Objective: To assess the value of spectroscopic and perfusion MRI for glioma grading and for distinguishing glioblastomas from metastases and from CNS lymphomas. Methods: The authors examined 79 consecutive patients with first detection of a brain neoplasm on nonenhanced CT scans and no therapy prior to evaluation. Spectroscopic MRI; arterial spin-labeling MRI for measuring cerebral blood flow (CBF); first-pass dynamic, susceptibility-weighted, contrast-enhanced MRI for measuring cerebral blood volume; and T1-weighted dynamic contrast-enhanced MRI were performed. Receiver operating characteristic analysis was performed, and optimum thresholds for tumor classification and glioma grading were determined. Results: Perfusion MRI had a higher diagnostic performance than spectroscopic MRI. Because of a significantly higher tumor blood flow in glioblastomas compared with CNS lymphomas, a threshold value of 1.2 for CBF provided sensitivity of 97%, specificity of 80%, positive predictive value (PPV) of 94%, and negative predictive value (NPV) of 89%. Because CBF was significantly higher in peritumoral nonenhancing T2-hyperintense regions of glioblastomas compared with metastases, a threshold value of 0.5 for CBF provided sensitivity, specificity, PPV, and NPV of 100%, 71%, 94%, and 100%. Glioblastomas had the highest tumor blood flow values among all other glioma grades. For discrimination of glioblastomas from grade 3 gliomas, sensitivity was 97%, specificity was 50%, PPV was 84%, and NPV was 86% (CBF threshold value of 1.4), and for discrimination of glioblastomas from grade 2 gliomas, sensitivity was 94%, specificity was 78%, PPV was 94%, and NPV was 78% (CBF threshold value of 1.6). Conclusion: Perfusion MRI is predictive in distinguishing glioblastomas from metastases, CNS lymphomas and other gliomas vs. MRI and magnetic resonance spectroscopy.

Author

M A Weber, S Zoubaa, M Schlieter, E Juttler, H B Huttner, K Geletneky, C Ittrich, M P Lichy, A Kroll, J Debus, F L Giesel, M Hartmann and M Essig

Contact Details

Corresponding address:
Dr Marc-Andre Weber,
Department of Radiology,
German Cancer Research Center,
Im Neuenheimer Feld 280,
D-69120 Heidelberg, Germany

Reference

ICIS Cancer Imaging Volume 6 Special Issue A
DOI: 10.1102/1470-7330.2006.9096

Date Posted

31 October 2006

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