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AJNR - American Journal of Neuroradiology

Published ahead of print on January 17, 2008
doi: 10.3174/ajnr.A0899

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American Journal of Neuroradiology 29:694-700, April 2008
© 2008 American Society of Neuroradiology

BRAIN

Quantitative Estimation of Permeability Surface-Area Product in Astroglial Brain Tumors Using Perfusion CT and Correlation with Histopathologic Grade

R. Jain^a, S.K. Ellika^a, L. Scarpace^b, L.R. Schultz^c, J.P. Rock^b, J. Gutierrez^d, S.C. Patel^a, J. Ewing^e and T. Mikkelsen^b

^a From the Division of Neuroradiology, Department of Radiology, Henry Ford Hospital, Detroit, Mich
^b Department of Neurosurgery, Henry Ford Hospital, Detroit, Mich
^c Department of Biostatistics and Research Epidemiology, Henry Ford Hospital, Detroit, Mich
^d Department of Pathology, Henry Ford Hospital, Detroit, Mich
^e Department of Neurology, Henry Ford Hospital, Detroit, Mich

Please address correspondence to Rajan Jain, MD, Division of Neuroradiology, Department of Radiology, Henry Ford Health System, 2799 West Grand Blvd, Detroit MI 48202; e-mail: rajanj{at}rad.hfh.edu

BACKGROUND AND PURPOSE: Glioma angiogenesis and its different hemodynamic features, which can be evaluated by using perfusion CT (PCT) imaging of the brain, have been correlated with the grade and the aggressiveness of gliomas. Our hypothesis was that quantitative estimation of permeability surface area product (PS), cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) in astroglial brain tumors by using PCT will correlate with glioma grade. High-grade gliomas will show higher PS and CBV as compared with low-grade gliomas.

MATERIALS AND METHODS: PCT was performed in 32 patients with previously untreated astroglial tumors (24 high-grade gliomas and 8 low-grade gliomas) by using a total acquisition time of 170 seconds. World Health Organization (WHO) glioma grades were compared with PCT parameter absolute values by using Student or nonparametric Wilcoxon 2-sample tests. Receiver operating characteristic (ROC) analyses were also done for each of the parameters.

RESULTS: The differences in PS, CBV, and CBF between the low- and high-grade tumor groups were statistically significant, with the low-grade group showing lower mean values than the high-grade group. ROC analyses showed that both CBV (C-statistic 0.930) and PS (C-statistic 0.927) were very similar to each other in differentiating low- and high-grade gliomas and had higher predictability compared with CBF and MTT. Within the high-grade group, differentiation of WHO grade III and IV gliomas was also possible by using PCT parameters, and PS showed the highest C-statistic value (0.926) for the ROC analyses in this regard.

CONCLUSIONS: Both PS and CBV showed strong association with glioma grading, high-grade gliomas showing higher PS and CBV as compared with low-grade gliomas. Perfusion parameters, especially PS, can also be used to differentiate WHO grade III from grade IV in the high-grade tumor group.

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