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A Mouse Model of Incompletely Resected Soft Tissue Sarcoma for Testing Neoadjuvant Therapies
Published on: July 28, 2020
Pretreatment tumor SUVmax predicts disease-specific and overall survival in patients with head and neck soft tissue
Seung Cheol Ha1, Jungsu S Oh2, Jong-Lyel Roh3
1Departments of Otolaryngology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Republic of Korea.
Purpose:
Head and neck soft tissue sarcoma (HNSTS) is a rare type of tumor with various histological presentations and clinical behaviors. 18F-FDG PET/CT is being increasingly used for staging, grading, and predicting treatment outcomes in various types of human cancers, although this modality has been rarely studied in the survival prediction of HNSTS. Here we examined the prognostic value of tumor metabolic parameters measured using 18F-FDG PET/CT in patients with HNSTS.
Methods:
This study included 36 consecutive patients with HNSTS who underwent 18F-FDG PET/CT scanning prior to treatment at our institution. Tumor gross total volume (GTV) was measured from pretreatment contrast-enhanced CT scans, and maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured using pretreatment 18F-FDG PET/CT scans. Univariate and multivariate Cox proportional hazard regression analyses were used to identify associations between imaging parameters and disease-specific survival (DSS) or overall survival (OS).
Results:
Univariate analyses showed that SUVmax, MTV, and TLG, but not GTV, were significantly associated with DSS and OS (all P < 0.05). After controlling for clinicopathological factors, SUVmax, MTV, and TLG were significantly associated with DSS and OS (all P < 0.05). Patients with a tumor SUVmax value of >7.0 experienced an approximately fivefold increase in mortality in terms of DSS and OS relative to those with a tumor SUVmax <7.0.
Conclusion:
Quantitative metabolic measurements on pretreatment 18F-FDG PET/CT can yield values that are significantly predictive of survival after treatment for HNSTS.
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