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AJNR - American Journal of Neuroradiology

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Histogram Analysis versus Region of Interest Analysis of Dynamic Susceptibility Contrast Perfusion MR Imaging Data in the Grading of Cerebral Gliomas

M. Law^a,b, R. Young^a, J. Babb^a, E. Pollack^a and G. Johnson^a

^a Department of Radiology, NYU Medical Center, New York, NY
^b Department of Neurosurgery, NYU Medical Center, New York, NY

View larger version (32K): [in this window] [in a new window]   Fig 1. Sample histogram. Percentile mean and SD measures are calculated from the top 50%, 25%, and 10% of the histogram curve. Skewness is zero if the data are distributed symmetrically around the mean, negative if the data are more spread out on the left of the mean, and positive if the data are more spread out on the right of the mean. Kurtosis, a measure of how "peaked" the histogram is, equals zero if the histogram is Gaussian, is positive if the histogram has a sharper peak, and is negative if it has a flatter top.

View larger version (38K): [in this window] [in a new window]   Fig 2. Low-grade glioma (grade II/IV) in left frontal lobe, T2-weighted (A) and contrast T1-weighted (B) images. The rCBVmax method uses 4 small ROIs targeted to foci of greatest perfusion on the rCBV map (C), with the maximal rCBV recorded from the subsequent perfusion curves (E). The signal intensity curves from each of the 5 ROIs are denoted as S1, S2, S3, S4, and S5, where S1 is the signal intensity curve for the ROI placed in normal brain and S2–S5 are the other ROIs placed in the tumoral tissue. These 5 signal intensity curves were obtained from a single section from the perfusion dataset. The rCBV histogram method uses a single ROI (D) that encompasses the maximal tumor diameter to generate the histogram curve (F), from which multiple metrics are derived.

View larger version (42K): [in this window] [in a new window]   Fig 3. High-grade glioma, glioblastoma multiforme (grade IV/IV) in frontal lobes spanning the corpus callosum. T2-weighted (A) and contrast T1-weighted (B) images are shown along with rCBVmax map (C) with ROIs targeted to avoid areas of radiologic necrosis to determine perfusion curves (E). rCBV histogram map (D) and histogram curve (F) are derived from the maximal tumor diameter regardless of heterogeneity.