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Neurosurgery. 2009 Jul;65(1):121-8; discussion 128-9. doi: 10.1227/01.NEU.0000347890.19718.0A.

Prediction of surgical view of neurovascular decompression using interactive computer graphics.

Author information

1
Department of Neurosurgery, University of Tokyo, Tokyo, Japan. tkin-tky@umin.ac.jp

Abstract

OBJECTIVE:

To assess the value of an interactive visualization method for detecting the offending vessels in neurovascular compression syndrome in patients with facial spasm and trigeminal neuralgia. Computer graphics models are created by fusion of fast imaging employing steady-state acquisition and magnetic resonance angiography.

METHODS:

High-resolution magnetic resonance angiography and fast imaging employing steady-state acquisition were performed preoperatively in 17 patients with neurovascular compression syndromes (facial spasm, n = 10; trigeminal neuralgia, n = 7) using a 3.0-T magnetic resonance imaging scanner. Computer graphics models were created with computer software and observed interactively for detection of offending vessels by rotation, enlargement, reduction, and retraction on a graphic workstation. Two-dimensional images were reviewed by 2 radiologists blinded to the clinical details, and 2 neurosurgeons predicted the offending vessel with the interactive visualization method before surgery. Predictions from the 2 imaging approaches were compared with surgical findings. The vessels identified during surgery were assumed to be the true offending vessels.

RESULTS:

Offending vessels were identified correctly in 16 of 17 patients (94%) using the interactive visualization method and in 10 of 17 patients using 2-dimensional images. These data demonstrated a significant difference (P = 0.015 by Fisher's exact method).

CONCLUSION:

The interactive visualization method data corresponded well with surgical findings (surgical field, offending vessels, and nerves). Virtual reality 3-dimensional computer graphics using fusion magnetic resonance angiography and fast imaging employing steady-state acquisition may be helpful for preoperative simulation.

[Indexed for MEDLINE]

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