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Proceedings Paper

Neurosurgical procedures under near-real-time MR guidance
Author(s): Haiying Liu; Charles L. Truwit
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Paper Abstract

A robust near real-time magnetic resonance imaging (MRI) based guidance scheme has been developed, validated and used for in vivo neurosurgical applications. The key concept of the method is to use tomographical imagine techniques, such as MRI, to facilitate the alignment process of a trajectory guidance device for biopsy needle. Since the trajectory corresponding to the biopsy needle pivoted at an entry point on patient skull has two orientational degrees of freedom, the alignment of the needle can be tracked using a 2-dimensional (2D) imaging plane that is placed perpendicular to the desired trajectory. Using a near real-time visual feedbacak in 2D during the adjustment of the alignment guide, the required trajectory alignment can be translated into a simple targeting task on computer monitor. This MR based guidance technique has practically allowed neurosurgeons to accomplish the required alignment of a surgical device to an aribitrary target accurately in a straight forward procedure on conventional MR scanner. The actual MR-guided biopsy using the new methodology has shown that is has the required targeting accuracy for neurosurgery even in the presence of brain shift. The use of the method in 20 MR-guided brain lesion biopsy procedures can significantly reduce the surgery time, in fact the time required for the needle trajectory alignment is less than 1 min. Furthermore, the post- alignment trajectory can be validated using near real-time MRI scans in two orthogonal views before the needle insertion. In conclusion, this scheme provides a unique alternative of trajectory guidance and monitoring methodology that can take full advantages of the capabilities of modern imaging techniques such as MRI.

Paper Details

Date Published: 9 October 2000
PDF: 9 pages
Proc. SPIE 4118, Parallel and Distributed Methods for Image Processing IV, (9 October 2000); doi: 10.1117/12.403605
Show Author Affiliations
Haiying Liu, Univ. of Minnesota/Twin Cities (United States)
Charles L. Truwit, Univ. of Minnesota/Twin Cities (United States)


Published in SPIE Proceedings Vol. 4118:
Parallel and Distributed Methods for Image Processing IV
Hongchi Shi; Patrick C. Coffield; Divyendu Sinha, Editor(s)

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