1. Brizel DM, Albers ME, Fisher SR (1998) Hyperfractionated irradiation with or without concurrent chemotherapy for locally advanced head and neck cancer. The New England journal of medicine, 338(25): 1798-1804. [DOI:10.1056/NEJM199806183382503]

2. Delaney G, Jacob S, Featherstone C (2005) The role of radiotherapy in cancer treatment: estimating optimal utilization from a review of evidence-based clinical guidelines. Cancer, 104(6): 1129-1137. [DOI:10.1002/cncr.21324]

3. Tinhofer I, Niehr F, Konschak R (2015) Next-generation sequencing: hype and hope for development of personalized radiation therapy? Radiat Oncol, 10: 183. [DOI:10.1186/s13014-015-0481-x]

4. Biomarkers Definitions Working G (2001) Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther, 69(3): 89-95. [DOI:10.1067/mcp.2001.113989]

5. Cooper JS, Pajak TF, Forastiere AA (2004) Postoperative concurrent radiotherapy and chemotherapy for high-risk squamous-cell carcinoma of the head and neck. The New England journal of medicine, 350(19): 1937-1944. [DOI:10.1056/NEJMoa032646]

6. Knegjens JL, Hauptmann M, Pameijer FA (2011) Tumor volume as prognostic factor in chemoradiation for advanced head and neck cancer. Head & neck, 33(3): 375-382. [DOI:10.1002/hed.21459]

7. Zoumalan RA, Kleinberger AJ, Morris LG (2010) Lymph node central necrosis on computed tomography as predictor of extracapsular spread in metastatic head and neck squamous cell carcinoma: pilot study. J Laryngol Otol, 124(12): 1284-1288. [DOI:10.1017/S0022215110001453]

8. Imsande HM, Davison JM, Truong MT (2011) Use of 18F-FDG PET/CT as a predictive biomarker of outcome in patients with head-and-neck non-squamous cell carcinoma. AJR Am J Roentgenol, 197(4): 976-980. [DOI:10.2214/AJR.10.4884]

9. Machtay M, Natwa M, Andrel J (2009) Pretreatment FDG-PET standardized uptake value as a prognostic factor for outcome in head and neck cancer. Head & neck, 31(2): 195-201. [DOI:10.1002/hed.20942]

10. Ai QY, King AD, Law BK (2017) Diffusion-weighted imaging of nasopharyngeal carcinoma to predict distant metastases. Eur Arch Otorhinolaryngol, 274(2): 1045-1051. [DOI:10.1007/s00405-016-4333-6]

11. Assaf Y, Kafri M, Shinar H (2002) Changes in axonal morphology in experimental autoimmune neuritis as studied by high b-value q-space (1)H and (2)H DQF diffusion magnetic resonance spectroscopy. Magn Reson Med, 48(1): 71-81. [DOI:10.1002/mrm.10183]

12. Jensen JH, Helpern JA, Ramani A (2005) Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med, 53(6): 1432-1440. [DOI:10.1002/mrm.20508]

13. Chen Y, Ren W, Zheng D (2015) Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients. J Magn Reson Imaging, 42(5): 1354-1361. [DOI:10.1002/jmri.24910]

14. Kang HS, Kim JY, Kim JJ (2022) Diffusion Kurtosis MR Imaging of Invasive Breast Cancer: Correlations With Prognostic Factors and Molecular Subtypes. J Magn Reson Imaging, 56(1): 110-120. [DOI:10.1002/jmri.27999]

15. Zhu L, Pan Z, Ma Q (2017) Diffusion Kurtosis Imaging Study of Rectal Adenocarcinoma Associated with Histopathologic Prognostic Factors: Preliminary Findings. Radiology, 284(1): 66-76. [DOI:10.1148/radiol.2016160094]

16. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR Biomed, 23(7): 698-710. [DOI:10.1002/nbm.1518]

17. Rosenkrantz AB, Padhani AR, Chenevert TL (2015) Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice. J Magn Reson Imaging, 42(5): 1190-1202. [DOI:10.1002/jmri.24985]

18. Tabesh A, Jensen JH, Ardekani BA (2011) Estimation of tensors and tensor-derived measures in diffusional kurtosis imaging. Magn Reson Med, 65(3): 823-836. [DOI:10.1002/mrm.22655]

19. Veraart J, Poot DH, Van Hecke W (2011) More accurate estimation of diffusion tensor parameters using diffusion Kurtosis imaging. Magn Reson Med, 65(1): 138-145. [DOI:10.1002/mrm.22603]

20. Sridhar P, Mercier G, Tan J (2014) FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors. AJR Am J Roentgenol, 202(5): 1114-1119. [DOI:10.2214/AJR.13.11456]

21. Eisenhauer EA, Therasse P, Bogaerts J (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer, 45(2): 228-247. [DOI:10.1016/j.ejca.2008.10.026]

22. Moon SH, Choi JY, Lee HJ (2013) Prognostic value of 18F-FDG PET/CT in patients with squamous cell carcinoma of the tonsil: comparisons of volume-based metabolic parameters. Head & neck, 35(1): 15-22. [DOI:10.1002/hed.22904]

23. Pak K, Cheon GJ, Nam HY (2014) Prognostic value of metabolic tumor volume and total lesion glycolysis in head and neck cancer: a systematic review and meta-analysis. J Nucl Med, 55(6): 884-890. [DOI:10.2967/jnumed.113.133801]

24. Kim S, Oh S, Kim JS (2018) Prognostic value of FDG PET/CT during radiotherapy in head and neck cancer patients. Radiat Oncol J, 36(2): 95-102. [DOI:10.3857/roj.2017.00577]

25. Velasquez LM, Boellaard R, Kollia G (2009) Repeatability of 18F-FDG PET in a multicenter phase I study of patients with advanced gastrointestinal malignancies. J Nucl Med, 50(10): 1646-1654. [DOI:10.2967/jnumed.109.063347]

26. Westerterp M, Pruim J, Oyen W (2007) Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters. Eur J Nucl Med Mol Imaging, 34(3): 392-404. [DOI:10.1007/s00259-006-0224-1]

27. Zhang Y, Liu X, Zhang Y (2015) Prognostic value of the primary lesion apparent diffusion coefficient (ADC) in nasopharyngeal carcinoma: a retrospective study of 541 cases. Scientific reports, 5: 12242. [DOI:10.1038/srep12242]

28. Chen Y, Liu X, Zheng D (2014) Diffusion-weighted magnetic resonance imaging for early response assessment of chemoradiotherapy in patients with nasopharyngeal carcinoma. Magn Reson Imaging, 32(6): 630-637. [DOI:10.1016/j.mri.2014.02.009]

29. Basser PJ, Jones DK (2002) Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review. NMR Biomed, 15(7-8): 456-467. [DOI:10.1002/nbm.783]

30. Lu H, Jensen JH, Ramani A (2006) Three-dimensional characterization of non-gaussian water diffusion in humans using diffusion kurtosis imaging. NMR Biomed, 19(2): 236-247. [DOI:10.1002/nbm.1020]

31. Shima T, Fujima N, Yamano S (2020) Evaluation of non-Gaussian model-based diffusion-weighted imaging in oral squamous cell carcinoma: comparison with tumour functional information derived from positron-emission tomography. Clin Radiol, 75(5): 397 e315-397 e321. [DOI:10.1016/j.crad.2019.12.018]

32. Hori M, Fukunaga I, Masutani Y (2012) Visualizing non-Gaussian diffusion: clinical application of q-space imaging and diffusional kurtosis imaging of the brain and spine. Magn Reson Med Sci, 11(4): 221-233. [DOI:10.2463/mrms.11.221]

33. Imaizumi A, Obata T, Kershaw J (2020) Imaging of Hypoxic Tumor: Correlation between Diffusion-weighted MR Imaging and (18)F-fluoroazomycin Arabinoside Positron Emission Tomography in Head and Neck Carcinoma. Magn Reson Med Sci, 19(3): 276-281. [DOI:10.2463/mrms.tn.2019-0007]