A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma
<b>Background:</b> A micropapillary pattern (MP) and solid pattern (SP) in lung adenocarcinoma (LUAD), a major subtype of non-small-cell lung cancer (NSCLC), are associated with a poor prognosis and necessitate accurate preoperative identification. This study aimed to develop and validat...
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2025-05-01
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| Series: | Current Oncology |
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| author | Xiangyu Xie Lei Chen Kun Li Liang Shi Lei Zhang Liang Zheng |
| author_facet | Xiangyu Xie Lei Chen Kun Li Liang Shi Lei Zhang Liang Zheng |
| author_sort | Xiangyu Xie |
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| description | <b>Background:</b> A micropapillary pattern (MP) and solid pattern (SP) in lung adenocarcinoma (LUAD), a major subtype of non-small-cell lung cancer (NSCLC), are associated with a poor prognosis and necessitate accurate preoperative identification. This study aimed to develop and validate a predictive model combining clinical and radiomics features for differentiating a high-risk MP/SP in LUAD. <b>Methods:</b> This retrospective study analyzed 180 surgically confirmed NSCLC patients (Stages I–IIIA), randomly divided into training (70%, n = 126) and validation (30%, n = 54) cohorts. Three prediction models were constructed: (1) a clinical model based on independent clinical and CT morphological features (e.g., nodule size, lobulation, spiculation, pleural indentation, and vascular abnormalities), (2) a radiomics model utilizing LASSO-selected features extracted using 3D Slicer, and (3) a comprehensive model integrating both clinical and radiomics data. <b>Results:</b> The clinical model yielded AUCs of 0.7975 (training) and 0.8462 (validation). The radiomics model showed superior performance with AUCs of 0.8896 and 0.8901, respectively. The comprehensive model achieved the highest diagnostic accuracy, with training and validation AUCs of 0.9186 and 0.9396, respectively (DeLong test, <i>p</i> < 0.05). Decision curve analysis demonstrated the enhanced clinical utility of the combined approach. <b>Conclusions:</b> Integrating clinical and radiomics features significantly improves the preoperative identification of aggressive NSCLC patterns. The comprehensive model offers a promising tool for guiding surgical and adjuvant therapy decisions. |
| format | Article |
| id | doaj-art-e53eac700b084daaab605cfff7bb8640 |
| institution | OA Journals |
| issn | 1198-0052 1718-7729 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Current Oncology |
| spelling | doaj-art-e53eac700b084daaab605cfff7bb86402025-08-20T02:24:25ZengMDPI AGCurrent Oncology1198-00521718-77292025-05-0132632310.3390/curroncol32060323A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung AdenocarcinomaXiangyu Xie0Lei Chen1Kun Li2Liang Shi3Lei Zhang4Liang Zheng5Department of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, ChinaDepartment of Thoracic Surgery, The First People’s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China<b>Background:</b> A micropapillary pattern (MP) and solid pattern (SP) in lung adenocarcinoma (LUAD), a major subtype of non-small-cell lung cancer (NSCLC), are associated with a poor prognosis and necessitate accurate preoperative identification. This study aimed to develop and validate a predictive model combining clinical and radiomics features for differentiating a high-risk MP/SP in LUAD. <b>Methods:</b> This retrospective study analyzed 180 surgically confirmed NSCLC patients (Stages I–IIIA), randomly divided into training (70%, n = 126) and validation (30%, n = 54) cohorts. Three prediction models were constructed: (1) a clinical model based on independent clinical and CT morphological features (e.g., nodule size, lobulation, spiculation, pleural indentation, and vascular abnormalities), (2) a radiomics model utilizing LASSO-selected features extracted using 3D Slicer, and (3) a comprehensive model integrating both clinical and radiomics data. <b>Results:</b> The clinical model yielded AUCs of 0.7975 (training) and 0.8462 (validation). The radiomics model showed superior performance with AUCs of 0.8896 and 0.8901, respectively. The comprehensive model achieved the highest diagnostic accuracy, with training and validation AUCs of 0.9186 and 0.9396, respectively (DeLong test, <i>p</i> < 0.05). Decision curve analysis demonstrated the enhanced clinical utility of the combined approach. <b>Conclusions:</b> Integrating clinical and radiomics features significantly improves the preoperative identification of aggressive NSCLC patterns. The comprehensive model offers a promising tool for guiding surgical and adjuvant therapy decisions.https://www.mdpi.com/1718-7729/32/6/323lung adenocarcinomaradiomicsclinical independent factorsmicropapillary and solid patterns |
| spellingShingle | Xiangyu Xie Lei Chen Kun Li Liang Shi Lei Zhang Liang Zheng A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma Current Oncology lung adenocarcinoma radiomics clinical independent factors micropapillary and solid patterns |
| title | A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma |
| title_full | A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma |
| title_fullStr | A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma |
| title_full_unstemmed | A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma |
| title_short | A Clinical–Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma |
| title_sort | clinical radiomics nomogram for the preoperative prediction of aggressive micropapillary and a solid pattern in lung adenocarcinoma |
| topic | lung adenocarcinoma radiomics clinical independent factors micropapillary and solid patterns |
| url | https://www.mdpi.com/1718-7729/32/6/323 |
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