Primary aim of this study was to assess if subtraction maps generated using CE T1-weighted, non-enhanced T1-weighted and T2-weighted images offered better contrast in differentiating tumor and edema from normal appearing white matter (NAWM) as compared to traditionally acquired anatomic, diffusion tensor imaging (DTI), perfusion weighted imaging (PWI) and MR spectroscopy imaging (MRSI) sequences.The study involved retrospective data analysis of 46 subjects with untreated gliomas histologically verified with World Health Organization classifications of grade II (n = 18), III (n = 11) and IV (n = 17). Subjects underwent a 50-minute MR imaging protocol at 3T (Signa HDxt; GE Healthcare, Milwaukee, Wisconsin) comprising of pre- and post-CE T1-weighted MR, DTI, CE perfusion measurement (DCE-MRI), T2-weighted MR imaging, and whole-brain MRSI. Details of subject selection and imaging methods are previously reported [1, 2]. Maps were generated by digital subtraction of non-enhanced T1-weighted images from Contrast Enhanced (CE) T1-weighted images (ΔT1 map) and non-enhanced T1-weighted images from T2-weighted images (ΔT2 map). Prior to subtraction images were Gaussian normalized (GN) and spatially registered. Figure 1 shows subtraction images for a subject with a grade IV glioma. Manually drawn regions of interest (ROI) were positioned in (1) NAWM in the contralateral hemisphere to the gross tumor, (2) enhancing tumor region (ER) as seen on CE T1-weighted imaging, (3) hyperintense regions (HR) on T2 images located in the gross tumor volume but not in the enhancing or necrotic regions, (4) necrotic region (NR), (5) immediate peritumoral region (IPR) defined as a 1 cm wide band around the enhancing region, and (6) distal peritumoral region (DPR) defined as a band approximately 2 -3 cm away from the enhancing region. ROIs drawn on CE T1-weighted images and T2-weighted images were transferred to DTI maps (ADC, FA), PWI CBV map, MRSI maps (Cho/Cr, NAA/Cr) and generated subtraction maps, which were all registered to the pre-contrast T1-weighted imaging using the MIDAS software (http://mrir.med.miami.edu) [3, 4]. Mean intensity for each MR map within study ROIs was calculated. Relative signal contrast (RSC) was estimated as the difference in the mean intensities between the ROI under consideration and contralateral NAWM. One way analysis of variance (ANOVA) was used to estimate if mean calculated RSC for a particular tissue type was significantly different across image types with post-hoc analysis carried out with Tukey's test for pair-wise comparisons.In Figure 2 is shown the mean RSC for all image series and for each of the six contrasts, accounting for tumor grade. ΔT1 maps offer significantly higher contrast as compared to other parametric maps in differentiating the ER from contralateral NAWM (p < 0.001). Tukey's pair-wise comparisons demonstrated that CBV, Cho/Cr and ΔT2 maps all provided equal contrast for differentiating ER from NAWM (p > 0.05). In differentiating edematous regions from NAWM it was found that ΔT2 maps offer the highest contrast (p < 0.001) with significantly higher contrasts in high grade tumors as compared to low grade tumor. Although subtraction maps using T2-weighted (ΔT2) and T1-weighted (ΔT1) do offer the highest contrast in distinguishing IPR and DPR from NAWM, respectively, they fail to reach a significance level of 0.05 on ANOVA analysis. For Grade II and Grade III tumors, ΔT2 maps provided the highest contrast in differentiating IPR from NAWM, however, for grade IV tumors CBV maps provided the highest optical contrast among all imaging modalities. In discriminating between ER and Edema ΔT1 maps provide excellent contrast as compared to other parametric maps (p < 0.001). Moreover, it is seen that in contrasts involving ER (ER versus NAWM and ER versus Edema) CBV maps provide the second highest mean RSC among the different parametric maps, only second to ΔT1.The main finding of this study was that subtraction maps generated using a combination of pre- and post-contrast T1-weighted imaging and T2-weighted imaging provided better contrast in identifying various regions of the gross tumor area than other parametric images/maps generated using DTI, PWI or MRSI.