Neurology
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Figures Only
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Data Supplement
Right arrow A correction has been published
Right arrow Correspondence:
Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Correspondence are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Weber, M. A.
Right arrow Articles by Essig, M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Weber, M. A.
Right arrow Articles by Essig, M.
Related Collections
Right arrow MRI
Right arrow MRS
Right arrow All Oncology
Right arrow Primary brain tumor
NEUROLOGY 2006;66:1899-1906
© 2006 American Academy of Neurology

Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors

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

From the Departments of Radiology (M.A.W., M.P.L., J.D., F.L.G., M.E.) and Physics in Radiology (A.K.), Central Unit Biostatistics (C.I.), German Cancer Research Center, Heidelberg, Germany; Departments of Pathology (S.Z.), Neuroradiology (M.S., M.H.), Neurology (E.J., H.B.H.), and Neurosurgery (K.G.), University of Heidelberg, Germany.

Address correspondence and reprint requests to Dr. Marc-André Weber, Department of Radiology, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany; e-mail: m.a.weber{at}dkfz.de

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.

Additional material related to this article can be found on the Neurology Web site. Go to www.neurology.org and scroll down the Table of Contents for the June 27 issue to find the title link for this article.

Disclosure: The authors report no conflicts of interest.

Received November 21, 2005. Accepted in final form March 10, 2006.




This article has been cited by other articles:


Home page
 Am. J. Neuroradiol.Home page
K. Yamashita, T. Yoshiura, H. Arimura, F. Mihara, T. Noguchi, A. Hiwatashi, O. Togao, Y. Yamashita, T. Shono, S. Kumazawa, et al.
Performance Evaluation of Radiologists with Artificial Neural Network for Differential Diagnosis of Intra-Axial Cerebral Tumors on MR Images
AJNR Am. J. Neuroradiol., June 1, 2008; 29(6): 1153 - 1158.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Neuroradiol.Home page
T. Noguchi, T. Yoshiura, A. Hiwatashi, O. Togao, K. Yamashita, E. Nagao, T. Shono, M. Mizoguchi, S. Nagata, T. Sasaki, et al.
Perfusion Imaging of Brain Tumors Using Arterial Spin-Labeling: Correlation with Histopathologic Vascular Density
AJNR Am. J. Neuroradiol., April 1, 2008; 29(4): 688 - 693.
[Abstract] [Full Text] [PDF]

Home page
 RadiologyHome page
P. J. van Laar, J. van der Grond, and J. Hendrikse
Brain Perfusion Territory Imaging: Methods and Clinical Applications of Selective Arterial Spin-labeling MR Imaging
Radiology, February 1, 2008; 246(2): 354 - 364.
[Abstract] [Full Text] [PDF]

Home page
 RadiologyHome page
P. J. van Laar, Y. van der Graaf, W. P. T. M. Mali, J. van der Grond, and J. Hendrikse
Effect of Cerebrovascular Risk Factors on Regional Cerebral Blood Flow
Radiology, December 1, 2007; 246(1): 198 - 204.
[Abstract] [Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2006 by AAN Enterprises, Inc.