2011
DOI: 10.3174/ajnr.a2581
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Differentiation of Brain Abscesses from Necrotic Glioblastomas and Cystic Metastatic Brain Tumors with Diffusion Tensor Imaging

Abstract: BACKGROUND AND PURPOSE:The differentiation of abscesses from glioblastomas and metastases may not always be possible on the basis of DWI. Our hypothesis was that differences in diffusion properties as detected by DTI allow differentiation of abscess from glioblastomas and metastasis. Furthermore, diagnostic performance of tensor metrics quantifying anisotropy or tensor shapes is better than that of ADC in measuring mean diffusivity for this purpose.

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Cited by 89 publications
(71 citation statements)
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“…11,12 The third type is focused on 3 locations: the enhancing part of the tumor, regions with peritumoral T2 prolongation, and the necrotic areas within the tumor. 7 With regard to the enhancing part of the tumor, DTI and perfusion metrics showed inconsistent conclusions, with some authors believing there was no difference between the 2 types of tumors, 10,13,16 contrary to the others. 6,8,14,15 As for the peritumoral T2 prolongation, the results were also controversial.…”
Section: Figmentioning
confidence: 99%
See 1 more Smart Citation
“…11,12 The third type is focused on 3 locations: the enhancing part of the tumor, regions with peritumoral T2 prolongation, and the necrotic areas within the tumor. 7 With regard to the enhancing part of the tumor, DTI and perfusion metrics showed inconsistent conclusions, with some authors believing there was no difference between the 2 types of tumors, 10,13,16 contrary to the others. 6,8,14,15 As for the peritumoral T2 prolongation, the results were also controversial.…”
Section: Figmentioning
confidence: 99%
“…2,3 Therefore, it is thought to be very difficult to distinguish between these 2 types of tumors with routine MR imaging alone. [4][5][6] Many studies have focused on other advanced MR imaging modalities, such as DTI, 3,5,7,8 DWI, 9,10 PWI, 6,[11][12][13][14][15][16] and MR spectroscopy, 17 to explore the differentiating characteristics.…”
mentioning
confidence: 99%
“…FA and ADC were calculated from diffusion-tensor data by use of standard algorithms described previously. 5,12,13 The CBV for each voxel was estimated by integrating the relaxivity-time curve converted from the dynamic signal intensity curve. Contrast leakage correction was performed by use of a technique outlined by Boxerman et al 14,15 …”
Section: Image Postprocessingmentioning
confidence: 99%
“…Using different measurements and patterns generated from these measurements, obtained through processing of the DTI data, researchers found that differences in the enhancing rim could differentiate glioblastoma from metastasis and that differences in the cystic cavity could be used to identify abscess from these other disease entities. 43 DTI has been used in a similar fashion to differentiate primary CNS lymphoma from glioblastoma 46 and atypical from classic meningioma. 44,47 Measurements obtained from DTI data have been used to measure cellularity and tumor infiltration and to determine astrocytic tumor grade.…”
Section: Diffusion Mri In Tumor Diagnosis and Gradingmentioning
confidence: 99%
“…DTI has also been used to delineate among abscesses, cystic metastases, and necrotic glioblastomas. 43 Because DTI allows for visualization of fiber tracts, it can also be helpful for surgical planning, especially when a large mass has displaced the fiber tracts. 44 It may also be useful for a more precise sculpting of the boost radiation in intensity-modulated radiation treatment planning.…”
Section: Diffusion Mrimentioning
confidence: 99%