American Journal of Neuroradiology 2008;29:1664.
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American Journal of Neuroradiology
DOI 10.3174/ajnr.A1182
BRAIN
Histogram Analysis of MR Imaging–Derived Cerebral Blood Volume Maps: Combined Glioma Grading and Identification of Low-Grade Oligodendroglial Subtypes
From the Department of Medical Physics (K.E.E., A.B.), The Pathology Clinic (D.S., K.B.), Departments of Neuroradiology (P.D.-T., B.N., T.N., J.K.H.) and Neurosurgery (T.R.M.), and The Interventional Centre (K.E.E), Rikshospitalet University Hospital, Oslo, Norway; and Department of Physics (A.B.), 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.