Kao, Chia-ChengChia-ChengKaoWang, Hu-Lin ChristinaHu-Lin ChristinaWangMONG-WEI LINTUNG-MING TSAIHSAO-HSUN HSULiao, Hsien-ChiHsien-ChiLiaoJIN-SHING CHEN2025-06-232025-06-232025-04-23https://scholars.lib.ntu.edu.tw/handle/123456789/730182Background/objectives: For thoracic surgeons, the extent of visceral pleural invasion is a crucial consideration in the surgical approach to adenocarcinoma; this invasion may influence the extent of surgical resection and predict prognosis. With advances in preoperative imaging technology, predicting visceral pleural invasion via computed tomography (CT) characteristics may be feasible. The aim of this study was to evaluate the association between CT characteristics and visceral pleural invasion in patients with surgically resected lung adenocarcinoma. Methods: Patients with lung adenocarcinoma who underwent curative lung tumor resection (n = 643) were retrospectively included in this study between January 2011 and December 2015. Basic demographic CT images were analyzed by experienced thoracic surgeons and radiologists. Postoperative pathology reports were confirmed by experienced pathologists. Univariate and multivariate analyses were performed for potential prognostic factors. Results: Potential visceral pleural invasion characteristics of preoperative CT included tumor size (cm), solid part size, pleural contact of arch distance, ground glass opacity (%), tumor shape, border type, distance from visceral pleura, depth, and invasion site. In addition, solid part size, ground glass opacity (%), consolidation to tumor ratio (%), tumor shape, border type, distance from visceral pleura, and invasion site showed statistical significance for prognosis. Conclusions: Increased precision of image interpretation may provide more predictive clues to improve the identification of visceral pleural invasion before operations. The extent of surgical resection may be more accurately determined, and systemic treatment may be administered earlier for those with poor prognostic factors.enfalsecurative lung resectionpreoperative imagingjournal article10.3390/cancers17091414403613422-s2.0-105005086393