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 (ADC_median) and mean ADC (ADC_mean) 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 ADC_mean and ADC_median 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 ADC_mean and ADC_median 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.

Keywords: Diffusion-weighted imaging; Head and neck cancer; Neck nodes; Quantitative imaging.