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Pre-treatment apparent diffusion coefficient mapping: differentiation of benign from malignant laryngeal lesions

Published online by Cambridge University Press:  08 January 2015

M S Taha ,
M Amir ,
O Hassan ,
R Sabra ,
T Taha  and
M A Riad
M S Taha
Affiliation:
Department of Otorhinolaryngology, Ain Shams University, Cairo, Egypt
M Amir*
Affiliation:
Department of Otorhinolaryngology, Ain Shams University, Cairo, Egypt
O Hassan
Affiliation:
Department of Otorhinolaryngology, Ain Shams University, Cairo, Egypt
R Sabra
Affiliation:
Department of Otorhinolaryngology, Ain Shams University, Cairo, Egypt
T Taha
Affiliation:
Department of Radiodiagnosis, Ain Shams University, Cairo, Egypt
M A Riad
Affiliation:
Department of Otorhinolaryngology, Ain Shams University, Cairo, Egypt
*
Address for correspondence: Dr Mohamed Amir, 38 Mahmoud Khairy Street, Nasr City, Cairo, Egypt Fax:+ 202 24013835 E-mail: [email protected]
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Abstract

Objective:

To determine whether a threshold apparent diffusion coefficient value may help to differentiate laryngeal carcinomas from benign lesions.

Methods:

Fifty-three patients with laryngeal masses were recruited; four of them were excluded because of susceptibility artefacts. In the remaining 49 patients, the pathological results showed 32 laryngeal carcinomas and 17 benign lesions. The diagnostic value of diffusion-weighted magnetic resonance imaging for the identification of malignant lesions was determined. In addition, the agreement between diffusion-weighted magnetic resonance imaging and histopathology was assessed. Moreover, the sensitivity, specificity, and negative and positive predictive values of the apparent diffusion coefficient in detecting benign and malignant lesions were analysed. An apparent diffusion coefficient histogram was also produced.

Results:

An apparent diffusion coefficient value of 1.1 × 10−3 mm2/second produced the best result when used as the cut-off point to differentiate malignant from benign masses.

Conclusion:

An apparent diffusion coefficient threshold of 1.1 × 10−3 mm2/second is optimal for distinguishing laryngeal carcinomas from benign lesions. Apparent diffusion coefficient values were lower for patients with laryngeal carcinomas than for those with benign lesions.

Keywords

Laryngeal NeoplasmsDiagnosisPathologyDiffusion Weighted MRI
Type
Main Articles
Information
The Journal of Laryngology & Otology , Volume 129 , Issue 1 , January 2015 , pp. 57 - 62
Copyright
Copyright © JLO (1984) Limited 2015 

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References

1Wang, J, Takashima, S, Takayama, F, Kawakami, S, Saito, A, Matsushita, T et al. Head and neck lesions: characterization with diffusion-weighted echo-planar MR imaging. Radiology 2001;220:621–30Google Scholar
2Sumi, M, Sakihama, N, Sumi, T, Morikawa, M, Uetani, M, Kabasawa, H et al. Discrimination of metastatic cervical lymph nodes with diffusion-weighted MR imaging in patients with head and neck cancer. AJNR Am J Neuroradiol 2003;24:1627–34Google Scholar
3Habermann, CR, Gossrau, P, Graessner, J, Arndt, C, Cramer, MC, Reitmeier, F et al. Diffusion-weighted echo-planar MRI: a valuable tool for differentiating primary parotid gland tumors? Rofo 2005;177:940–5CrossRefGoogle ScholarPubMed
4Schafer, J, Srinivan, A, Mukherji, S. Diffusion magnetic resonance imaging in the head and neck. Magn Reson Imaging Clin N Am 2011;19:55–67CrossRefGoogle ScholarPubMed
5Thoeny, HC. Diffusion-weighted MRI in head and neck radiology: applications in oncology. Cancer Imaging 2011;10:209–14Google Scholar
6Razek, AA. Diffusion-weighted magnetic resonance imaging of head and neck. J Comput Assist Tomogr 2010;34:808–15Google Scholar
7Vandecaveye, V, De Keyzer, F, Dirix, P, Lambrecht, M, Nuyts, S, Hermans, R. Applications of diffusion-weighted magnetic resonance imaging in head and neck squamous cell carcinoma. Neuroradiology 2010;52:773–84Google Scholar
8Perrone, A, Guerrisi, P, Izzo, L, D'Angeli, I, Sassi, S, Mele, LL et al. Diffusion-weighted MRI in cervical lymph nodes: differentiation between benign and malignant lesions. Eur J Radiol 2011;77:281–6Google Scholar
9Vandecaveye, V, Dirix, P, De Keyzer, F, Op de Beeck, K, Vander Poorten, V, Hauben, E et al. Diffusion-weighted magnetic resonance imaging early after chemoradiotherapy to monitor treatment response in head-and-neck squamous cell carcinoma. Int J Radiat Oncol Biol Phys 2012;82:1098–107Google Scholar
10Rashed, L, Elwan, S, Abdurrahman, L, El-Fiky, L, Shehata, M, Basyouni, R. The added value of DW-MRI in characterization of tissues in treated head and neck tumors. Egyptian Journal of Ear, Nose, Throat and Allied Sciences 2010;11:35–40Google Scholar
11Galbán, S, Lemasson, B, Williams, TM, Li, F, Heist, KA, Johnson, TD et al. DW-MRI as a biomarker to compare therapeutic outcomes in radiotherapy regimens incorporating temozolomide or gemcitabine in glioblastoma. PloS One 2012;7:e35857CrossRefGoogle ScholarPubMed
12Thoeny, HC, De Keyzer, F, King, AD. Diffusion-weighted MR imaging in the head and neck. Radiology 2012;263:19–32Google Scholar
13Tshering Vogel, DW, Zbaeren, P, Geretschlaeger, A, Vermathen, P, De Keyzer, F, Thoeny, HC. Diffusion-weighted MR imaging including bi-exponential fitting for the detection of recurrent or residual tumour after (chemo)radiotherapy for laryngeal and hypopharyngeal cancers. Eur Radiol 2013;23:562–9Google Scholar
14Hatakenaka, M, Nakamura, K, Yabuuchi, H, Shioyama, Y, Matsuo, Y, Ohnishi, K 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;81:339–45Google Scholar
15de Bree, R, van, derPutten, L, Brouwer, J, Castelijns, JA, Hoekstra, OS, Leemans, CR. Detection of locoregional recurrent head and neck cancer after (chemo)radiotherapy using modern imaging. Oral Oncol 2009;45:386–93CrossRefGoogle ScholarPubMed
16Vandecaveye, V, de Keyzer, F, Vander Poorten, V, Deraedt, K, Alaerts, H, Landuyt, W et al. Evaluation of the larynx for tumour recurrence by diffusion-weighted MRI after radiotherapy: initial experience in four cases. Br J Radiol 2006;79:681–7CrossRefGoogle ScholarPubMed
17Abdel Razek, AA, Gaballa, G, Elhawarey, G, Megahed, AS, Hafez, M, Nada, N. Characterization of pediatric head and neck masses with diffusion-weighted MR imaging. Eur Radiol 2009;19:201–8CrossRefGoogle ScholarPubMed
18Mackinnon, A. A spreadsheet for the calculation of comprehensive statistics for the assessment of diagnostic tests and inter-rater agreement. Comput Biol Med 2000;30:127–34Google Scholar
19Altman, DG. Practical Statistics for Medical Research. London: Chapman and Hall, 1991Google Scholar
20Taha, MS, Hassan, O, Amir, M, Taha, T, Riad, MA. Diffusion-weighted MRI in diagnosing thyroid cartilage invasion in laryngeal carcinoma. Eur Arch Otorhinolaryngol 2014;271:2511–16CrossRefGoogle ScholarPubMed
21Stejskal, EO, Tanner, J. Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J Chem Phys 1965;42:288–92Google Scholar
22Le Bihan, D, Breton, E, Lallemand, D, Aubin, ML, Vignaud, J, Laval-Jeantet, M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497–505CrossRefGoogle ScholarPubMed
23Srinivasan, A, Dvorak, R, Perni, K, Rohrer, S, Mukherji, SK. Differentiation of benign and malignant pathology in the head and neck using 3T apparent diffusion coefficient values: early experience. AJNR Am J Neuroradiol 2008;29:40–4Google Scholar
24Sasaki, M, Eida, S, Sumi, M, Nakamura, T. Apparent diffusion coefficient mapping for sinonasal diseases: differentiation of benign and malignant lesions. AJNR Am J Neuroradiol 2011;32:1100–6Google Scholar
25Eida, S, Sumi, M, Sakihama, N, Takahashi, H, Nakamura, T. Apparent diffusion coefficient mapping of salivary gland tumors: prediction of the benignancy and malignancy. AJNR Am J Neuroradiol 2007;28:116–21Google ScholarPubMed
26Shang, DS, Ruan, LX, Zhou, SH, Bao, YY, Cheng, KJ, Wang, QY. Differentiating laryngeal carcinomas from precursor lesions by diffusion-weighted magnetic resonance imaging at 3.0 T: a preliminary study. PLoS One 2013;8:e68622CrossRefGoogle ScholarPubMed