Shu-Hang Ng1,2,3, Chun-Ta Liao4, Chien-Yu Lin5, Sheng-Chieh Chan1,6, Yu-Chun Lin2,3, Tzu-Chen Yen1,6, Joseph Tung-Chieh Chang5, Sheung-Fat Ko2, Kang-Hsing Fan5, Hung-Ming Wang7, Lan-Yan Yang8, Jiun-Jie Wang9,10,11,12. 1. Molecular Imaging Center, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 2. Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 3. Department of Medical Imaging and Radiological Sciences, Chang Gung Memorial Hospital, Chang Gung University, 259 Wen Hua 1st Road, Kueishan, Taoyuan, 333, Taiwan. 4. Department of Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 5. Department of Radiation Oncology, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 6. Department of Nuclear Medicine, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 7. Department of Medical Oncology, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 8. Biostatistics and Informatics Unit, Chang Gung Memorial Hospital, Chang Gung University, Kueishan, Taoyuan, Taiwan. 9. Department of Medical Imaging and Radiological Sciences, Chang Gung Memorial Hospital, Chang Gung University, 259 Wen Hua 1st Road, Kueishan, Taoyuan, 333, Taiwan. jwang@mail.cgu.edu.tw. 10. Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan. jwang@mail.cgu.edu.tw. 11. Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung, Taiwan. jwang@mail.cgu.edu.tw. 12. Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University / Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan. jwang@mail.cgu.edu.tw.
Abstract
OBJECTIVES: We prospectively investigated the roles of pretreatment dynamic contrast-enhanced MR imaging (DCE-MRI), diffusion-weighted MR imaging (DWI) and 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG PET)/CT for predicting survival of oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC) patients treated with chemoradiation. METHODS: Patients with histologically proven OHSCC and neck nodal metastases scheduled for chemoradiation were eligible. Clinical variables as well as DCE-MRI-, DWI- and 18F-FDG PET/CT-derived parameters of the primary tumours and metastatic neck nodes were analysed in relation to 3-year progression-free survival (PFS) and overall survival (OS) rates. RESULTS: Eighty-six patients were available for analysis. Multivariate analysis identified the efflux rate constant (K ep)-tumour < 3.79 min-1 (P = 0.001), relative volume of extracellular extravascular space (V e)-node < 0.23 (P = 0.004) and SUVmax-tumour > 19.44 (P = 0.025) as independent risk factors for both PFS and OS. A scoring system based upon the sum of each of the three imaging parameters allowed stratification of our patients into three groups (patients with 0/1 factor, patients with 2 factors and patients with 3 factors, respectively) with distinct PFS (3-year rates = 72 %, 38 % and 0 %, P < 0.0001) and OS (3-year rates = 81 %, 46 % and 20 %, P < 0.0001). CONCLUSIONS: K ep-tumour, V e-node and SUVmax-tumour were independent prognosticators for OHSCC treated with chemoradiation. Their combination helped survival stratification. KEY POINTS: • K ep -tumour, V e -node and SUV max -tumour are independent predictors of survival rates. • The combination of these three prognosticators may help stratification of survival. • MRI and FDG-PET/CT play complementary roles in prognostication of head and neck cancer.
OBJECTIVES: We prospectively investigated the roles of pretreatment dynamic contrast-enhanced MR imaging (DCE-MRI), diffusion-weighted MR imaging (DWI) and 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG PET)/CT for predicting survival of oropharyngeal or hypopharyngeal squamous cell carcinoma (OHSCC) patients treated with chemoradiation. METHODS:Patients with histologically proven OHSCC and neck nodal metastases scheduled for chemoradiation were eligible. Clinical variables as well as DCE-MRI-, DWI- and 18F-FDG PET/CT-derived parameters of the primary tumours and metastatic neck nodes were analysed in relation to 3-year progression-free survival (PFS) and overall survival (OS) rates. RESULTS: Eighty-six patients were available for analysis. Multivariate analysis identified the efflux rate constant (K ep)-tumour < 3.79 min-1 (P = 0.001), relative volume of extracellular extravascular space (V e)-node < 0.23 (P = 0.004) and SUVmax-tumour > 19.44 (P = 0.025) as independent risk factors for both PFS and OS. A scoring system based upon the sum of each of the three imaging parameters allowed stratification of our patients into three groups (patients with 0/1 factor, patients with 2 factors and patients with 3 factors, respectively) with distinct PFS (3-year rates = 72 %, 38 % and 0 %, P < 0.0001) and OS (3-year rates = 81 %, 46 % and 20 %, P < 0.0001). CONCLUSIONS: K ep-tumour, V e-node and SUVmax-tumour were independent prognosticators for OHSCC treated with chemoradiation. Their combination helped survival stratification. KEY POINTS: • K ep -tumour, V e -node and SUV max -tumour are independent predictors of survival rates. • The combination of these three prognosticators may help stratification of survival. • MRI and FDG-PET/CT play complementary roles in prognostication of head and neck cancer.
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