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fMRI for preoperative neurosurgical mapping of motor cortex and language in a clinical setting. J Comput Assist Tomogr 2000;24(6):927-34

Date

12/06/2000

Pubmed ID

11105714

DOI

10.1097/00004728-200011000-00020

Scopus ID

2-s2.0-0034465314 (requires institutional sign-in at Scopus site)   61 Citations

Abstract

PURPOSE: Identification of the precentral gyrus can be difficult in patients with brain tumors. The purpose of the current study was to evaluate the clinical usefulness of functional MRI (fMRI) in identifying motor cortex and speech areas as a part of preoperative neurosurgical planning.

METHOD: fMRI was performed using a 1.5 T MR unit in 41 patients with brain tumors. The motor paradigm was finger tapping and foot movement, whereas the language paradigm consisted of a two word semantic test. Statistical analysis of the data was done using the Kolmogorow-Smirnow test. Plots of signal intensities over time were created.

RESULTS: The precentral gyrus was identified in 38 of 41 patients. In two patients, fMRI was not of acceptable quality due to motion artifacts. Speech areas were localized in 33 patients. In a typical clinical setting, the value of the method was graded "high."

CONCLUSION: fMRI's efficacy in the preoperative localization of language and motor areas is high. The method should become a routine adjunct for preoperative evaluation of brain tumors in the near future.

Author List

Tomczak RJ, Wunderlich AP, Wang Y, Braun V, Antoniadis G, Görich J, Richter HP, Brambs HJ

Author

Yang Wang MD Professor in the Radiology department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Adult
Aged
Artifacts
Astrocytoma
Brain Mapping
Brain Neoplasms
Dominance, Cerebral
Echo-Planar Imaging
Electric Stimulation
Evoked Potentials, Somatosensory
Female
Glioblastoma
Humans
Language
Magnetic Resonance Imaging
Male
Middle Aged
Monitoring, Intraoperative
Motor Cortex
Motor Skills
Oligodendroglioma
Patient Care Planning
Preoperative Care
Speech
Statistics, Nonparametric