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A Study on Clinical Characteristics and Magnetic Resonance Imaging Manifestations on Systemic Rosai-Dorfman Disease.

Chinese Medical Journal 2018 Februrary 21
Background:: Rosai-Dorfman disease (RDD) is typically characterized by painless bilateral and symmetrical cervical lymphadenopathy, with associated fever and leukocytosis. The aim of the current study was to summarize the clinical features and imaging characteristics of RDD, in an effort to improve its diagnostic accuracy.

Methods: The study was analyzed from 32 patients between January 2011 and December 2017; of these, 16 patients had pathologically diagnosed RDD, eight had pathologically diagnosed meningioma, and eight pathologically diagnosed lymphoma. All patients underwent computed tomography and magnetic resonance imaging (MRI). Clinical features and imaging characteristics of RDD were analyzed retrospectively. The mean apparent diffusion coefficient (ADC) values of lesions at different sites were measured, and one-way analysis of variance and the least significant difference t-test were used to compare the differences between groups and draw receiver operating characteristic curves. The tumors were excised for biopsy and analyzed using immunohistochemistry.

Results:: The mean ADCs were (0.81 ± 0.10) × 10-3 mm2 /s for intercranial RDD, (0.73 ± 0.05) × 10-3 mm2 /s for nasopharyngeal RDD, (0.74 ± 0.11) × 10-3 mm2 /s for bone RDD, and (0.71 ± 0.04) × 10-3 mm2 /s for soft-tissue RDD. The optimum ADC to distinguish intracranial RDD from lymphoma was 0.79 × 10-3 mm2 /s (62.5% sensitivity and 100% specificity) and to distinguish meningioma from intracranial RDD was 0.92 × 10-3 mm2 /s (62.5% sensitivity and 100% specificity). Levels of C-reactive protein, erythrocyte sediment rate and D-dimer were significantly elevated (81%, 87%, and 75%, respectively). On immunohistochemistry, RDD was positive for both S-100 and CD68 proteins but negative for CD1a.

Conclusions:: Conventional MRI, combined with diffusion-weighted imaging and ADC mapping, is an important diagnostic tool in evaluating RDD patients. An accurate diagnosis of RDD should consider the clinical features, imaging characteristics, and the pathological findings.

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