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Due to significant variability in postoperative recurrence among early\u2010stage LUAD patients with aggressive tumors, a more effective risk stratification system is urgently needed to improve prognosis. This study developed the T1LUT system, a transformer\u2010based tool for T1N0M0 LUAD management, covering preoperative tumor invasiveness identification and postoperative recurrence risk stratification. Preoperatively, a 3D Vision Transformer (ViT) with extra learnable tokens analyzes CT images. It outperforms 3D ViT with only CLS tokens, 2D ViT, and 3D ResNet across three independent test centers (Center D: 0.896\u00a0vs. 0.892, 0.879, 0.836; Center E: 0.906\u00a0vs. 0.837, 0.837, 0.835; Center F: 0.884\u00a0vs. 0.884, 0.881, 0.861), achieving higher mean AUROC to accurately assess invasiveness and guide surgical resection extent. Postoperatively, the multimodal IAC\u2010PR model integrates CT images, reports, pathological data, and clinical\/demographic information. It stratifies invasive adenocarcinoma (IAC) patients into low\u2010, medium\u2010, or high\u2010risk groups with an AUROC of 0.807 in testing\u2014significantly better than single\/partial\u2010modal models. Validated via large\u2010scale multicenter research, this system overcomes traditional assessment limitations, offering a robust tool for precise early LUAD treatment and improved prognosis.<\/jats:p>","DOI":"10.1002\/mco2.71055","type":"journal-article","created":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T05:22:27Z","timestamp":1791782547000},"source":"Crossref","is-referenced-by-count":0,"title":["Transformer\u2010Based Preoperative Invasiveness Identification and Postoperative Recurrence Risk Stratification in Stage T1N0M0 Lung Adenocarcinoma: A Multi\u2010Center Cohort Study"],"prefix":"10.1002","volume":"7","author":[{"given":"Xueyun","family":"Tan","sequence":"first","affiliation":[{"name":"Department of Respiratory and Critical Care Medicine Hubei Province Clinical Research Center for Major Respiratory Disease Union Hospital Tongji Medical College Huazhong University of Science and Technology  Wuhan China"},{"name":"Department of Respiratory and Critical Care Medicine 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