Efficacy of Diffusion-Weighted Imaging for the Differentiation between Lymphomas and Carcinomas of the Nasopharynx and Oropharynx: Correlations of Apparent Diffusion Coefficients and Histologic Features
Open Access
- 15 December 2011
- journal article
- Published by American Society of Neuroradiology (ASNR) in American Journal Of Neuroradiology
- Vol. 33 (4), 761-766
- https://doi.org/10.3174/ajnr.a2834
Abstract
BACKGROUND AND PURPOSE: ADCs may help distinguish benign from malignant head and neck diseases. We sought to evaluate the effectiveness of ADC for differentiating between carcinomas and lymphomas of the nasopharynx and oropharynx. MATERIALS AND METHODS: We retrospectively compared the ADCs between 24 histologically proved lymphomas and 32 carcinomas, including 8 NPCs and 7 lymphomas of the nasopharynx, and 24 SCCs and 17 lymphomas of the oropharynx. ADCs were determined on tumor-by-tumor (overall ADCs) and pixel-by-pixel (ADC mapping) bases by using 2 b-values (500 and 1000 s/mm2). RESULTS: Lymphomas and oropharyngeal SCCs had unique histologic features in terms of keratinization, cell attenuation, stromal areas, and necrosis and had distinctive ADCs (0.503 ± 0.099 × 10−3 mm2/s for lymphomas and 0.842 ± 0.164 × 10−3 mm2/s for SCCs). However, NPCs and lymphomas were similar in terms of these histologic features, exhibiting comparable ADCs (0.567 ± 0.057 × 10−3 mm2/s for NPCs and 0.528 ± 0.094 × 10−3 mm2/s for lymphomas). Poorly and moderately differentiated SCCs with homogeneous T2 signals were indistinguishable from lymphomas on conventional MR images; however, ADCs of these SCC subtypes were significantly larger than those of lymphomas. ADC mapping profiles with respect to percentage of tumor areas of extremely low, intermediate, and high ADC levels were well-correlated with the histologic features of lymphomas, NPCs, and different types of SCCs. CONCLUSIONS: The effectiveness of ADC-based differentiation between lymphomas and carcinomas of the nasopharynx and oropharynx depends on their histologic characteristics.Keywords
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