The role of ADC histogram analysis in the diagnosis of pediatric malignant lymphadenopathy

Abstract

Aim: Lymphadenopathy (LAP) is one of the most common daily practice clinical findings in children. LAPs that involve more than one region and do not decrease with treatment are a significant cause of anxiety for clinicians and families. In this occurence, ultrasonography, which is the primary imaging method, is insufficient in some cases. Our aim is to make histopathological predictions with apparent diffusion coefficient (ADC) histogram analysis. Material and Method: A total of thirty-one patients, seventeen male and fourteen female, who underwent magnetic resonance imaging and were diagnosed histopathologically (with tru-cut or excisional biopsy) were included in our study. Magnetic resonance imagings were evaluated retrospectively. Results: We could not differentiate lymphoma (when considered as a single group), granulomatous LAP and reactive lymphoid hyperplasia with an ADC histogram analysis (p>0.05). However, when the lymphoma subgroups were evaluated separately, we could only distinguish Burkitt’s lymphoma (with ADCmin values) from other pathologies (p<0.05). The optimal cut-off value distinguishing Burkitt’s lymphoma from other groups was 245×10-6 mm2/sec in receiver operating characteristic curve analysis (AUC 0.981, sensitivity 75%, specificity 93%, PPV 67%, NPV 93%). As in recent studies, we did not find significant differences in ADC histogram analysis values of reactive lymphoid hyperplasia, granulomatous LAPs and lymphomas (when considered as a single group). However, when the lymphoma subgroups were considered separately, we were able to distinguish Burkitt’s lymphoma from other subgroups and granulomatous LAP, reactive lymphoid hyperplasia with the ADCmin value. Conclusion: The ADCmin value in pediatric LAPs may contribute to the diagnosis of Burkitt’s lymphoma.

Keywords

• Lymphadenopathy
• magnetic resonance imaging
• histogram analysis
• apparent diffusion coefficient

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