CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma
Abstract Objectives This research aimed to examine the relationships between clinicopathological characteristics and the occurrence of Spread Through Air Spaces (STAS) in patients with stage IA lung adenocarcinoma (LUAD) and to develop a preoperative prediction model. Methods Data from 1,375 patient...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-06-01
|
| Series: | Cancer Imaging |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40644-025-00893-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850218551688822784 |
|---|---|
| author | Bin Luo Han Yang Ningbo Fan Pengfei Duan Zhesheng Wen Peng Lin |
| author_facet | Bin Luo Han Yang Ningbo Fan Pengfei Duan Zhesheng Wen Peng Lin |
| author_sort | Bin Luo |
| collection | DOAJ |
| description | Abstract Objectives This research aimed to examine the relationships between clinicopathological characteristics and the occurrence of Spread Through Air Spaces (STAS) in patients with stage IA lung adenocarcinoma (LUAD) and to develop a preoperative prediction model. Methods Data from 1,375 patients with stage IA LUAD at Sun Yat-sen University Cancer Center were analyzed. Propensity score matching (PSM) was employed to match 141 STAS-positive patients with 282 STAS-negative patients. Both univariate and multivariate logistic regression analyses were performed to determine independent variables among 16 clinicopathological and 13 CT imaging characteristics. A nomogram prediction model was developed and evaluated via receiver operating characteristic (ROC) and decision curve analyses (DCAs). Results Multivariate analysis identified several independent risk factors. Irregular nodule shape (OR = 1.817, 95% CI: 1.106–2.986, p = 0.018), irregular margin (OR = 2.050, 95% CI: 1.218–3.449, p = 0.007), lobulation (OR = 2.235, 95% CI: 1.336–3.739, p = 0.002), and vascular convergence (OR = 5.032, 95% CI: 2.050–12.349, p < 0.001) were significantly associated with an increased risk of STAS. Compared with a consolidation tumor ratio (CTR) = 0% (reference), a CTR of 75–100% (OR = 7.086, 95% CI: 2.542–19.750, p < 0.001) and a CTR = 100% (OR = 11.502, 95% CI: 4.752–27.840, p < 0.001) were significantly associated with an increased risk of STAS. The nomogram was developed and internally validated, demonstrating good predictive accuracy (AUC = 0.812, 95% CI: 0.761–0.863) and favorable clinical utility, with a sensitivity of 69.5% and a specificity of 80.2%. Conclusion The nomogram reliably predicts STAS preoperatively and may assist in guiding surgical decision-making. |
| format | Article |
| id | doaj-art-bf803baa842d4b8289649ce465bea5c5 |
| institution | OA Journals |
| issn | 1470-7330 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Cancer Imaging |
| spelling | doaj-art-bf803baa842d4b8289649ce465bea5c52025-08-20T02:07:41ZengBMCCancer Imaging1470-73302025-06-0125111410.1186/s40644-025-00893-xCT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinomaBin Luo0Han Yang1Ningbo Fan2Pengfei Duan3Zhesheng Wen4Peng Lin5Department of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterDepartment of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer CenterAbstract Objectives This research aimed to examine the relationships between clinicopathological characteristics and the occurrence of Spread Through Air Spaces (STAS) in patients with stage IA lung adenocarcinoma (LUAD) and to develop a preoperative prediction model. Methods Data from 1,375 patients with stage IA LUAD at Sun Yat-sen University Cancer Center were analyzed. Propensity score matching (PSM) was employed to match 141 STAS-positive patients with 282 STAS-negative patients. Both univariate and multivariate logistic regression analyses were performed to determine independent variables among 16 clinicopathological and 13 CT imaging characteristics. A nomogram prediction model was developed and evaluated via receiver operating characteristic (ROC) and decision curve analyses (DCAs). Results Multivariate analysis identified several independent risk factors. Irregular nodule shape (OR = 1.817, 95% CI: 1.106–2.986, p = 0.018), irregular margin (OR = 2.050, 95% CI: 1.218–3.449, p = 0.007), lobulation (OR = 2.235, 95% CI: 1.336–3.739, p = 0.002), and vascular convergence (OR = 5.032, 95% CI: 2.050–12.349, p < 0.001) were significantly associated with an increased risk of STAS. Compared with a consolidation tumor ratio (CTR) = 0% (reference), a CTR of 75–100% (OR = 7.086, 95% CI: 2.542–19.750, p < 0.001) and a CTR = 100% (OR = 11.502, 95% CI: 4.752–27.840, p < 0.001) were significantly associated with an increased risk of STAS. The nomogram was developed and internally validated, demonstrating good predictive accuracy (AUC = 0.812, 95% CI: 0.761–0.863) and favorable clinical utility, with a sensitivity of 69.5% and a specificity of 80.2%. Conclusion The nomogram reliably predicts STAS preoperatively and may assist in guiding surgical decision-making.https://doi.org/10.1186/s40644-025-00893-xLung adenocarcinomaSpread through air spacesClinicopathologic featuresCT featuresNomogram |
| spellingShingle | Bin Luo Han Yang Ningbo Fan Pengfei Duan Zhesheng Wen Peng Lin CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma Cancer Imaging Lung adenocarcinoma Spread through air spaces Clinicopathologic features CT features Nomogram |
| title | CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma |
| title_full | CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma |
| title_fullStr | CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma |
| title_full_unstemmed | CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma |
| title_short | CT feature-based nomogram for predicting tumor spread through air spaces in stage IA lung adenocarcinoma |
| title_sort | ct feature based nomogram for predicting tumor spread through air spaces in stage ia lung adenocarcinoma |
| topic | Lung adenocarcinoma Spread through air spaces Clinicopathologic features CT features Nomogram |
| url | https://doi.org/10.1186/s40644-025-00893-x |
| work_keys_str_mv | AT binluo ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma AT hanyang ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma AT ningbofan ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma AT pengfeiduan ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma AT zheshengwen ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma AT penglin ctfeaturebasednomogramforpredictingtumorspreadthroughairspacesinstageialungadenocarcinoma |