Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography
-
Published:2024-04-10
Issue:4
Volume:150
Page:
-
ISSN:1432-1335
-
Container-title:Journal of Cancer Research and Clinical Oncology
-
language:en
-
Short-container-title:J Cancer Res Clin Oncol
Author:
Wang Yun,Lyu Deng,Cheng Chao,Zhou Taohu,Tu Wenting,Xiao Yi,Zuo Changjing,Fan Li,Liu Shiyuan
Abstract
Abstract
Purpose
This study aims to assess the predictive value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) radiological features and the maximum standardized uptake value (SUVmax) in determining the presence of spread through air spaces (STAS) in clinical-stage IA non-small cell lung cancer (NSCLC).
Methods
A retrospective analysis was conducted on 180 cases of NSCLC with postoperative pathological assessment of STAS status, spanning from September 2019 to September 2023. Of these, 116 cases from hospital one comprised the training set, while 64 cases from hospital two formed the testing set. The clinical information, tumor SUVmax, and 13 related CT features were analyzed. Subgroup analysis was carried out based on tumor density type. In the training set, univariable and multivariable logistic regression analyses were employed to identify the most significant variables. A multivariable logistic regression model was constructed and the corresponding nomogram was developed to predict STAS in NSCLC, and its diagnostic efficacy was evaluated in the testing set.
Results
SUVmax, consolidation-to-tumor ratio (CTR), and lobulation sign emerged as the best combination of variables for predicting STAS in NSCLC. Among these, SUVmax and CTR were identified as independent predictors for STAS prediction. The constructed prediction model demonstrated area under the curve (AUC) values of 0.796 and 0.821 in the training and testing sets, respectively. Subgroup analysis revealed a 2.69 times higher STAS-positive rate in solid nodules compared to part-solid nodules. SUVmax was an independent predictor for predicting STAS in solid nodular NSCLC, while CTR and an emphysema background were independent predictors for STAS in part-solid nodular NSCLC.
Conclusion
Our nomogram based on preoperative 18F-FDG PET/CT radiological features and SUVmax effectively predicts STAS status in clinical-stage IA NSCLC. Furthermore, our study highlights that metabolic parameters and CT variables associated with STAS differ between solid and part-solid nodular NSCLC.
Funder
National Natural Science Foundation of China Shanghai Sailing Program National Key R&D Program of China Clinical Innovative Project of Shanghai Changzheng Hospital Program of Science and Technology Commission of Shanghai Municipality Key Program of National Natural Science Foundation of China Shanghai Science and Technology Innovation Action Plan Program
Publisher
Springer Science and Business Media LLC
Reference34 articles.
1. Aly RG, Rekhtman N, Li X, Takahashi Y, Eguchi T, Tan KS, Rudin CM, Adusumilli PS, Travis WD (2019) Spread through air spaces (STAS) is prognostic in atypical carcinoid, large cell neuroendocrine carcinoma, and small cell carcinoma of the lung. J Thorac Oncol 14(9):1583–1593. https://doi.org/10.1016/j.jtho.2019.05.009 2. Bains S, Eguchi T, Warth A, Yeh YC, Nitadori JI, Woo KM, Chou TY, Dienemann H, Muley T, Nakajima J, Shinozaki-Ushiku A, Wu YC, Lu S, Kadota K, Jones DR, Travis WD, Tan KS, Adusumilli PS (2019) Procedure-specific risk prediction for recurrence in patients undergoing lobectomy or sublobar resection for small (≤2 cm) lung adenocarcinoma: an international cohort analysis. J Thorac Oncol 14(1):72–86. https://doi.org/10.1016/j.jtho.2018.09.008 3. Chen Y, Jiang C, Kang W, Gong J, Luo D, You S, Cheng Z, Luo Y, Wu K (2022) Development and validation of a CT-based nomogram to predict spread through air space (STAS) in peripheral stage IA lung adenocarcinoma. Jpn J Radiol 40(6):586–594. https://doi.org/10.1007/s11604-021-01240-3 4. de Geus-Oei LF, van Krieken JH, Aliredjo RP, Krabbe PF, Frielink C, Verhagen AF, Boerman OC, Oyen WJ (2007) Biological correlates of FDG uptake in non-small cell lung cancer. Lung Cancer 55(1):79–87. https://doi.org/10.1016/j.lungcan.2006.08.018 5. Dercle L, Fronheiser M, Lu L, Du S, Hayes W, Leung DK, Roy A, Wilkerson J, Guo P, Fojo AT, Schwartz LH, Zhao B (2020) Identification of non-small cell lung cancer sensitive to systemic cancer therapies using radiomics. Clin Cancer Res 26(9):2151–2162. https://doi.org/10.1158/1078-0432.CCR-19-2942
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|