Objective: To investigate the computed tomography (CT) features of malignant pleural mesothelioma (MPM) cases, comparing them to those in other malignant and benign pleural diseases.
Materials and methods: We reviewed the CT findings of 215 patients; 99 with MPM, 39 with metastatic pleural disease (MPD), and 77 with benign pleural disease. The findings were evaluated in univariate and multivariate analysis for differentiation of pleural diseases.
Results: In patients with MPM, the most common CT features were circumferential lung encasement by multiple nodules (28%); pleural thickening with irregular pleuropulmonary margins (26%); and pleural thickening with superimposed nodules (20%). In the majority (70%) of cases, there was rind-like extension of tumor on the pleural surfaces. In multivariate analysis, the CT findings of "rind-like pleural involvement", "mediastinal pleural involvement", and "pleural thickness more than 1 cm" were independent findings in differentiating MPM from MPD with the sensitivity/specificity values of 70/85, 85/67, and 59/82, respectively. "Rind-like pleural involvement", "mediastinal pleural involvement", "pleural nodularity" and "pleural thickness more than 1 cm" were independent findings for differentiation of malignant pleural diseases (MPM+MPD) from benign pleural disease with the sensitivity/specificity values of 54/95, 70/83, 38/96, and 47/64, respectively. Invasion of thoracic structures such as pericardium, chest wall, diaphragm, mediastinum, with pleural disease and nodular involvement of fissures, was detected infrequently; however, since these invasions were not seen in benign pleural diseases, it was concluded these invasions, if detected on a CT scan, directly suggested malignancy.
Conclusion: A patient has extremely high probability of malignant pleural disease if one or more of these CT findings are found and the possibility of MPM is high. These findings may be important for patients in bad state or patients who do not want any invasive biopsy procedures. It is also possible to identify cases with a low probability of malignant disease.