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Evaluation of mediastinal lymphadenopathy by diffusion weighted MRI; correlation with histopathological results. | LitMetric

Introduction: Diffusion weighted imaging (DWI) has shown its potential as a reliable noninvasive technique for tissue characterization. DWI reflects the tissue specific diffusion capacity which can be used for tissue characterization. Hypercellular tissue (e.g; malignant tumors) had restricted diffusion capacity with increased signals on DWI and low ADC values. Non-tumoral tissues show low cellularity, and diffusion capacity is not restricted resulting in signal loss on DWI and high apparent diffusion coefficient (ADC). Differential diagnosis of mediastinal lymphadenopathy is an issue of debate, especially in malignant benign differentiation. Diffusion weighted imaging with magnetic resonance could improve the diagnostic accuracy in differentiation between benign and malignant mediastinal nodes.

Objectives: to determine the efficacy of diffusion weighted MRI in evaluation of mediastinal lymphadenopathy with histopathological correlation to differentiate benign from malignant lymph nodes.

Material And Methods: 30 patients with mediastinal lymphadenopathy underwent diffusion weighted MRI. ADCs of lymph nodes were derived and constructed from b = 0 and b = 1000 sec/mm2 values by drawing regions of interests (ROI). Consequently, mediastinal nodes were studied, biopsies and histopathological analysis were done after MRI examination.

Results: The best cutoff point of ADC to differentiate benign from malignant lesions was 1.15 mm/sec (sensitivity 77%, specificity 92% and AUC 81.4%). Significant negative correlation of ADC by DW MRI and the size of the LNs. The mean ADC values in the lymphoma group was lower than in the sarcoidosis group, and the difference was statistically significant.

Conclusion: The study supports that MRI with diffusion weighted images can differentiate benign from malignant mediastinal lymphadenopathy and differentiate lymphoma from sarcoidosis non-invasively.

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http://dx.doi.org/10.5603/ARM.2019.0033DOI Listing

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