ABSTRACT

BACKGROUND AND PURPOSE: Glioblastomas, brain metastases, and PCLs may have similar enhancement patterns on MR imaging, making the differential diagnosis difficult or even impossible. The purpose of this study was to determine whether a combination of DTI and DSC can assist in the differentiation of glioblastomas, solitary brain metastases, and PCLs.

Hypoxia is known to be an important prognostic marker in many human cancers. We report the use of two oxygen measurement techniques in human brain tumors and compare these data with semiquantitative histological end points. Oxygenation was measured using the Eppendorf needle electrode and/or EF5 binding in 28 brain tumors. These data were compared with necrosis, mitosis, and endothelial proliferation. In some tumors, absolute EF5 binding was converted to tissue pO 2 based on in vitro calibrations. Eppendorf electrode readings could not be used to identify WHO grade 1/2 versus WHO grade 3/4 tumors, they could not differentiate grade 3 versus grade 4 glial-derived neoplasms, nor did they correlate with necrosis or endothelial proliferation scores. EF5 binding increased as the tumor grade increased and was significantly associated with necrosis and endothelial proliferation. There was no statistically significant correlation between the two hypoxia detection techniques, although both methods indicated similar absolute ranges of tissue pO 2 . There was substantial inter-and intratumoral heterogeneity of EF5 binding in WHO grade 4 glial neoplasms. The majority of cells in glial-derived tumor had levels of hypoxia that were mild to moderate (defined herein as 10% to 0.5% pO 2 ) rather than severe (defined as approximately 0.1% pO 2 ). Immunohistochemical detection of EF5 binding tracks histological parameters in adult brain tumors, with increased binding associated with increasing necrosis and endothelial proliferation. The proportion of moderately to severely hypoxic cells is relatively low, even in the high-grade tumors. Human brain tumors are dominated by oxic to moderately hypoxic cells.

The purpose of this study is to determine whether diffusion tensor imaging (DTI) metrics including tensor shape measures such as linear and planar anisotropy coefficients (CL and CP) can help differentiate glioblastomas from solitary brain metastases. Sixty-three patients with histopathologic diagnosis of glioblastomas (22 men, 16 women, mean age 58.4 years) and brain metastases (13 men, 12 women, mean age 56.3 years) were included in this study. Contrast-enhanced T1-weighted, fluid attenuated inversion recovery (FLAIR) images, fractional anisotropy (FA), apparent diffusion coefficient (ADC), CL and CP maps were co-registered and each lesion was semi-automatically subdivided into four regions: central, enhancing, immediate peritumoral and distant peritumoral. DTI metrics as well as the normalized signal intensity from the contrast-enhanced T1-weighted images were measured from each region. Univariate and multivariate logistic regression analyses were employed to determine the best model for classification. The results demonstrated that FA, CL and CP from glioblastomas were significantly higher than those of brain metastases from all segmented regions (p < 0.05), and the differences from the enhancing regions were most significant (p < 0.001). FA and CL from the enhancing region had the highest prediction accuracy when used alone with an area under the curve of 0.90. The best logistic regression model included three parameters (ADC, FA and CP) from the enhancing part, resulting in 92% sensitivity, 100% specificity and area under the curve of 0.98. We conclude that DTI metrics, used individually or combined, have a potential as a noninvasive measure to differentiate glioblastomas from metastases.

An integrated MR imaging-based strategy, which is accurate in differentiation of several intraaxial brain masses, was proposed.