CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study
Purpose: The aim of this study was to explore and develop a preoperative and noninvasive model for predicting spread through air spaces (STAS) status in lung adenocarcinoma (LUAD) with diameter ≤ 3 cm. Methods: This multicenter retrospective study included 640 LUAD patients. Center I included 525 pa...
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Elsevier
2025-06-01
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| Series: | European Journal of Radiology Open |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352047724000856 |
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| author | Yangfan Su Junli Tao Xiaosong Lan Changyu Liang Xuemei Huang Jiuquan Zhang Kai Li Lihua Chen |
| author_facet | Yangfan Su Junli Tao Xiaosong Lan Changyu Liang Xuemei Huang Jiuquan Zhang Kai Li Lihua Chen |
| author_sort | Yangfan Su |
| collection | DOAJ |
| description | Purpose: The aim of this study was to explore and develop a preoperative and noninvasive model for predicting spread through air spaces (STAS) status in lung adenocarcinoma (LUAD) with diameter ≤ 3 cm. Methods: This multicenter retrospective study included 640 LUAD patients. Center I included 525 patients (368 in the training cohort and 157 in the validation cohort); center II included 115 patients (the test cohort). We extracted radiomics features from the intratumor, extended tumor and peritumor regions. Multivariate logistic regression and boruta algorithm were used to select clinical independent risk factors and radiomics features, respectively. We developed a clinical model and four radiomics models (the intratumor model, extended tumor model, peritumor model and fusion model). A nomogram based on prediction probability value of the optimal radiomics model and clinical independent risk factors was developed to predict STAS status. Results: Maximum diameter and nodule type were clinical independent risk factors. The extended tumor model achieved satisfactory STAS status discrimination performance with the AUC of 0.74, 0.71 and 0.80 in the three cohorts, respectively, performed better than other radiomics models. The integrated discrimination improvement value revealed that the nomogram outperformed compared to the clinical model with the value of 12 %. Patients with high nomogram score (≥ 77.31) will be identified as STAS-positive. Conclusions: Peritumoral information is significant to predict STAS status. The nomogram based on the extended tumor model and clinical independent risk factors provided good preoperative prediction of STAS status in LUAD with diameter ≤ 3 cm, aiding surgical decision-making. |
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| id | doaj-art-07b60f11d68b4b2ab3cd40e8e75d460d |
| institution | Kabale University |
| issn | 2352-0477 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Elsevier |
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| series | European Journal of Radiology Open |
| spelling | doaj-art-07b60f11d68b4b2ab3cd40e8e75d460d2025-01-03T04:08:45ZengElsevierEuropean Journal of Radiology Open2352-04772025-06-0114100630CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter studyYangfan Su0Junli Tao1Xiaosong Lan2Changyu Liang3Xuemei Huang4Jiuquan Zhang5Kai Li6Lihua Chen7Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, ChinaDepartment of Radiology, The First Affiliated Hospital of Guangxi Medical University, No. 6 Shuangyong road, Qingxiu district, Nanning, Guangxi Zhuang Autonomous Region 530021, China; Corresponding author.Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China; Correspondence to: Department of Radiology, Chongqing University Cancer Hospital, No. 181 Hanyu road, Shapingba district, Chongqing 400030, China.Purpose: The aim of this study was to explore and develop a preoperative and noninvasive model for predicting spread through air spaces (STAS) status in lung adenocarcinoma (LUAD) with diameter ≤ 3 cm. Methods: This multicenter retrospective study included 640 LUAD patients. Center I included 525 patients (368 in the training cohort and 157 in the validation cohort); center II included 115 patients (the test cohort). We extracted radiomics features from the intratumor, extended tumor and peritumor regions. Multivariate logistic regression and boruta algorithm were used to select clinical independent risk factors and radiomics features, respectively. We developed a clinical model and four radiomics models (the intratumor model, extended tumor model, peritumor model and fusion model). A nomogram based on prediction probability value of the optimal radiomics model and clinical independent risk factors was developed to predict STAS status. Results: Maximum diameter and nodule type were clinical independent risk factors. The extended tumor model achieved satisfactory STAS status discrimination performance with the AUC of 0.74, 0.71 and 0.80 in the three cohorts, respectively, performed better than other radiomics models. The integrated discrimination improvement value revealed that the nomogram outperformed compared to the clinical model with the value of 12 %. Patients with high nomogram score (≥ 77.31) will be identified as STAS-positive. Conclusions: Peritumoral information is significant to predict STAS status. The nomogram based on the extended tumor model and clinical independent risk factors provided good preoperative prediction of STAS status in LUAD with diameter ≤ 3 cm, aiding surgical decision-making.http://www.sciencedirect.com/science/article/pii/S2352047724000856LungAdenocarcinomaNeoplasm invasivenessRadiomicsNomograms |
| spellingShingle | Yangfan Su Junli Tao Xiaosong Lan Changyu Liang Xuemei Huang Jiuquan Zhang Kai Li Lihua Chen CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study European Journal of Radiology Open Lung Adenocarcinoma Neoplasm invasiveness Radiomics Nomograms |
| title | CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study |
| title_full | CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study |
| title_fullStr | CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study |
| title_full_unstemmed | CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study |
| title_short | CT-based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm: A multicenter study |
| title_sort | ct based intratumoral and peritumoral radiomics nomogram to predict spread through air spaces in lung adenocarcinoma with diameter ≤ 3 cm a multicenter study |
| topic | Lung Adenocarcinoma Neoplasm invasiveness Radiomics Nomograms |
| url | http://www.sciencedirect.com/science/article/pii/S2352047724000856 |
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