Perfusion measurement in brain gliomas with intravoxel incoherent motion MRI.
OBJECTIVE
Intravoxel incoherent motion MRI has been proposed as an alternative method to measure brain perfusion. Our aim was to evaluate the utility of intravoxel incoherent motion perfusion parameters (the perfusion fraction, the pseudodiffusion coefficient, and the flow-related parameter) to differentiate high- and low-grade brain gliomas.


METHODS
The intravoxel incoherent motion perfusion parameters were assessed in 21 brain gliomas (16 high-grade, 5 low-grade). Images were acquired by using a Stejskal-Tanner diffusion pulse sequence, with 16 values of b (0-900 s/mm(2)) in 3 orthogonal directions on 3T systems equipped with 32 multichannel receiver head coils. The intravoxel incoherent motion perfusion parameters were derived by fitting the intravoxel incoherent motion biexponential model. Regions of interest were drawn in regions of maximum intravoxel incoherent motion perfusion fraction and contralateral control regions. Statistical significance was assessed by using the Student t test. In addition, regions of interest were drawn around all whole tumors and were evaluated with the help of histograms.


RESULTS
In the regions of maximum perfusion fraction, perfusion fraction was significantly higher in the high-grade group (0.127 ± 0.031) than in the low-grade group (0.084 ± 0.016, P < .001) and in the contralateral control region (0.061 ± 0.011, P < .001). No statistically significant difference was observed for the pseudodiffusion coefficient. The perfusion fraction correlated moderately with dynamic susceptibility contrast relative CBV (r = 0.59). The histograms of the perfusion fraction showed a "heavy-tailed" distribution for high-grade but not low-grade gliomas.


CONCLUSIONS
The intravoxel incoherent motion perfusion fraction is helpful for differentiating high- from low-grade brain gliomas.
From the Department of Diagnostic and Interventional Radiology (C.F., R.M., P.M., P.H.), Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland.
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C
Federau
R
R
Meuli
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K
O'Brien
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P
Maeder
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P
Hagmann
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001783:Blood Flow Velocity; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000503:physiopathology*; D002560:Cerebrovascular Circulation; D002648:Child; D002675:Child, Preschool; D005260:Female; D005910:Glioma / Q000175:diagnosis* / Q000503:physiopathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009038:Motion; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult