A novel diagnostic model for differentiation of lung metastasis from primary lung cancer in patients with colorectal cancer

Rui Guo; Shi Yan; Fei Wang; Hua Su; Qing Xie; Wei Zhao; Zhi Yang; Nan Li; Jiangyuan Yu

doi:10.3389/fonc.2022.1017618

A novel diagnostic model for differentiation of lung metastasis from primary lung cancer in patients with colorectal cancer

Front Oncol. 2022 Oct 24:12:1017618. doi: 10.3389/fonc.2022.1017618. eCollection 2022.

Authors

Rui Guo¹, Shi Yan², Fei Wang¹, Hua Su¹, Qing Xie¹, Wei Zhao¹, Zhi Yang¹, Nan Li¹, Jiangyuan Yu¹

Affiliations

¹ Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education, Beijing), National Medical Products Administration (NPMA) Key Laboratory for Research and Evaluation of Radiopharmaceuticals (National Medical Products Administration), Department of Nuclear Medicine, Peking University Cancer Hospital & Institute, Beijing, China.
² Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Thoracic Surgery II, Peking University Cancer Hospital and Institute, Beijing, China.

Abstract

Objective: This study aimed to evaluate the ¹⁸F-FDG PET/CT in differentiating lung metastasis(LM) from primary lung cancer(LC) in patients with colorectal cancer (CRC).

Methods: A total of 120 CRC patients (80 male, 40 female) who underwent ¹⁸F-FDG PET/CT were included. The diagnosis of primary lung cancer or lung metastasis was based on histopathology The patients were divided into a training cohort and a validation cohort randomized 1:1. Independent risk factors were extracted through the clinical information and ¹⁸F-FDG PET/CT imaging characteristics of patients in the validation cohort, and then a diagnostic model was constructed and a nomograms was made. ROC curve, calibration curve, cutoff, sensitivity, specificity, and accuracy were used to evaluate the prediction performance of the diagnostic model.

Results: One hundred and twenty Indeterminate lung lesions (ILLs) (77 lung metastasis, 43 primary lung cancer) were analyzed. No significant difference in clinical characteristics and imaging features between the training and the validation cohorts (P > 0. 05). Using uni-/multivariate analysis, pleural tags and contour were identified as independent predictors. These independent predictors were used to establish a diagnostic model with areas under the receiver operating characteristic curves (AUCs) of 0.92 and 0.89 in the primary and validation cohorts, respectively. The accuracy rate of the diagnostic model for differentiating LM from LC were higher than that of subjective diagnosis (P < 0.05).

Conclusions: Pleural tags and contour were identified as independent predictors. The diagnostic model of ILLs in patients with CRC could help differentiate between LM and LC.

Keywords: PET/CT; colorectal cancer; lung lesion; lung metastasis; primary lung cancer.