Objective To explore the clinical value of dual-layer spectral detector CT (DLCT) in distinguishing diagnosis of pulmonary primary malignant tumor, chronic inflammation and tuberculosis by measuring and analyzing the parameters and conventional CT signs. Methods The clinical data of 345 patients with pulmonary lesions were collected from August 2020 to June 2021, who underwent DLCT chest enhanced scan and obtained pathological results in People's Hospital of Gansu Province, and then divided into three groups: pulmonary primary malignant tumor group (n=187), chronic inflammation group (n=101) and tuberculosis group (n=57). The conventional CT signs of the three groups were retrospectively analyzed and the DLCT parameters were measured. The logistic regression analysis was performed for parameters with statistically significant differences, and then conventional CT signs diagnostic model, DLCT parameter diagnostic model and combined diagnostic model were established. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficacy of each model. Delong test was used to compare the AUC of each models. Results In distinguishing the conventional CT signs of the three lesions, statistical differences existed in the following indicators: the distance of lesions to pleura (P=0.009), morphology (P<0.001), density (P=0.001), the boundary between lesions and lung (P=0.001), lobulation (P<0.001), liquefaction necrosis (P=0.003), vascular cluster sign(P<0.001), halo sign (P=0.003), satellite focus (P=0.045), pleural effusion (P=0.002), enlarged lymph nodes in the mediastinum(P<0.001), effective atomic number (Z_eff), iodine concentration (IC), normalization iodine concentration (NIC), energy spectrum curve slope (λ_HU), and arterial enhancement fraction (AEF) (P<0.001) both in the arterial phase (AP) and venous phase (VP).In the differential diagnosis of pulmonary primary malignant tumor and chronic inflammation, the boundary between lesion and lung tissue (P=0.009), lobulation (P<0.001), liquefaction necrosis (P<0.001), halo sign (P=0.025), mediastinal lymphadenopathy(P<0.001), λ_HU-AP (P=0.037) and λ_HU-VP (P=0.029) are independent influencing factors. In the differential diagnosis of pulmonary primary malignant tumor and tuberculosis, lesion morphology (P=0.019), vascular cluster sign (P=0.009), satellite focus (P=0.006),pleural effusion (P=0.001), AEF (P=0.041), λ_HU-AP (P=0.038) and λ_HU-VP (P<0.001) are independent influencing factors. Pleural effusion (P=0.002), mediastinal lymphadenopathy (P<0.001), NIC-VP (P=0.001), Z_eff-VP (P=0.043), λ_HU-AP (P=0.015) and λ_HU-VP (P=0.023) are independent influencing factors in the differential diagnosis of chronic inflammation and tuberculosis. To pathology results for the gold standard, the AUC of conventional CT signs diagnostic model for distinguishing pulmonary primary malignant tumor and chronic inflammation, pulmonary primary malignant tumor and tuberculosis, chronic inflammation and tuberculosis were 0.827, 0.770 and 0.753. The AUC of DLCT parameter values for distinguishing pulmonary primary malignant tumor, chronic inflammation and tuberculosis were 0.905 0.909 and 0.824. The AUC of the combined model for distinguishing pulmonary primary malignant tumor, chronic inflammation and tuberculosis were 0.929, 0.942 and 0.889. Conclusion DLCT parameters combined with conventional CT signs may improve the differential diagnosis efficiency of pulmonary primary malignant tumor, chronic inflammation and tuberculosis.