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AJNR - American Journal of Neuroradiology

Published ahead of print on June 26, 2008
doi: 10.3174/ajnr.A1182

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American Journal of Neuroradiology 29:1664-1670, October 2008
© 2008 American Society of Neuroradiology

BRAIN

Histogram Analysis of MR Imaging–Derived Cerebral Blood Volume Maps: Combined Glioma Grading and Identification of Low-Grade Oligodendroglial Subtypes

K.E. Emblem^a,e, D. Scheie^b, P. Due-Tonnessen^c, B. Nedregaard^c, T. Nome^c, J.K. Hald^c, K. Beiske^b, T.R. Meling^d and A. Bjornerud^a,f

^a Department of Medical Physics, Rikshospitalet University Hospital, Oslo, Norway
^b The Pathology Clinic, Rikshospitalet University Hospital, Oslo, Norway
^c Department of Neuroradiology, Rikshospitalet University Hospital, Oslo, Norway
^d Department of Neurosurgery, Rikshospitalet University Hospital, Oslo, Norway
^e The Interventional Centre, Rikshospitalet University Hospital, Oslo, Norway
^f Department of Physics, University of Oslo, Oslo, Norway

Please address correspondence to Kyrre E. Emblem, MSc, Department of Medical Physics, Rikshospitalet University Hospital, Sognsvannsveien 20, N-0027 Oslo, Norway; e-mail: kyrre.eeg.emblem{at}rikshospitalet.no

BACKGROUND AND PURPOSE: Inclusion of oligodendroglial tumors may confound the utility of MR based glioma grading. Our aim was, first, to assess retrospectively whether a histogram-analysis method of MR perfusion images may both grade gliomas and differentiate between low-grade oligodendroglial tumors with or without loss of heterozygosity (LOH) on 1p/19q and, second, to assess retrospectively whether low-grade oligodendroglial subtypes can be identified in a population of patients with high-grade and low-grade astrocytic and oligodendroglial tumors.

MATERIALS AND METHODS: Fifty-two patients (23 women, 29 men; mean age, 52 years; range, 19–78 years) with histologically confirmed gliomas were imaged by using dynamic susceptibility contrast MR imaging at 1.5T. Relative cerebral blood volume (rCBV) maps were created, and 4 neuroradiologists defined the glioma volumes independently. Averaged over the 4 observers, a histogram-analysis method was used to assess the normalized histogram peak height of the glioma rCBV distributions.

RESULTS: Of the 52 patients, 22 had oligodendroglial tumors. The histogram method was able to differentiate high-grade gliomas (HGGs) from low-grade gliomas (LGGs) (Mann-Whitney U test, P < .001) and to identify low-grade oligodendroglial subtypes (P = .009). The corresponding intraclass correlation coefficients were 0.902 and 0.801, respectively. The sensitivity and specificity in terms of differentiating low-grade oligodendroglial tumors without LOH on 1p/19q from the other tumors was 100% (6/6) and 91% (42/46), respectively.

CONCLUSION: With histology as a reference, our results suggest that histogram analysis of MR imaging–derived rCBV maps can differentiate HGGs from LGGs as well as low-grade oligodendroglial subtypes with high interobserver agreement. Also, the method was able to identify low-grade oligodendroglial tumors without LOH on 1p/19q in a population of patients with astrocytic and oligodendroglial tumors.