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Arterial spin labelling and diffusion-weighted magnetic resonance imaging in differentiation of recurrent head and neck cancer from post-radiation changes

Published online by Cambridge University Press:  02 November 2018

A A K Abdel Razek
A A K Abdel Razek*
Affiliation:
Department of Diagnostic Radiology, Faculty of Medicine, Mansoura University, Egypt
*
Author for correspondence: Dr Ahmed Abdel Khalek Abdel Razek, Department of Diagnostic Radiology, Faculty of Medicine, Mansoura University, Mansoura 13351, Egypt E-mail: [email protected] Fax: +20 502 315 105
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Abstract

Objective

To assess arterial spin labelling and diffusion-weighted imaging in the differentiation of recurrent head and neck cancer from post-radiation changes.

Methods

A retrospective study was conducted of 47 patients with head and neck cancer, treated with radiotherapy, who underwent magnetic resonance arterial spin labelling and diffusion-weighted magnetic resonance imaging. Tumour blood flow and apparent diffusion co-efficient of the lesion were calculated.

Results

There was significant difference (p = 0.001) in tumour blood flow between patients with recurrent head and neck cancer (n = 31) (47.37 ± 16.3 ml/100 g/minute) and those with post-radiation changes (n = 16) (18.80 ± 2.9 ml/100 g/minute). The thresholds of tumour blood flow and apparent diffusion co-efficient used for differentiating recurrence from post-radiation changes were more than 24.0 ml/100 g/minute and 1.21 × 10−3 mm2/second or less, with area under the curve values of 0.94 and 0.90, and accuracy rates of 88.2 per cent and 88.2 per cent, respectively. The combined tumour blood flow and apparent diffusion co-efficient values used for differentiating recurrence from post-radiation changes had an area under the curve of 0.96 and an accuracy of 90.2 per cent.

Conclusion

Combined tumour blood flow and apparent diffusion co-efficient can differentiate recurrence from post-radiation changes.

Keywords

NeoplasmsRecurrenceRadiotherapy
Type
Main Articles
Information
The Journal of Laryngology & Otology , Volume 132 , Issue 10 , October 2018 , pp. 923 - 928
Copyright
Copyright © JLO (1984) Limited, 2018 

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Footnotes

Dr A A K Abdel Razek takes responsibility for the integrity of the content of the paper

References

1Chang, JH, Wu, CC, Yuan, KS, Wu, AT, Wu, SY. Locoregionally recurrent head and neck squamous cell carcinoma: incidence, survival, prognostic factors, and treatment outcomes. Oncotarget 2017;8:55600–12Google Scholar
2Shaikh, T, Handorf, EA, Murphy, CT, Mehra, R, Ridge, JA, Galloway, TJ. The impact of radiation treatment time on survival in patients with head and neck cancer. Int J Radiat Oncol Biol Phys 2016;96:967–75Google Scholar
3Abdel Razek, A. Neoplastic pathology of the neck. In Luca, S, ed. Image Principles, Neck, and the Brain. Boca Raton, FL: CRC Press, 2016;425–52Google Scholar
4Saito, N, Nadgir, RN, Nakahira, M, Takahashi, M, Uchino, A, Kimura, F et al. Posttreatment CT and MR imaging in head and neck cancer: what the radiologist needs to know. Radiographics 2012;32:1261–82Google Scholar
5King, AD, Keung, CK, Yu, KH, Mo, FK, Bhatia, KS, Yeung, DK et al. T2-weighted MR imaging early after chemoradiotherapy to evaluate treatment response in head and neck squamous cell carcinoma. AJNR Am J Neuroradiol 2013;34:1237–41Google Scholar
6Chikui, T, Kawano, S, Kawazu, T, Hatakenaka, M, Koga, S, Ohga, M et al. Prediction and monitoring of the response to chemoradiotherapy in oral squamous cell carcinomas using a pharmacokinetic analysis based on the dynamic contrast-enhanced MR imaging findings. Eur Radiol 2011;21:1699–708Google Scholar
7Abdel Razek, AA, Gaballa, G, Ashamalla, G, Alashry, MS, Nada, N. Dynamic susceptibility contrast perfusion-weighted MR imaging and diffusion-weighted MR imaging in differentiating recurrent head and neck cancer from post-radiation changes. J Comput Assist Tomogr 2015;39:849–54Google Scholar
8Abdel Razek, AA, Gaballa, G. Role of perfusion magnetic resonance imaging in cervical lymphadenopathy. J Comput Assist Tomogr 2011;35:21–5Google Scholar
9King, AD, Yeung, DK, Yu, KH, Mo, FK, Hu, CW, Bhatia, KS et al. Monitoring of treatment response after chemoradiotherapy for head and neck cancer using in vivo 1H MR spectroscopy. Eur Radiol 2010;20:165–72Google Scholar
10Razek, AA, Nada, N. Correlation of choline/creatine and apparent diffusion coefficient values with the prognostic parameters of head and neck squamous cell carcinoma. NMR Biomed 2016;29:483–9Google Scholar
11Abdel Razek, AA, Poptani, H. MR spectroscopy of head and neck cancer. Eur J Radiol 2013;82:982–9Google Scholar
12Clavel, S, Charron, MP, Bélair, M, Delouya, G, Fortin, B, Després, P et al. The role of computed tomography in the management of the neck after chemoradiotherapy in patients with head-and-neck cancer. Int J Radiat Oncol Biol Phys 2012;82:567–73Google Scholar
13Razek, AA, Tawfik, A, Elsorogy, L, Soliman, N. Perfusion CT of head and neck cancer. Eur J Radiol 2014;83:537–44Google Scholar
14Kostakoglu, L, Fardanesh, R, Posner, M, Som, P, Rao, S, Park, E et al. Early detection of recurrent disease by FDG-PET/CT leads to management changes in patients with squamous cell cancer of the head and neck. Oncologist 2013;18:1108–17Google Scholar
15Lee, YZ, Ramalho, J, Kessler, B. PET-MR imaging in head and neck. Magn Reson Imaging Clin N Am 2017;25:315–24Google Scholar
16Razek, AA, El-Serougy, L, Abdelsalam, M, Gaballa, G, Talaat, M. Differentiation of residual/recurrent gliomas from postradiation necrosis with arterial spin labeling and diffusion tensor magnetic resonance imaging-derived metrics. Neuroradiology 2018;60:169–77Google Scholar
17Fujima, N, Kudo, K, Tsukahara, A, Yoshida, D, Sakashita, T, Homma, A et al. Measurement of tumor blood flow in head and neck squamous cell carcinoma by pseudo-continuous arterial spin labeling: comparison with dynamic contrast-enhanced MRI. J Magn Reson Imaging 2015;41:983–91Google Scholar
18Fujima, N, Yoshida, D, Sakashita, T, Homma, A, Tsukahara, A, Tha, KK et al. Usefulness of pseudocontinuous arterial spin-labeling for the assessment of patients with head and neck squamous cell carcinoma by measuring tumor blood flow in the pretreatment and early treatment period. AJNR Am J Neuroradiol 2016;37:342–8Google Scholar
19Fujima, N, Kudo, K, Yoshida, D, Homma, A, Sakashita, T, Tsukahara, A et al. Arterial spin labeling to determine tumor viability in head and neck cancer before and after treatment. J Magn Reson Imaging 2014;40:920–8Google Scholar
20Razek, AA. Assessment of masses of the external ear with diffusion-weighted MR imaging. Otol Neurotol 2018;39:227–31Google Scholar
21Abdel Razek, AA. Assessment of solid lesions of the temporal fossa with diffusion-weighted magnetic resonance imaging. Int J Oral Maxillofac Surg 2015;44:1081–5Google Scholar
22Varoquaux, A, Rager, O, Dulguerov, P, Burkhardt, K, Ailianou, A, Becker, M. Diffusion-weighted and PET/MR imaging after radiation therapy for malignant head and neck tumor. Radiographics 2015;35:1502–27Google Scholar
23Hwang, I, Choi, SH, Kim, YJ, Kim, KG, Lee, AL, Yun, TJ et al. Differentiation of recurrent tumor and posttreatment changes in head and neck squamous cell carcinoma: application of high b-value diffusion-weighted imaging. AJNR Am J Neuroradiol 2013;34:2343–8Google Scholar
24Abdel Razek, AA, Kandeel, AY, Soliman, N, El-shenshawy, HM, Kamel, Y, Nada, N et al. Role of diffusion-weighted echo-planar MR imaging in differentiation of residual or recurrent head and neck tumors and posttreatment changes. AJNR Am J Neuroradiol 2007;28:1146–52Google Scholar
25Hauser, T, Essig, M, Jensen, A, Laun, FB, Münter, M, Maier-Hein, KH et al. Prediction of treatment response in head and neck carcinomas using IVIM-DWI: evaluation of lymph node metastasis. Eur J Radiol 2014;83:783–7Google Scholar
26Fujima, N, Yoshida, D, Sakashita, T, Homma, A, Kudo, K, Shirato, H. Residual tumour detection in post-treatment granulation tissue by using advanced diffusion models in head and neck squamous cell carcinoma patients. Eur J Radiol 2017;90:14–19Google Scholar
27Min, M, Lee, MT, Lin, P, Holloway, L, Wijesekera, D, Gooneratne, D et al. Assessment of serial multi-parametric functional MRI (diffusion-weighted imaging and R2*) with (18)F-FDG-PET in patients with head and neck cancer treated with radiation therapy. Br J Radiol 2016;89:20150530Google Scholar
28Wong, KH, Panek, R, Bhide, SA, Nutting, CM, Harrington, KJ, Newbold, KL. The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective. Br J Radiol 2017;90:20160768Google Scholar
29King, AD, Thoeny, HC. Functional MRI for the prediction of treatment response in head and neck squamous cell carcinoma: potential and limitations. Cancer Imaging 2016;16:23Google Scholar
30Abdel Razek, A, Elkhamary, S, Al-Mesfer, S, Alkatan, HM. Correlation of apparent diffusion coefficient at 3 T with prognostic parameters of retinoblastoma. AJNR Am J Neuroradiol 2012;33:944–8Google Scholar
31Tawfik, AM, Razek, AA, Kerl, JM, Nour-Eldin, NE, Bauer, R, Vogl, TJ. Comparison of dual-energy CT-derived iodine content and iodine overlay of normal, inflammatory and metastatic squamous cell carcinoma cervical lymph nodes. Eur Radiol 2014;24:574–80Google Scholar
32Abdel Razek, AA, Gaballa, G. Role of perfusion magnetic resonance imaging in cervical lymphadenopathy. J Comput Assist Tomogr 2011;35:21–5Google Scholar
33Abdel Razek, AA, Samir, S, Ashmalla, GA. Characterization of parotid tumors with dynamic susceptibility contrast perfusion-weighted magnetic resonance imaging and diffusion-weighted MR imaging. J Comput Assist Tomogr 2017;41:131–6Google Scholar
34Razek, AA, Sieza, S, Maha, B. Assessment of nasal and paranasal sinus masses by diffusion-weighted MR imaging. J Neuroradiol 2009;36:206–11Google Scholar
35El-Serougy, L, Abdel Razek, AA, Ezzat, A, Eldawoody, H, El-Morsy, A. Assessment of diffusion tensor imaging metrics in differentiating low-grade from high-grade gliomas. Neuroradiol J 2016;29:400–7Google Scholar
36Razek, AA. Prediction of malignancy of submandibular gland tumors with apparent diffusion coefficient. Oral Radiol 2017; doi.org/10.1007/s11282-017-0311-yGoogle Scholar