Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs

医学 神经组阅片室 接收机工作特性 阶段(地层学) 放射科 介入放射学 切断 曲线下面积 肺癌 医学诊断 核医学 内科学 神经学 古生物学 物理 精神科 生物 量子力学
作者
Hyewon Choi,Hyungjin Kim,Wonju Hong,Jongsoo Park,Eui Jin Hwang,Chang Min Park,Young Tae Kim,Jin Mo Goo
出处
期刊:European Radiology [Springer Science+Business Media]
卷期号:31 (5): 2866-2876 被引量:32
标识
DOI:10.1007/s00330-020-07431-2
摘要

To develop and validate a preoperative CT-based deep learning model for the prediction of visceral pleural invasion (VPI) in early-stage lung cancer. In this retrospective study, dataset 1 (for training, tuning, and internal validation) included 676 patients with clinical stage IA lung adenocarcinomas resected between 2009 and 2015. Dataset 2 (for temporal validation) included 141 patients with clinical stage I adenocarcinomas resected between 2017 and 2018. A CT-based deep learning model was developed for the prediction of VPI and validated in terms of discrimination and calibration. An observer performance study and a multivariable regression analysis were performed. The area under the receiver operating characteristic curve (AUC) of the model was 0.75 (95% CI, 0.67–0.84), which was comparable to those of board-certified radiologists (AUC, 0.73–0.79; all p > 0.05). The model had a higher standardized partial AUC for a specificity range of 90 to 100% than the radiologists (all p   0.05), and its output was an independent predictor for VPI (adjusted odds ratio, 1.07; 95% CI, 1.03–1.11; p < 0.001). The deep learning model demonstrated a radiologist-level performance. The model could achieve either highly sensitive or highly specific diagnoses depending on clinical needs. • The preoperative CT-based deep learning model demonstrated an expert-level diagnostic performance for the presence of visceral pleural invasion in early-stage lung cancer. • Radiologists had a tendency toward highly sensitive, but not specific diagnoses for the visceral pleural invasion.
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