In transforming low-grade glioma, susceptibility-weighted MR perfusion imaging can demonstrate significant increases in rCBV up to 12 months before contrast enhancement is apparent on T1-weighted MR images.

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Six-month tumor growth helps predict outcome in patients with LGG better than parameters derived from perfusion- or diffusion-weighed MR imaging. Tumor growth can readily be calculated from volume measurements on images acquired with standard MR imaging protocols and may well prove most useful among various MR imaging findings in clinical practice.

SUMMARY:We assessed the influence of inclusion (method 1) and exclusion (method 2) of intratumoral vessels when determining maximum relative cerebral blood volume (rCBVmax) in 3 types of low-grade gliomas (LGGs): astrocytomas, oligoastrocytomas, and oligodendrogliomas. Method 1 yielded significantly higher mean rCBVmax than method 2. However, only method 2 demonstrated a significant (P ϭ .026) association between rCBVmax and membership of a differently ranked histologic category. Exclusion of intratumoral vessels appears, therefore, preferable when determining rCBVmax in LGGs. Dynamic susceptibility contrast-enhanced (DSC) MR perfusion imaging has become an important technique for studying brain tumors. Intratumoral relative cerebral blood volume (CBV [rCBV]) correlates with histologic and angiographic measures of tumor vascularity, 1 helps predict the histologic grade of gliomas, 2 and correlates with outcome in lowgrade gliomas (LGGs).3 High-grade gliomas usually have a higher rCBV than low-grade tumors, but rCBVs may also be elevated in low-grade oligodendrogliomas (ODs), 4 which confounds tumor grading. 5Techniques of data acquisition, postprocessing, and analysis influence rCBV measurements. Gradient-echo echo-planar imaging (GE-EPI) pulse sequences are more sensitive to larger vessels than spin-echo echo-planar imaging (SE-EPI) methods and provide better differentiation between histopathologic tumor grades. 6 Wetzel et al 7 found that interobserver and intraobserver reproducibility for intratumoral rCBV were best when the highest CBV from several regions of interest (ROIs) was chosen and highlighted the importance of excluding large vessels. Inclusion or exclusion of intratumoral vessels is often not explicitly stated in glioma perfusion studies, though some investigators focused on excluding peritumoral vessels. 6 The significance of intratumoral vessels for rCBV measurements has, to our knowledge, not been formally examined.Here we studied the influence of intratumoral vessels on rCBV characterization in 3 histologic categories of low-grade glial tumors: astrocytomas (ACs), ODs, and oligoastrocytomas (OAs). Technique and Results Thirty-four patients withLGGs, composed of 21 ACs, 8 ODs, and 5 OAs, had DSC GE-EPI (TR ϭ 1200 ms; TE ϭ 40 ms; flip angle ϭ 20°; FOV ϭ 26 cm; matrix ϭ 96 ϫ 128; section thickness ϭ 5 mm) at 1.5T (GE Signa Horizon Echospeed LX9.1; GE Healthcare, Waukesha, Wis) with a bolus of 0.1 mmol/kg of body weight of gadoterate meglumine at 5 mL/s. Color maps of rCBV were generated with FuncTool 1.9 (GE Healthcare) and analyzed by 2 neuroradiologists (H.R.J. and G.B.C., with 15 and 7 years of experience, respectively), reaching a consensus for placement of ROIs. At least 6 intratumoral ROIs with a size of 9 pixels were placed over areas showing mostly elevated CBV on color perfusion maps. Blood vessels within the tumor were identified on unprocessed perfusion images acquired between the time points of maximum arterial and venous signal intensity drop. Sections above and below intratumoral ves...

Object The consistency of parametric registration in multitemporal magnetic resonance (MR) imaging studies was evaluated. Materials and methods Serial MRI scans of adult patients with a brain tumor (glioma) were aligned by parametric registration. The performance of low-order spatial alignment (6/9/12 degrees of freedom) of different 3D serial MR-weighted images is evaluated. A registration protocol for the alignment of all images to one reference coordinate system at baseline is presented. Registration results were evaluated for both, multimodal intra-timepoint and mono-modal multi-temporal registration. The latter case might present a challenge to automatic intensity-based registration algorithms due to ill-defined correspondences. The performance of our algorithm was assessed by testing the inverse registration consistency. Four different similarity measures were evaluated to assess consistency. A. Mang (B) · T. M. BuzugResults Careful visual inspection suggests that images are well aligned, but their consistency may be imperfect. Subvoxel inconsistency within the brain was found for all similarity measures used for parametric multi-temporal registration. T1-weighted images were most reliable for establishing spatial correspondence between different timepoints. Conclusions The parametric registration algorithm is feasible for use in this application. The sub-voxel resolution mean displacement error of registration transformations demonstrates that the algorithm converges to an almost identical solution for forward and reverse registration.