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Volume-based parameter of 18F-FDG PET/CT in malignant pleural mesothelioma: Prediction of therapeutic response and prognostic implications

Research output: Contribution to journalArticlepeer-review

Abstract

Background: To evaluate the importance of assessing volume-based parameter of 18F-FDG PET/CT in patients with malignant pleural mesothelioma (MPM) for the prediction of response and patient outcome early in the course of treatment. Materials and Methods: Patients (n = 13; M:F = 9:4, mean age, 54 years) with histopathologically proven MPM, all of whom were scheduled to undergo curative extrapleural pneumonectomy (EPP) or palliative chemotherapy, were included in this study. They were evaluated using integrated 18F-FDG PET/CT at baseline. Maximum standardized uptake value (SUVmax), average SUV (SUVavg), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured using PET/CT data. Relationships between tumor progression and PET parameters were statistically analyzed. Results: Of the 13 patients, 8 (62%) developed disease recurrence after surgery or tumor progression after chemotherapy (median follow-up, 329 days; range, 28-536 days). Between subgroups with and without tumor progression, significant differences were noted in MTV (P = 0.045). On ROC curve analysis, MTV (AUC = 0.850, 95% confidence interval [95% CI] 0.550-0.977) and TLG (AUC = 0.800, 95% CI 0.494-0.960) showed good predictive performance for tumor progression. Multivariate analysis adjusted for treatment modality showed that MTV (HR 1.003, P = 0.025) and TLG (HR 1.001, P = 0.031) were independent factors associated with tumor progression. Time to tumor progression was shorter in patients with a high volume-based parameter of PET than in those with a low value. Conclusions: Volume-based parameters of 18F-FDG PET/CT have the potential to provide prognostic information in MPM patients who are receiving surgery or palliative chemotherapy.

Original languageEnglish
Pages (from-to)2787-2794
Number of pages8
JournalAnnals of Surgical Oncology
Volume17
Issue number10
DOIs
StatePublished - Oct 2010

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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