Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
Noninvasive prediction of EGFR gene mutation in lung adenocarcinoma using multiparametric CT perfusion imaging
By Chen C, Liu X, Xie Q and 5 others.
Abstract
Objectives
Determination of epidermal growth factor receptor (EGFR) gene mutation status is essential for molecular targeted therapy in patients with lung adenocarcinoma (LUAD). Currently, tumor tissue for genetic testing is commonly obtained through invasive procedures such as surgery or needle biopsy. This study aims to explore the potential associations between multiple quantitative parameters derived from computed tomography perfusion imaging (CTPI) and EGFR gene mutations in patients with LUAD, and to provide preliminary evidence for the noninvasive prediction of EGFR mutation status in LUAD.
Methods
Patients with LUAD pathologically confirmed by surgery or needle biopsy at The Third Xiangya Hospital, Central South University, were enrolled. All patients underwent pulmonary CTPI within 1 week before surgery and subsequently underwent EGFR gene testing. According to the EGFR gene testing results, the patients were divided into an EGFR-mutant group and an EGFR-wild-type group. Differences in CTPI-derived quantitative parameters between the 2 groups were statistically analyzed. Logistic regression analysis was performed to identify independent predictors of EGFR mutation and to construct a combined prediction model. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to evaluate the predictive performance of each independent predictor and the combined model.