{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:21:04Z","timestamp":1780633264720,"version":"3.54.1"},"reference-count":42,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T00:00:00Z","timestamp":1748563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Applied Basic Research Programs of Changzhou","award":["CJ20230049"],"award-info":[{"award-number":["CJ20230049"]}]},{"name":"Applied Basic Research Programs of Changzhou","award":["20230171"],"award-info":[{"award-number":["20230171"]}]},{"name":"Changzhou Sci&amp;Tech Program","award":["CJ20230049"],"award-info":[{"award-number":["CJ20230049"]}]},{"name":"Changzhou Sci&amp;Tech Program","award":["20230171"],"award-info":[{"award-number":["20230171"]}]},{"name":"First People\u2019s Hospital of Changzhou","award":["CJ20230049"],"award-info":[{"award-number":["CJ20230049"]}]},{"name":"First People\u2019s Hospital of Changzhou","award":["20230171"],"award-info":[{"award-number":["20230171"]}]},{"name":"Third Affiliated Hospital of Soochow University","award":["CJ20230049"],"award-info":[{"award-number":["CJ20230049"]}]},{"name":"Third Affiliated Hospital of Soochow University","award":["20230171"],"award-info":[{"award-number":["20230171"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Current Oncology"],"abstract":"<jats:p>Background: 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. Methods: This retrospective study analyzed 180 surgically confirmed NSCLC patients (Stages I\u2013IIIA), 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. Results: 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, p &lt; 0.05). Decision curve analysis demonstrated the enhanced clinical utility of the combined approach. Conclusions: 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.<\/jats:p>","DOI":"10.3390\/curroncol32060323","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T08:34:13Z","timestamp":1748853253000},"page":"323","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Clinical\u2013Radiomics Nomogram for the Preoperative Prediction of Aggressive Micropapillary and a Solid Pattern in Lung Adenocarcinoma"],"prefix":"10.3390","volume":"32","author":[{"given":"Xiangyu","family":"Xie","sequence":"first","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Thoracic Surgery, The First People\u2019s Hospital of Changzhou and The Third Affiliated Hospital of Soochow University, Changzhou 213000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/S0140-6736(21)00312-3","article-title":"Lung cancer","volume":"398","author":"Thai","year":"2021","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1974","DOI":"10.1515\/cclm-2022-0291","article-title":"Artificial intelligence in clinical applications for lung cancer","volume":"60","author":"Pei","year":"2022","journal-title":"Clin. 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