Cervical lymphadenopathy: can the histogram analysis of apparent diffusion coefficient help to differentiate between lymphoma and squamous cell carcinoma in patients with unknown clinical primary tumor?

Abstract

Purpose: To retrospectively evaluate the value of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating between lymphoma and metastatic squamous cell carcinoma (SCC) of unknown clinical primary in neck nodes. Methods: A total of 39 patients, 20 affected by lymphoma and 19 affected by metastatic non-nasopharyngeal SCC, were included in this retrospective study. All patients underwent MR imaging with a 1.5 T scanner system, including diffusion-weighted imaging (DWI) with three different b values (b = 0, 500 and 800 s/mm2). The entire tumor volume was manually delineated on the ADC maps, using the T2-weighted images and DWIs with b = 800 s/mm2 as a guide to the lesion location. The Mann–Whitney rank-sum test for independent samples was performed to compare the histogram parameters of patients with lymphoma and SCC. Results: The SCCs showed significantly higher median ADC (ADCmedian) and mean ADC (ADCmean) values, compared to lymphomas (p < 0.001), while they exhibited lower kurtosis and skewness without reaching significance (p = 0.066 and 0.148, respectively). The ADCmean and ADCmedian had the best discriminative powers for differentiating lymphoma and SCC, with an area under the curve of 87% and 85%, respectively. The optimal cutoff values for ADCmean and ADCmedian as predictors for lymphoma were ≤ 0.83 × 10−3 mm2/s and ≤ 0.73 × 10−3 mm2/s, respectively. Conclusions: The whole-lesion ADC histogram analysis of cervical lymphadenopathy may help to discriminate lymphomas from non-nasopharyngeal SCC in patients with unknown clinical primary tumor.