Preoperative magnetic resonance imaging protocol for endoscopic cranial base image-guided surgery.

Publication/Presentation Date

1-1-2011

Abstract

OBJECTIVE: Despite the increasing utilization of image-guided surgery, no radiology protocols for obtaining magnetic resonance (MR) imaging of adequate quality are available in the current literature. At our institution, more than 300 endonasal cranial base procedures including pituitary, extended pituitary, and other anterior skullbase procedures have been performed in the past 3 years. To facilitate and optimize preoperative evaluation and assessment, there was a need to develop a magnetic resonance protocol.

METHODS: Retrospective Technical Assessment was performed.

DISCUSSION: Through a collaborative effort between the otolaryngology, neurosurgery, and neuroradiology departments at our institution, a skull base MR image-guided (IGS) protocol was developed with several ends in mind. First, it was necessary to generate diagnostic images useful for the more frequently seen pathologies to improve work flow and limit the expense and inefficiency of case specific MR studies. Second, it was necessary to generate sequences useful for IGS, preferably using sequences that best highlight that lesion. Currently, at our institution, all MR images used for IGS are obtained using this protocol as part of preoperative planning. The protocol that has been developed allows for thin cut precontrast and postcontrast axial cuts that can be used to plan intraoperative image guidance. It also obtains a thin cut T2 axial series that can be compiled separately for intraoperative imaging, or may be fused with computed tomographic images for combined modality. The outlined protocol obtains image sequences effective for diagnostic and operative purposes for image-guided surgery using both T1 and T2 sequences.

Volume

32

Issue

6

First Page

451

Last Page

454

ISSN

1532-818X

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

21035917

Department(s)

Administration and Leadership

Document Type

Article

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