CT定量参数预测肺磨玻璃结节病理类型的价值OA北大核心CSTPCD

Background and objective The pathological types of lung ground glass nodules(GGNs)show great significance to the clinical treatment.This study was aimed to predict pathological types of GGNs based on computed tomog-raphy(CT)quantitative parameters.Methods 389 GGNs confirmed by postoperative pathology were selected,including 138 cases of precursor glandular lesions[atypical adenomatous hyperplasia(AAH)and adenocarcinoma in situ(AIS)],109 cases of microinvasive adenocarcinoma(MIA)and 142 cases of invasive adenocarcinoma(IAC).The morphological characteristics of nodules were evaluated subjectively by radiologist,as well as artificial intelligence(AI).Results In the subjective CT signs,the maximum diameter of nodule and the frequency of spiculation,lobulation and pleural traction increased from AAH+AIS,MIA to IAC.In the AI quantitative parameters,parameters related to size and CT value,proportion of solid component,energy and entropy increased from AAH+AIS,MIA to IAC.There was no significant difference between AI quantitative parameters and the subjective CT signs for distinguishing the pathological types of GGNs.Conclusion AI quantitative parameters were valu-able in distinguishing the pathological types of GGNs.