American Journal of Neuroradiology 25:1524-1532, October 2004
© 2004 American Society of Neuroradiology
BRAIN
Characterization of a First-Pass Gradient-Echo Spin-Echo Method to Predict Brain Tumor Grade and Angiogenesis
a Department of Radiology, Medical College of Wisconsin, Milwaukee, WI
b Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI
c Departments of Neurology and Neurosurgery, Medical College of Wisconsin, Milwaukee, WI
d Department of Biomedical Engineering, Marquette University, Milwaukee, WI
Address reprint requests to Kathleen M. Schmainda, PhD, Medical College of Wisconsin, Department of Biophysics, 8701 Watertown Plank Rd, Milwaukee, WI 53226
BACKGROUND AND PURPOSE: No widespread clinical method provides specific information about the angiogenic characteristics of gliomas. We characterized blood volume and vascular morphologic parameters from combined gradient-echo (GE) and spin-echo (SE) MR imaging and assessed their relationship to tumor grade, a known correlate of glioma angiogenesis.
METHODS: Simultaneous GE and SE echo-planar imaging was performed with bolus gadolinium administration (0.20–0.25 mmol/kg) in 73 patients with glioma. To diminish possible T1 changes due to contrast agent extravasation, a preload (0.05–0.10 mmol/kg) was administered before the study, and a postprocessing correction algorithm was applied. Image maps of total (GE) and microvascular (SE) relative cerebral blood volume (rCBV) and the mean vessel diameter (mVD) calculated from the ratio of GE and SE relaxation rate changes (
R2*/R2) were compared with tumor grade. A nonparametric K nearest-neighbor decision rule was applied to determine if the combined data could be used to distinguish low-grade (I–II) from high-grade (III–IV) tumors on a per-patient basis.
RESULTS: For whole tumors, significant correlations were found between GE rCBV and grade (P < .0001) and between mVD and grade (P = .0001) but not between SE rCBV and grade (P = .08). For areas of highest SE rCBV (microvascular hotspots), SE rCBV and tumor grade were significantly correlated (P = .0007). In terms of differentiation, 69% of low-grade tumors and 96% of high-grade tumors were correctly classified.
CONCLUSION: Combined GE and SE MR imaging provides information consistent with neoplastic angiogenesis, demonstrating its potential to aid in optimizing treatments, categorizing lesions, and influencing patient care.
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