Purpose: To investigate whether estimates of relative cerebral blood volume (rCBV) in brain tumors, obtained by using dynamic susceptibility-weighted contrast material–enhanced magnetic resonance (...

Purpose: To present comprehensive examinations of the assumptions made in functional diffusion map (fDM) analyses and provide a biological basis for fDM classification.Materials and Methods: Sixty‐nine patients with gliomas were enrolled in this study. To determine the sensitivity of apparent diffusion coefficients (ADCs) to cellularity, cell density from stereotactic biopsy specimens was correlated with preoperative ADC maps. For definition of ADC thresholds used for fDMs, the 95% confidence intervals (CI) for changes in voxel‐wise ADC measurements in normal appearing tissue was analyzed. The sensitivity and specificity to progressing disease was examined using both radiographic and neurological criteria.Results: Results support the hypothesis that ADC is inversely proportional to cell density with a sensitivity of 1.01 × 10⁻⁷ [mm²/s]/[nuclei/mm²]. The 95% CI for white matter = 0.25 × 10⁻³ mm²/s, gray matter = 0.31 × 10⁻³ mm²/s, a mixture of white and gray matter = 0.40 × 10⁻³ mm²/s, and a mixture of white matter, gray matter, and cerebrospinal fluid = 0.75 × 10⁻³ mm²/s. Application of these measurements as ADC thresholds produce varying levels of sensitivity and specificity to disease progression, which were all significantly better than chance.Conclusion: This study suggests fDMs are valid biomarkers for brain tumor cellularity. J. Magn. Reson. Imaging 2010;31:538–548. ©2010 Wiley‐Liss, Inc.

The study goal was to determine whether changes in relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast (DSC) MRI are predictive of overall survival (OS) in patients with recurrent glioblastoma multiforme (GBM) when measured 2, 8, and 16 weeks after treatment initiation. Patients with recurrent GBM (37/123) enrolled in ACRIN 6677/RTOG 0625, a multicenter, randomized, phase II trial of bevacizumab with irinotecan or temozolomide, consented to DSC-MRI plus conventional MRI, 21 with DSC-MRI at baseline and at least 1 postbaseline scan. Contrast-enhancing regions of interest were determined semi-automatically using pre- and postcontrast T1-weighted images. Mean tumor rCBV normalized to white matter (nRCBV) and standardized rCBV (sRCBV) were determined for these regions of interest. The OS rates for patients with positive versus negative changes from baseline in nRCBV and sRCBV were compared using Wilcoxon rank-sum and Kaplan–Meier survival estimates with log-rank tests. Patients surviving at least 1 year (OS-1) had significantly larger decreases in nRCBV at week 2 (P = .0451) and sRCBV at week 16 (P = .014). Receiver operating characteristic analysis found the percent changes of nRCBV and sRCBV at week 2 and sRCBV at week 16, but not rCBV data at week 8, to be good prognostic markers for OS-1. Patients with positive change from baseline rCBV had significantly shorter OS than those with negative change at both week 2 and week 16 (P = .0015 and P = .0067 for nRCBV and P = .0251 and P = .0004 for sRCBV, respectively). Early decreases in rCBV are predictive of improved survival in patients with recurrent GBM treated with bevacizumab.

The anti-VEGF antibody, bevacizumab, is standard treatment for patients with recurrent glioblastoma. In this setting, traditional anatomic MRI methods such as post-contrast T1-weighted and T2-weighted imaging are proving unreliable for monitoring response. Here we evaluate the prognostic significance of pre- and posttreatment relative cerebral blood volume (rCBV) derived from dynamic susceptibility contrast MRI to predict response to bevacizumab. Thirty-six participants with recurrent high-grade gliomas who underwent rCBV imaging 60 days before and 20–60 days after starting bevacizumab treatment were enrolled. Tumor regions of interest (ROIs) were determined from deltaT1 maps computed from the difference between standardized post and precontrast T1-weighted images. Both pre- and posttreatment rCBV maps were corrected for leakage and standardized (stdRCBV) to a consistent intensity scale. The Kaplan–Meier method was used to determine if either the pre- or post-bevacizumab stdRCBV within the tumor ROI was predictive of overall survival (OS) or progression free survival (PFS). The OS was significantly longer if either the pre- (380d vs 175d; P=.0024) or posttreatment stdRCBV (340d vs 186d; P = .0065) was <4400. The posttreatment stdRCBV was also predictive of PFS (167d vs 78d; P = .0006). When the stdRCBV values were both above versus both below threshold, the OS was significantly worse (100.5d vs 395d; P < .0001). With a 32.5% decrease in stdRCBV, the risk of death was reduced by about 68% but increased by 140% with a 29% increase in stdRCBV. Standardized rCBV is predictive of OS and PFS in patients with recurrent high-grade brain tumor treated with bevacizumab.

In an effort to develop MRI methods for the evaluation of tumor angiogenesis (new blood vessel formation), MRI‐derived cerebral blood volume (CBV) information has been compared to histologic measures of microvessel density (MVD). Although MVD is a standard marker of angiogenesis, it is not a direct correlate of the volume measurements made with MRI, and therefore inappropriate for the development and validation of the MR techniques. Therefore, the goal of this study was to develop an approach by which MR measurements of CBV can be directly correlated. To this end, dynamic susceptibility contrast (DSC) MRI experiments were performed in six Fisher rats implanted with 9L gliosarcoma brain tumors. Subsequently, the circulation was perfused with a latex compound (Microfil®), after which 50‐μm tissue sections were analyzed for vessel count, diameter, and the fraction of area comprised of vessels. The results demonstrate that while fractional area (FA) does not provide a good measure of CBV, FA corrected for section thickness effects does. Whereas the FA in normal brain was found to be 13.03 ± 1.83% the corrected FA, or fractional volume (FV), was 1.89 ± 0.39%, a value in agreement with those reported in the literature for normal brain. Furthermore, while no significant difference was found between normal brain and tumor FA (P = 0.55), the difference was significant for FV (P = 0.036), as would be expected. And only with FV does a correlation with the MRI‐derived CBV become apparent (r_S = 0.74). There was strong correlation (r_s = 0.886) between the tumor / normal blood volume ratios as estimated by each technique, although the MR‐ratio (1.56 ± 0.29) underestimated the histologic‐ratio (2.35 ± 0.75). Thus, the correlation of MRI CBV methods requires a measurement of fractional vessel area and correction of this area for section thickness effects. This new independent correlative measure should enable efficient and accurate progress in the development of MRI methods to evaluate tumor angiogenesis. Magn Reson Med 46:735–747, 2001.

Purpose: To examine the effect of low b‐values (0 < b < 50 s/mm²) on the calculation of the intravoxel incoherent motion (IVIM) derived pseudodiffusion parameter in the normal liver.Methods: Simulations were performed to examine the effects of adding low b‐values on the pseudodiffusion parameter. Low b‐values were cumulatively added to the distribution and the IVIM signal was generated with varying pseudodiffusion values. The signal was fit with the IVIM model after the addition of Gaussian noise, and the simulated values were compared with the true values. In addition, the livers of eight control subjects were imaged using respiratory‐triggered DWI. Pseudodiffusion was calculated with and without low b‐values and compared.Results: Pseudodiffusion tended to be underestimated when low b‐values were not included in the b‐value distribution as predicted by simulations and confirmed with in vivo imaging. The number of outlier values was also reduced as more low b‐values were added.Conclusion: In conclusion, this study showed pseudodiffusion in the liver tended to be underestimated when too few low b‐values (0 < b < 50 s/mm²) were included in the distribution. Therefore, it is recommended to include at least two low b‐values when performing liver IVIM studies. Magn Reson Med 73:306–311, 2015.