Prognostic significance of preoperative metabolic tumour volume and total lesion glycolysis measured by 18F-FDG PET/CT in squamous cell carcinoma of the oral cavity
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- Ryu, I.S., Kim, J.S., Roh, J. et al. Eur J Nucl Med Mol Imaging (2014) 41: 452. doi:10.1007/s00259-013-2571-z
Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) from 18F-FDG PET/CT are emerging prognostic biomarkers in human solid cancers; yet few studies have investigated their clinical and prognostic significance in oral cavity squamous cell carcinoma (OSCC). The present retrospective study evaluated the utility of pretreatment MTV and TLG measured by 18F-FDG PET/CT to predict survival and occult metastasis (OM) in OSCC.
Of 162 patients with OSCC evaluated preoperatively by 18F-FDG PET/CT, 105 who underwent definitive surgery with or without adjuvant therapy were eligible. Maximum standardized uptake value (SUVmax), MTV and TLG were measured. For calculation of MTV, 3-D regions of interest were drawn and a SUV threshold of 2.5 was used for defining regions. Univariate and multivariate analyses identified clinicopathological and imaging variables associated with OM, disease-free survival (DFS) and overall survival (OS).
The median (range) SUVmax, MTV and TLG were 7.3 (0.7–41.9), 4.5 ml (0.7–115.1 ml) and 18.3 g (2.4–224.1 g), respectively. Of 53 patients with clinically negative lymph nodes, OM was detected in 19 (36 %). By univariate and multivariate analyses, MTV (P = 0.018) and TLG (P = 0.011) were both independent predictive factors for OM, although they were not independent of each other. The 4-year DFS and OS rates were 53.0 % and 62.0 %, respectively. Univariate and multivariate analyses revealed that MTV (P = 0.001) and TLG (P = 0.006), with different cut-off levels, were both independent predictive factors for DFS, although they were not independent of each other, and MTV (P = 0.001), TLG (P = 0.002) and the involved resection margin (P = 0.007) were independent predictive factors for OS.
Pretreatment MTV and TLG may be useful in stratifying the likelihood of survival and predicting OM in OSCC.