, et al. Computed tomographic characteristics of interval and post-screen carcinomas in lung cancer screening. Eur Radiol 2015; 25: 81-88.
 
14.
Park MD, Le Berichel J, Hamon P, Wilk CM, Belabed M, Yatim N, et al. Hematopoietic aging promotes cancer by fueling IL-1-driven emergency myelopoiesis. Science 2024; 386: eadn0327. DOI: 10.1126/science.adn0327.
 
15.
Yang Y, Li X, Duan Y, Zhao J, Huang Q, Zhou C, et al. Risk factors for malignant solid pulmonary nodules: a meta-analysis. BMC Cancer 2025; 25: 312.
 
16.
Carter BD, Abnet CC, Feskanich D, Freedman ND, Hartge P, Lewis CE, et al. Smoking and mortality – beyond established causes. N Engl J Med 2015; 372: 631-340.
 
17.
Zekeridou A, Majed M, Heliopoulos I, Lennon VA. Paraneoplastic autoimmunity and small-cell lung cancer: Neurological and serological accompaniments, Thorac Cancer 2019; 10: 1001-1004.
 
18.
Shin J, Song SY, Ahn HS, An BC, Choi YD, Yang EG, et al. Integrative analysis for the discovery of lung cancer serological markers and validation by MRM-MS. PLoS One 2017; 12: e0183896. DOI: 10.1371/journal.pone.0183896.
 
19.
Lin ZQ, Ma C, Cao WZ, Ning Z, Tan G. Prognostic significance of NLR, PLR, LMR and tumor infiltrating T lymphocytes in patients undergoing surgical resection for hilar cholangiocarcinoma. Front Oncol 2022; 12: 908907. DOI: 10.3389/fonc.2022.908907.
 
20.
Tan Y, Gao J, Wu C, Zhao S, Yu J, Zhu R, et al. CT characteristics and pathologic basis of solitary cystic lung cancer. Radiology 2019; 291: 495-501.
 
21.
Lee HJ, Mazzone P, Feller-Kopman D, Yarmus L, Hogarth K, Lofaro LR, et al. Impact of the percepta genomic classifier on clinical management decisions in a multicenter prospective study. Chest 2021; 151: 401-412.
 
22.
Si MJ, Tao XF, Du GY, Cai LL, Han HX, Liang XZ, et al. Thin-section computed tomography-histopathologic comparisons of pulmonary focal interstitial fibrosis, atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma with pure ground-glass opacity. Eur J Radiol 2016; 10: 1708-1715.
 
23.
Hsu JS, Han IT, Tsai TH, Lin SF, Jaw TS, Liu GC, et al. Pleural tags on CT scans to predict visceral pleural invasion of non-small cell lung cancer that does not abut the pleura. Radiology 2016; 279: 590-596.
 
24.
Ikehara M, Saito H, Kondo T, Murakami S, Ito H, Tsuboi M, et al. Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: prognostic factors from CT findings. Eur J Radiol 2012; 81: 189-194.
 
25.
Jung W, Cho S, Yum S, Chung JH, Lee KW, Kim K, et al. Correction to: stepwise disease progression model of subsolid lung adenocarcinoma with cystic airspaces Ann Surg Oncol 2020; 27 (Suppl. 3): 981-982.
 
26.
Xu J, Zhang Y, Li M, Shao Z, Dong Y, Li Q, et al. A single-cell charac­terised signature integrating heterogeneity and microenvironment of lung adenocarcinoma for prognostic stratification. EBioMedicine 2024; 102: 105092. DOI: 10.1016/j.ebiom.2024.105092.
 
27.
Vanguri RS, Luo J, Aukerman AT, Egger JV, Fong CJ, Horvat N, et al. Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer. Nat Cancer 2022; 3: 1151-1164.
 
28.
Wang B, Hamal P, Sun K, Bhuva MS, Yang Y, Ai Z, et al. Clinical value and pathologic basis of cystic airspace within subsolid nodules confirmed as lung adenocarcinomas by surgery. Clin Lung Cancer 2021; 22: e881-e888. DOI: 10.1016/j.cllc.2021.05.005.
 
29.
Yang JJ, Wen W, Zahed H, Zheng W, Lan Q, Abe SK, et al. Lung cancer risk prediction models for asian ever-smokers. J Thorac Oncol 2024; 19: 451-464.
 
30.
Yao Y, Yang Y, Hu Q, Xie X, Jiang W, Liu C, et al. A nomogram combining CT-based radiomic features with clinical features for the differentiation of benign and malignant cystic pulmonary nodules. J Cardiothorac Surg 2024; 19: 392.
 
Journals System - logo
Scroll to top