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Technology Report

Free Access

Estimation of Brain Deformation for Volumetric Image Updating in Protoporphyrin IX Fluorescence-Guided Resection

Valdés P.A.a, b · Fan X.b · Ji S.b · Harris B.T.a, c · Paulsen K.D.a, b, d · Roberts D.W.a, d, e

Author affiliations

aDartmouth Medical School and bThayer School of Engineering, Dartmouth College, Hanover, N.H., cDepartment of Pathology, dNorris Cotton Cancer Center, and eSection of Neurosurgery, Dartmouth-Hitchcock Medical Center, Lebanon, N.H., USA

Corresponding Author

David W. Roberts, MD

Section of Neurosurgery, Dartmouth-Hitchcock Medical Center

One Medical Center Drive

Lebanon, NH 03756 (USA)

Tel. +1 603 650 8734, Fax +1 603 650 7911, E-Mail David.W.Roberts@dartmouth.edu

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Stereotact Funct Neurosurg 2010;88:1–10

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Introduction: Fluorescence-guided resection (FGR) of brain tumors is an intuitive, practical and emerging technology for visually delineating neoplastic tissue exposed intraoperatively. Image guidance is the standard technique for producing 3-dimensional spatially coregistered information for surgical decision making. Both technologies together are synergistic: the former detects surface fluorescence as a biomarker of the current surgical margin while the latter shows coregistered volumetric neuroanatomy but can be degraded by intraoperative brain shift. We present the implementation of deformation modeling for brain shift compensation in protoporphyrin IX FGR, integrating these two sources of information for maximum surgical benefit. Methods: Two patients underwent FGR coregistered with conventional image guidance. Histopathological analysis, intraoperative fluorescence and image space coordinates were recorded for biopsy specimens acquired during surgery. A biomechanical brain deformation model driven by intraoperative ultrasound data was used to generate updated MR images. Results: Combined use of fluorescence signatures and updated MR image information showed substantially improved accuracy compared to fluorescence or the original (i.e., nonupdated) MR images, detecting only true positives and true negatives, and no instances of false positives or false negatives. Conclusion: Implementation of brain deformation modeling in FGR shows promise for increasing the accuracy of neurosurgical guidance in the delineation and resection of brain tumors.

© 2009 S. Karger AG, Basel

Article / Publication Details

First-Page Preview
Abstract of Technology Report

Received: July 16, 2009
Accepted: August 28, 2009
Published online: November 12, 2009
Issue release date: January 2010

Number of Print Pages: 10
Number of Figures: 5
Number of Tables: 3

ISSN: 1011-6125 (Print)
eISSN: 1423-0372 (Online)

For additional information: http://www.karger.com/SFN

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