Findings at presentation in primary CNS diffuse large B-cell lymphoma of the brain: A comparison of immunocompetent and immunodeficient patients

Carolina Sobrido Sampedro, Juan D. Corroto, Mercedes Arias, Juan D. Corroto Murua, Manuela Fontanillo Fontanillo, Alfonso Iglesias Castañón, José Manuel Pumar Cebreiro

Abstract


Background/Objectives: Primary central nervous system lymphoma (PCNSL) is a rare tumour with poor prognosis. Due to the increased number of patients with PCNSL over the past two decades our purpose are to describe magnetic resonance imaging (MRI) and Computed Tomography (CT) findings in (PCNSL) of the brain, and to study the differences between immunocompetent and immunodeficient patients with PCNSL.

Methods: A retrospective, descriptive study was performed with 59 patients diagnosed of PCNSL in two hospitals from 1997 to 2010. Immunocompetent (n=38) and immunodeficient (n=21) patients were compared and differences between both groups were analyzed. Patients were evaluated according to sex, age, median time from clinical symptoms presentation to pathologic diagnosis, clinical symptoms, location, number of lesions, size, MRI and CT characteristics. Significance was defined as p < 0.05.

Results: MRI findings: 50% of lesions in immunocompetent and 52.4% in immunodeficient group were heterogeneous, 89.5% of lesions in immunocompetent and 85,7% in immunodeficient were hypo-isointense on T1WI; 63.2% of lesions in immunocompetent and 76.2% in immunodeficient group were hyperintense on T2WI. CT images: 48.39% of lesions in immunocompetent and 20% in immunodeficient group were hyperdense. Statistically significant differences between immunocompetent and immunodeficient patients were found when evaluating the age (p < 0.000) and median time from clinical symptoms presentation to pathologic diagnosis (p < 0.008).

Conclusions: MRI and CT are able to define imaging characteristics of PCNSL, promoting a quick diagnosis. There are no significant differences between immunocompetent and immunodeficient patients for MR and CT features.

Full Text: PDF DOI: 10.5430/jbgc.v3n4p59

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Journal of Biomedical Graphics and Computing
ISSN 1925-4008 (Print)   ISSN 1925-4016 (Online)
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