Abstract

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Title:: Predictive value of consolidation/tumor ratio at different CT thresholds for invasiveness in small lung cancer

Author(s):: NIU Shuguo1; ZHOU Fuxing1; YAN Kesong2; ZHAO Runsheng1; LIU Binbin3; CHAI Wenxiao2; 1. Department of Radiology, Wuwei Hospital of Traditional Chinese Medicine, Wuwei 733000, China 2. Department of Tumor Intervention, Gansu Provincial Hospital, Lanzhou 730000, China 3. Department of Pathology, Wuwei Hospital of Traditional Chinese Medicine, Wuwei 733000, China

Keywords:: Keywords: lung nodule lung cancer CT threshold consolidation/tumor ratio artificial intelligence

Abstract:: Abstract: Objective To compare the accuracy of consolidation/tumor ratio (CTR) measured at different CT thresholds for the prediction of invasiveness in small lung cancer with diameter ≤ 2 cm using artificial intelligence-assisted measurements, and to explore the CTR thresholds and the corresponding CT thresholds for predicting lung cancer invasiveness. Methods Clinical data from 59 lung cancer patients (78 lung nodules in total) treated at Wuwei Hospital of Traditional Chinese Medicine from January 2021 to May 2023 were collected to analyze the prediction efficacy of CTR on invasiveness in small lung cancer with diameter ≤ 2 cm measured at CT thresholds of -400, -350, -300, -250, -200, -150 HU. ROC curves were plotted to determine the optimal critical value for invasiveness prediction, followed by the corresponding CT threshold. Results The highest diagnostic efficacy for the invasiveness of lung nodules was achieved at a CT threshold of -250 HU, with an area under the curve of 0.931, sensitivity of 77.5%, specificity of 100%, and an optimal CTR threshold of 0.322. Conclusion For small lung cancers with a maximum diameter ≤ 2 cm, CTR measured at a CT threshold of -250 HU can accurately predict lung cancer invasiveness. At CTR > 0.322, the nodule is more likely to be microinvasive or invasive adenocarcinoma.