CC BY-NC-ND 4.0 · Int Arch Otorhinolaryngol 2017; 21(04): 358-365
DOI: 10.1055/s-0036-1597323
Original Research
Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil

Differentiating Benign from Malignant Sinonasal Lesions: Feasibility of Diffusion Weighted MRI

Khaled M. El-Gerby
1   Radiodiagnosis Department, Faculty of Medicine, Zagazig University, Zagazig, Egypt
,
Mohammad Waheed El-Anwar
2   Department of Otorhinolaryngology Head and Neck Surgery, Faculty of Medicine, Zagazig University, Zagazig, Egypt
› Author Affiliations
Further Information

Publication History

14 August 2016

06 October 2016

Publication Date:
04 January 2017 (online)

Abstract

Introduction Appearance of nasal masses on routine CT and MRI are not pathognomonic. We utilized the apparent diffusion coefficient (ADC) value obtained from diffusion weighted image (DWI) to detect the differences in the microstructures of tumor and non-tumor tissues.

Objective The objective of our study was to evaluate the diagnostic role of DWI and ADC values in differentiating between malignant and benign sinonasal lesions and its correlation with histopathological results as the reference standard.

Methods Patients with nasal and / or paranasal mass underwent CT, MRI, and DWI before any surgical intervention. We used diagnostic sinonasal endoscopy and biopsy to confirm the diagnosis after MRI.

Results When we used ADC value of (1.2 × 10–3 mm2/s) as a cut-off value for differentiating benign from malignant sinonasal lesions, we achieved 90% accuracy, 100% sensitivity, 88.4% specificity, 77.8% positive predictive value, and 100% negative predictive value. At this cut-off, benign lesions show statistically significant higher ADC value than malignant tumors.

Conclusion DW MRI and ADC value calculation are promising quantitative methods helping to differentiate between malignant and benign sinonasal lesions. Thus, they are effective methods compared with other conventional methods with short imaging time thus it is recommended to be incorporated into routine evaluations.

 
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