Identification of the optimal threshold for predicting the infiltration degree of T1-stage lung adenocarcinoma using solid component volume and three-dimensional consolidation-to-tumor ratio in threshold segmentation
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Predicting the invasiveness of pulmonary nodules when early-stage lung cancer is suspected is a clinical challenge. This study aimed to determine the optimal computed tomography (CT) threshold values for predicting the invasiveness of T1-stage lung adenocarcinoma. This was achieved using the solid component volume and three-dimensional consolidation-to-tumor ratio (3D CTR) via threshold segmentation. Methods: A retrospective study was conducted, involving 1,056 patients with 1,179 pulmonary nodules verified by postoperative pathology. These cases were sourced from two different centers. The patients were divided into two groups: the pre-invasive group, comprising atypical adenomatous hyperplasia (AAH) and adenocarcinoma in situ (AIS), and the invasive group, including minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC). Seven different CT threshold settings [-550, -450, -350, -250, -150, -50, 0 Hounsfield unit (HU)] were used, and the solid component volume was calculated; 3D CTR was determined using the threshold segmentation method and the differences between the two groups were analyzed. We plotted the receiver operating characteristic (ROC) curves to evaluate the effectiveness of predicting the invasiveness of T1-stage lung adenocarcinoma. Based on the analysis of the ROC curves, the optimal threshold was determined, and the corresponding optimal cut-off value was calculated. Results: , and 10.85% for 3D CTR. Conclusions: or a 3D CTR greater than 10.85% indicated a higher likelihood of MIA or IAC.
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4411901879