Literature DB >> 11734370

Discrimination of an infected brain tumor from a cerebral abscess by combined MR perfusion and diffusion imaging.

J H M Chan1, E Y K Tsui, L F Chau, K Y Chow, M S M Chan, M K Yuen, T L Chan, W K Cheng, K P C Wong.   

Abstract

The aim of this study was to investigate the signal characteristics of the abscess wall and tumor wall on diffusion-weighted and perfusion-weighted images and thus to evaluate the feasibility of using combined MR diffusion and perfusion imaging to differentiate pyogenic cerebral abscess from infected brain tumor. The tumor wall of various types of cystic or necrotic brain tumor was significantly hyperintense relative to that of cerebral abscess wall on both diffusion-weighted images and regional cerebral blood volume maps. Sixteen patients who had cerebral masses with large cystic or necrotic cavities were imaged to generate diffusion-weighted images and regional cerebral blood volume maps using single-shot echoplanar imaging (EPI) pulse sequences. Apart from qualitative analysis, apparent diffusion coefficients (ADC) as well as regional cerebral blood volume (rCBV) ratios were calculated from the abscess wall and peripheral tumor wall and comparison was made by using Student's t-test. The tumor wall of various types of cystic or necrotic brain tumor had significantly lower ADCs relative to those of the abscess wall (P<0.005) and thus appeared relatively hyperintense on diffusion-weighted images. The mean rCBV ratio relative to normal white matter (2.90+/-0.62) of the peripheral tumor wall of various types of cystic or necrotic brain tumor were significantly larger than the mean rCBV ratio (0.45+/-0.11) of the pyogenic cerebral abscess wall (P<0.001) by Student's t-test. It is concluded that the combined MR diffusion and perfusion imaging might be capable of differentiating an infected brain tumor from a pyogenic cerebral abscess.

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Year:  2002        PMID: 11734370     DOI: 10.1016/s0895-6111(01)00023-4

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


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