A Radiological-Radiomics model for differentiation between minimally invasive adenocarcinoma and invasive adenocarcinoma less than or equal to 3 cm: A two-center retrospective study

医学 接收机工作特性 腺癌 无线电技术 逻辑回归 曲线下面积 放射性武器 放射科 核医学 回顾性队列研究 病理 内科学 癌症
作者
Dong Hao,Yuzhen Xi,Kai Li,Lei Chen,Li Yang,Xianpan Pan,Xingwei Zhang,Xiaodan Ye,Zhongxiang Ding
出处
期刊:European Journal of Radiology [Elsevier BV]
卷期号:176: 111532-111532
标识
DOI:10.1016/j.ejrad.2024.111532
摘要

ObjectiveTo develop a Radiological-Radiomics (R-R) combined model for differentiation between minimal invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IA) of lung adenocarcinoma (LUAD) and evaluate its predictive performance.MethodsThe clinical, pathological, and imaging data of a total of 509 patients (522 lesions) with LUAD diagnosed by surgical pathology from 2 medical centres were retrospectively collected, with 392 patients (402 lesions) from center 1 trained and validated using a five-fold cross-validation method, and 117 patients (120 lesions) from center 2 serving as an independent external test set. The least absolute shrinkage and selection operator (LASSO) method was utilized to filter features. Logistic regression was used to construct three models for predicting IA, namely, Radiological model, Radiomics model, and R-R model. Also, receiver operating curve curves (ROCs) were plotted, generating corresponding area under the curve (AUC), sensitivity, specificity, and accuracy.ResultsThe R-R model for IA prediction achieved an AUC of 0.918 (95 % CI: 0.889–0.947), a sensitivity of 80.3 %, a specificity of 88.2 %, and an accuracy of 82.1 % in the training set. In the validation set, this model exhibited an AUC of 0.906 (95 % CI: 0.842–0.970), a sensitivity of 79.9 %, a specificity of 88.1 %, and an accuracy of 81.8 %. In the external test set, the AUC was 0.894 (95 % CI: 0.824–0.964), a sensitivity of 84.8 %, a specificity of 78.6 %, and an accuracy of 83.3 %.ConclusionThe R-R model showed excellent diagnostic performance in differentiating MIA and IA, which can provide a certain reference for clinical diagnosis and surgical treatment plans.
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