Automated 3D segmentation of the aorta and pulmonary artery for predicting outcomes after thoracoscopic lobectomy in lung cancer patients

Lee, Hsin-YingHsin-YingLeeChung, Yu-JungYu-JungChungWang, Hao-JenHao-JenWangXU-HENG CHIANGChen, Li-WeiLi-WeiChenLin, Yan-TingYan-TingLinLee, Yi-ChiehYi-ChiehLeeHSAO-HSUN HSUYEUN-CHUNG CHANGCHUNG-MING CHENMONG-WEI LINJIN-SHING CHEN2023-02-132023-02-1320222234-943Xhttps://scholars.lib.ntu.edu.tw/handle/123456789/627902Preoperative two-dimensional manual measurement of pulmonary artery diameter in a single-cut axial view computed tomography (CT) image is a commonly used non-invasive prediction method for pulmonary hypertension. However, the accuracy may be unreliable. Thus, this study aimed to evaluate the correlation of short-term surgical outcomes and pulmonary artery/aorta (PA/Ao) diameter ratio measured by automated three-dimensional (3D) segmentation in lung cancer patients who underwent thoracoscopic lobectomy.enaorta; computed tomography; lobectomy; lung cancer; pulmonary artery; pulmonary hypertension; segmentation[SDGs]SDG3Automated 3D segmentation of the aorta and pulmonary artery for predicting outcomes after thoracoscopic lobectomy in lung cancer patientsjournal article10.3389/fonc.2022.1027036363871802-s2.0-85141839900WOS:000883667900001https://api.elsevier.com/content/abstract/scopus_id/85141839900