Cerebral blood volume measurements by perfusion-weighted MR imaging in gliomas: ready for prime time in predicting short-term outcome and recurrent disease?

Current classification and grading of primary brain tumors has significant limitations. Our aim was to determine whether the relative cerebral volume (rCBV) measurements in gliomas may serve as an adjunct to histopathologic grading, with a hypothesis that rCBV values are more accurate in predicting 1-year survival and recurrence. Thirty-four patients with gliomas (WHO grade I-IV, 27 astrocytomas, 7 tumors with oligodendroglial components) underwent contrast-enhanced MR rCBV measurements before treatment. The region of interest and the single pixel with the maximum CBV value within the tumors were normalized relative to the contralateral normal tissue (rCBV(mean) and rCBV(max), respectively). Karnofsky performance score and progression-free survival (PFS) were recorded. Receiver operating characteristic curves and Kaplan-Meier survival analysis were conducted for CBV and histologic grade (WHO grade). Significant correlations were detected only when patients with oligodendrogliomas and oligoastrocytomas were excluded. The rCBV(mean) and rCBV(max) in the astrocytomas were 3.5 +/- 2.9 and 3.7 +/- 2.7. PFS correlated with rCBV parameters (r = -0.54 to -0.56, P < or = .009). WHO grade correlated with rCBV values (r = 0.65, P < or = .0002). rCBV(max) > 4.2 was found to be a significant cutoff value for recurrence prediction with 77.8% sensitivity and 94.4% specificity (P = .0001). rCBV(max) < or = 3.8 was a significant predictor for 1-year survival (93.7% sensitivity, 72.7% specificity, P = .0002). The relative risk for shorter PFS was 11.1 times higher for rCBV(max) > 4.2 (P = .0006) and 6.7 times higher for WHO grade > II (P = .05). The combined CBV-WHO grade classification enhanced the predictive value for recurrence/progression (P < .0001). rCBV values in astrocytomas but not tumors with oligodendroglial components are predictive for recurrence and 1-year survival and may be more accurate than histopathologic grading.