Pretreatment DWI with Histogram Analysis of the ADC in Predicting the Outcome of Advanced Oropharyngeal Cancer with Known Human Papillomavirus Status Treated with Chemoradiation

References

1. 1.↵
   1. Chaturvedi AK,
   2. Engels EA,
   3. Pfeiffer RM, et al

   . Human papillomavirus and rising oropharyngeal cancer incidence in the United States. J Clin Oncol 2011;29:4294–4301 doi:10.1200/JCO.2011.36.4596 pmid:21969503

   Abstract/FREE Full Text
2. 2.↵
   1. Huang SH,
   2. O’Sullivan B

   . Overview of the 8th Edition TNM Classification for Head and Neck Cancer. Curr Treat Options Oncol 2017;18:40 doi:10.1007/s11864-017-0484-y pmid:28555375

   CrossRefPubMed
3. 3.
   1. Würdemann N,
   2. Wagner S,
   3. Sharma SJ

   , et al. Prognostic impact of AJCC/UICC 8th Edition new staging rules in oropharyngeal squamous cell carcinoma. Front Oncol 2017;7:129 doi:10.3389/fonc.2017.00129 pmid:28713770

   CrossRefPubMed
4. 4.↵
   1. Zanoni DK,
   2. Patel SG,
   3. Shah JP

   . Changes in the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging of Head and Neck Cancer: rationale and implications. Curr Oncol Rep 2019;21:52 doi:10.1007/s11912-019-0799-x pmid:30997577

   CrossRefPubMed
5. 5.↵
   1. Windon MJ,
   2. D’Souza G,
   3. Fakhry C

   . Treatment preferences in human papillomavirus-associated oropharyngeal cancer. Future Oncol 2018;14:2521–30 doi:10.2217/fon-2018-0063 pmid:30265132

   CrossRefPubMed
6. 6.↵
   1. Larsen CG,
   2. Jensen DH,
   3. Carlander AL, et al

   . Novel nomograms for survival and progression in HPV+ and HPV− oropharyngeal cancer: a population-based study of 1,542 consecutive patients. Oncotarget 2016;7:71761–72 doi:10.18632/oncotarget.12335 pmid:27708214

   CrossRefPubMed
7. 7.↵
   1. Fakhry C,
   2. Zhang Q,
   3. Nguyen-Tân PF, et al

   . Development and validation of nomograms predictive of overall and progression-free survival in patients with oropharyngeal cancer. J Clin Oncol 2017;35:4057–65 doi:10.1200/JCO.2016.72.0748 pmid:28777690

   CrossRefPubMed
8. 8.↵
   1. Bossi P,
   2. Miceli R,
   3. Granata R, et al

   . In reply to Fakhry et al. Int J Radiat Oncol Biol Phys 2018;102:670–71 doi:10.1016/j.ijrobp.2018.06.019 pmid:30238903

   CrossRefPubMed
9. 9.↵
   1. Leijenaar RT,
   2. Carvalho S,
   3. Hoebers FJ, et al

   . External validation of a prognostic CT-based radiomic signature in oropharyngeal squamous cell carcinoma. Acta Oncol 2015;54:1423–29 doi:10.3109/0284186X.2015.1061214 pmid:26264429

   CrossRefPubMed
10. 10.↵
    M.D. Anderson Cancer Center Head and Neck Quantitative Imaging Working Group. Investigation of radiomic signatures for local recurrence using primary tumor texture analysis in oropharyngeal head and neck cancer patients. Sci Rep 2018;8:1524 doi:10.1038/s41598-017-14687-0 pmid:29367653

    CrossRefPubMed
11. 11.↵
    1. King AD,
    2. Thoeny HC

    . Functional MRI for the prediction of treatment response in head and neck squamous cell carcinoma: potential and limitations. Cancer Imaging 2016;16:23 doi:10.1186/s40644-016-0080-6 pmid:27542718

    CrossRefPubMed
12. 12.↵
    1. Ravanelli M,
    2. Grammatica A,
    3. Tononcelli E, et al

    . Correlation between human papillomavirus status and quantitative MR imaging parameters including diffusion-weighted imaging and texture features in oropharyngeal carcinoma. AJNR Am J Neuroradiol 2018;39:1878–83 doi:10.3174/ajnr.A5792 pmid:30213805

    Abstract/FREE Full Text
13. 13.↵
    1. Driessen JP,
    2. Caldas-Magalhaes J,
    3. Janssen LM, et al

    . Diffusion-weighted MR imaging in laryngeal and hypopharyngeal carcinoma: association between apparent diffusion coefficient and histologic findings. Radiology 2014;272:456–63 doi:10.1148/radiol.14131173 pmid:24749712

    CrossRefPubMed
14. 14.↵
    1. Swartz JE,
    2. Driessen JP,
    3. van Kempen PM, et al

    . Influence of tumor and microenvironment characteristics on diffusion-weighted imaging in oropharyngeal carcinoma: a pilot study. Oral Oncol 2018;77:9–15 doi:10.1016/j.oraloncology.2017.12.001 pmid:29362130

    CrossRefPubMed
15. 15.↵
    1. Kim S,
    2. Loevner L,
    3. Quon H, et al

    . Diffusion-weighted magnetic resonance imaging for predicting and detecting early response to chemoradiation therapy of squamous cell carcinomas of the head and neck. Clin Cancer Res 2009;15:986–94 doi:10.1158/1078-0432.CCR-08-1287 pmid:19188170

    Abstract/FREE Full Text
16. 16.
    1. Hatakenaka M,
    2. Nakamura K,
    3. Yabuuchi H, et al

    . Pretreatment apparent diffusion coefficient of the primary lesion correlates with local failure in head-and-neck cancer treated with chemoradiotherapy or radiotherapy. Int J Radiat Oncol Biol Phys 2011;81:339–45 doi:10.1016/j.ijrobp.2010.05.051 pmid:20832179

    CrossRefPubMed
17. 17.
    1. Ohnishi K,
    2. Shioyama Y,
    3. Hatakenaka M, et al

    . Prediction of local failures with a combination of pretreatment tumor volume and apparent diffusion coefficient in patients treated with definitive radiotherapy for hypopharyngeal or oropharyngeal squamous cell carcinoma. J Radiat Res 2011;52:522–30 doi:10.1269/jrr.10178 pmid:21905311

    CrossRefPubMed
18. 18.
    1. Srinivasan A,
    2. Chenevert TL,
    3. Dwamena BA, et al

    . Utility of pretreatment mean apparent diffusion coefficient and apparent diffusion coefficient histograms in prediction of outcome to chemoradiation in head and neck squamous cell carcinoma. J Comput Assist Tomogr 2012;36:131–37 doi:10.1097/RCT.0b013e3182405435 pmid:22261783

    CrossRefPubMed
19. 19.
    1. Nakajo M,
    2. Nakajo M,
    3. Kajiya Y, et al

    . FDG PET/CT and diffusion-weighted imaging of head and neck squamous cell carcinoma: comparison of prognostic significance between primary tumor standardized uptake value and apparent diffusion coefficient. Clin Nucl Med 2012;37:475–80 doi:10.1097/RLU.0b013e318248524a pmid:22475897

    CrossRefPubMed
20. 20.
    1. King AD,
    2. Chow KK,
    3. Yu KH, et al

    . Head and neck squamous cell carcinoma: diagnostic performance of diffusion-weighted MR imaging for the prediction of treatment response. Radiology 2013;266:531–38 doi:10.1148/radiol.12120167 pmid:23151830

    CrossRefPubMed
21. 21.
    1. Chawla S,
    2. Kim S,
    3. Dougherty L, et al

    . Pretreatment diffusion-weighted and dynamic contrast-enhanced MRI for prediction of local treatment response in squamous cell carcinomas of the head and neck. AJR Am J Roentgenol 2013;200:35–43 doi:10.2214/AJR.12.9432 pmid:23255739

    CrossRefPubMed
22. 22.
    1. Lambrecht M,
    2. Van Calster B,
    3. Vandecaveye V, et al

    . Integrating pretreatment diffusion weighted MRI into a multivariable prognostic model for head and neck squamous cell carcinoma. Radiother Oncol 2014;110:429–34 doi:10.1016/j.radonc.2014.01.004 pmid:24630535

    CrossRefPubMed
23. 23.
    1. Ng SH,
    2. Liao CT,
    3. Lin CY, et al

    . Dynamic contrast-enhanced MRI, diffusion-weighted MRI and 18F-FDG PET/CT for the prediction of survival in oropharyngeal or hypopharyngeal squamous cell carcinoma treated with chemoradiation. Eur Radiol 2016;26:4162–72 doi:10.1007/s00330-016-4276-8 pmid:26911889

    CrossRefPubMed
24. 24.
    1. Noij DP,
    2. Pouwels PJ,
    3. Ljumanovic R, et al

    . Predictive value of diffusion-weighted imaging without and with including contrast-enhanced magnetic resonance imaging in image analysis of head and neck squamous cell carcinoma. Eur J Radiol 2015;84:108–16 doi:10.1016/j.ejrad.2014.10.015 pmid:25467228

    CrossRefPubMed
25. 25.
    1. Preda L,
    2. Conte G,
    3. Bonello L, et al

    . Combining standardized uptake value of FDG-PET and apparent diffusion coefficient of DW-MRI improves risk stratification in head and neck squamous cell carcinoma. Eur Radiol 2016;26:4432–41 doi:10.1007/s00330-016-4284-8 pmid:26965504

    CrossRefPubMed
26. 26.
    1. Marzi S,
    2. Piludu F,
    3. Sanguineti G, et al

    . The prediction of the treatment response of cervical nodes using intravoxel incoherent motion diffusion-weighted imaging. Eur J Radiol 2017;92:93–102 doi:10.1016/j.ejrad.2017.05.002 pmid:28624026

    CrossRefPubMed
27. 27.
    1. Lombardi M,
    2. Cascone T,
    3. Guenzi E, et al

    . Predictive value of pre-treatment apparent diffusion coefficient (ADC) in radio-chemiotherapy treated head and neck squamous cell carcinoma. RadiolMed 2017;122:345–52 doi:10.1007/s11547-017-0733-y pmid:28188603

    CrossRefPubMed
28. 28.↵
    1. Martens RM,
    2. Noij DP,
    3. Koopman T, et al

    . Predictive value of quantitative diffusion-weighted imaging and 18-F-FDG-PET in head and neck squamous cell carcinoma treated by (chemo)radiotherapy. Eur J Radiol 2019;113:39–50 doi:10.1016/j.ejrad.2019.01.031 pmid:30927958

    CrossRefPubMed
29. 29.↵
    1. Chan MW,
    2. Higgins K,
    3. Enepekides D, et al

    . Radiologic differences between human papillomavirus-related and human papillomavirus-unrelated oropharyngeal carcinoma on diffusion-weighted imaging. ORL J Otorhinolaryngol Relat Spec 2016;78:344–52 doi:10.1159/000458446 pmid:28245461

    CrossRefPubMed
30. 30.↵
    1. Nakahira M,
    2. Saito N,
    3. Yamaguchi H, et al

    . Use of quantitative diffusion-weighted magnetic resonance imaging to predict human papilloma virus status in patients with oropharyngeal squamous cell carcinoma. Eur Arch Otorhinolaryngol 2014;271:1219–25 doi:10.1007/s00405-013-2641-7 pmid:23880924

    CrossRefPubMed
31. 31.↵
    1. Schouten CS,
    2. de Graaf P,
    3. Bloemena E, et al

    . Quantitative diffusion-weighted MRI parameters and human papillomavirus status in oropharyngeal squamous cell carcinoma. AJNR Am J Neuroradiol 2015;36:763–67 doi:10.3174/ajnr.A4271 pmid:25721078

    Abstract/FREE Full Text
32. 32.↵
    1. de Perrot T,
    2. Lenoir V,
    3. Domingo Ayllón M, et al

    . Apparent diffusion coefficient histograms of Human Papillomavirus-positive and human papillomavirus-negative head and neck squamous cell carcinoma: assessment of tumor heterogeneity and comparison with histopathology. AJNR Am J Neuroradiol 2017;38:2153–60 doi:10.3174/ajnr.A5370 pmid:28912282

    Abstract/FREE Full Text