• N Rollin, J Guyotat, N Streichenberger, J Honnorat, V-A Tran Minh, and F Cotton.
• Department of Radiology, Lyon University School of Medicine, France.
• Neuroradiology. 2006 Mar 1; 48 (3): 150-9.

AbstractAdvanced magnetic resonance (MR) imaging techniques provide physiologic information that complements the anatomic information available from conventional MR imaging. We evaluated the roles of diffusion and perfusion imaging for the assessment of grade and type of histologically proven intraaxial brain tumors. A total of 28 patients with intraaxial brain tumors underwent conventional MR imaging (T2- and T1-weighted sequences after gadobenate dimeglumine injection), diffusion imaging and T2*-weighted echo-planar perfusion imaging. Examinations were performed on 19 patients during initial diagnosis and on nine patients during follow-up therapy. Determinations of relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) were performed in the solid parts of each tumor, peritumoral region and contralateral white matter. For gliomas, rCBV values were greater in high-grade than in low-grade tumors (3.87+/-1.94 versus 1.30+/-0.42) at the time of initial diagnosis. rCBV values were increased in all recurrent tumors, except in one patient who presented with a combination of recurrent glioblastoma and massive radionecrosis on histology. Low-grade gliomas had low rCBV even in the presence of contrast medium enhancement. Differentiation between high- and low-grade gliomas was not possible using diffusion-weighted images and ADC values alone. In the peritumoral areas of untreated high-grade gliomas and metastases, the mean rCBV values were higher for high-grade gliomas (1.7+/-0.37) than for metastases (0.54+/-0.18) while the mean ADC values were higher for metastases. The rCBV values of four lymphomas were low and the signal intensity-time curves revealed a significant increase in signal intensity after the first pass of gadobenate dimeglumine. Diffusion and perfusion imaging, even with relatively short imaging and data processing times, provide important information for lesion characterization.

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