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Updated: Jun 18, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
[Comparative study on CT image characteristics of pneumoconiosis large shadow and primary lung cancer mass]
1Radiology Department of Zibo Occupational Disease Prevention Hospital, Zibo 255000, China.
Abstract:
Objective: To compare the CT image characteristics of pneumoconiosis large shadow and primary lung cancer mass, and analyze the value of CT image characteristics in the differential diagnosis of pneumoconiosis large shadow and primary lung cancer. Methods: In September 2022, 43 patients with stage Ⅲ pneumoconiosis who were hospitalized in Zibo Occupational Disease Prevention Hospital from January 2020 to June 2021 and 52 patients with primary lung cancer who were confirmed by pathology in the Affiliated Hospital of Jining Medical University during the same period were selected as the investigation objects, and the image characteristics of pneumoconiosis large shadow or lung cancer mass and surrounding tissues in the chest CT images of the two groups were compared. Univariate analysis, cluster analysis and cross analysis were used to screen out statistically significant indicators as independent variables, and pneumoconiosis and lung cancer as dependent variables for logistic regression analysis. Results: There were statistically significant differences between large shadow of pneumoconiosis and primary lung cancer mass in single factor CT imaging, such as irregular shape of lesions, CT attenuation value, calcification, cavitation, spiculation, liquefactive necrosis, satellite lesions, adjacent emphysema, short spicules, and pleural thickening (P<0.05). CT value ≥92 HU (abnormal CT attenuation value), calcification, peripheral satellite lesions, pleural thickening, parapunctal emphysema, spines on the lesion margin, irregular lesion morphology were typical features of stage Ⅲ pneumoconiosis, with multiple features of aggregation. The typical features of lung cancer were liquefaction necrosis, round or quasi-round appearance, cavitation and interlobar pleura. A logistic regression model was constructed using satellite lesions, spiculation, pleural thickening, and lesion abnormal CT attenuation value had an R(2) of 0.880 and an accuracy of 95.3% for differentiation. Conclusion: Abnormal CT attenuation value, calcification, peripheral satellite lesions, pleural thickening, spiculation at the edges, liquefaction necrosis, interlobar pleura involvement, and cavitation can distinguish the large shadow of stage Ⅲ pneumoconiosis from lung cancer mass.
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