AI Summary & Key Takeaways
AI InsightHowever, further studies are needed to firmly establish the imaging features of EHNL in predicting prognosis.
📌 3 Key Takeaways
Abstract
Objective: To determine the imaging features of extranodal head and neck lymphoma (EHNL) and their influence on prognosis. Methods: We retrospectively analyzed the clinical and imaging findings of patients who received a diagnosis of EHNL from January 2010 to September 2018. We documented their demographic characteristics and clinical, biochemical, and imaging features. We evaluated the number, location, size, margin, shape, enhancement degree and pattern, local tumor invasiveness, regional lymph node, and presence of necrosis using computed tomography or magnetic resonance imaging. The influence of imaging features on prognosis was assessed using univariate and multivariate logistic regression analyses. Results: Sixty-nine patients with EHNL (male/female: 39/30; mean age ± SD: 59.3±17 years; age range: 18-87 years) were included. The most frequent histological type was non-Hodgkin’s lymphoma (97.1%) with diffuse large B-cell lymphoma (47.8%) as subtype. Solitary involvement was more frequent (58%). The most commonly involved locations were the Waldeyer’s ring (60.9%) and sinonasal region (13%). Univariate analysis revealed that tumor size of 5 cm or larger, ill-defined margin, irregular shape, presence of local invasion, presence of necrosis, and heterogeneous irregular enhancement were more frequent in patients with a poor prognosis (P < .05). In contrast, multivariate analysis revealed that all these factors independently had no significant influence on prognosis. Conclusion: Radiological characteristics of tumor including size, margin, shape, contrast enhancement pattern, local tumor invasiveness, and presence of necrosis impacted prognosis in univariate analysis but not in multivariate analysis. However, further studies are needed to firmly establish the imaging features of EHNL in predicting prognosis.