OBJECT: The authors' aim was to assess the ability of @entity1541 ( @entity1541 ) ratios in distinguishing @entity867 from @entity39 . METHODS: Fifty-three @entity1 with rim-enhancing masses in the brain observed on T1-weighted MR images were included: 26 had abscesses (14 bacterial, six nonbacterial, and six of unknown origin), 11 had @entity463 multiforme, and 16 had rim-enhancing @entity3 . The @entity1541 values, derived from diffusion-weighted imaging, were measured in the most homogeneous portion of the cystic component of the mass. The @entity1541 ratios were calculated by dividing the @entity1541 values from the nonenhancing cystic portion of the mass by the @entity1541 values from contralateral normal-appearing white matter. Lesions were further differentiated based on presence, absence, or incompleteness of a T2 hypointensity rim. The mean (+/- standard deviation) @entity1541 ratios were significantly higher in @entity5 than in abscesses (2.45 +/- 0.91 compared with 1.12 +/- 0:53, p < 0.01). The accuracy of @entity1541 ratios in discriminating @entity5 , determined by the area under the receiver operating characteristic curve (Az), was high: 0.91 +/- 0.04 (mean +/- @entity2246 [ @entity2246 ]). The threshold of 1.7 was associated with highest efficiency (87%) in discriminating @entity5 . If only bacterial abscesses were analyzed compared with @entity5 , the Az increased to 0.96 +/- 0.03 ( @entity2246 ). Using @entity1541 ratios and T1 rim characteristics, 50 of 53 lesions were correctly classified (efficiency 94.3%). CONCLUSIONS: The accuracy of @entity1541 ratios in discriminating @entity867 from @entity39 is very high and can be further improved using T2 rim characteristics.

Discrimination of capsular stage @entity867 from necrotic or cystic XXXX using diffusion-weighted magnetic resonance imaging.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity39 :: ('MESH:D009336', 'Disease') :: ['cystic or necrotic neoplasms'] @entity5 :: ('MESH:D009369', 'Disease') :: ['abscesses from neoplasms', 'neoplasms'] @entity1541 :: ('MESH:C536023', 'Disease') :: ['apparent diffusion coefficient', 'ADC'] @entity3 :: ('MESH:D009362', 'Disease') :: ['metastasis'] @entity463 :: ('MESH:D005909', 'Disease') :: ['glioblastoma'] @entity867 :: ('MESH:D001922', 'Disease') :: ['brain abscesses'] @entity2246 :: ('MESH:D008661', 'Disease') :: ['SEM', 'standard error of the mean']
@entity5 :: (MESH:D009369,Disease) :: ['neoplasms']
