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Proceedings Paper

Image updating for brain deformation compensation in tumor resection
Author(s): Xiaoyao Fan; Songbai Ji; Jonathan D. Olson; David W. Roberts; Alex Hartov; Keith D. Paulsen
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Paper Abstract

Preoperative magnetic resonance images (pMR) are typically used for intraoperative guidance in image-guided neurosurgery, the accuracy of which can be significantly compromised by brain deformation. Biomechanical finite element models (FEM) have been developed to estimate whole-brain deformation and produce model-updated MR (uMR) that compensates for brain deformation at different surgical stages. Early stages of surgery, such as after craniotomy and after dural opening, have been well studied, whereas later stages after tumor resection begins remain challenging. In this paper, we present a method to simulate tumor resection by incorporating data from intraoperative stereovision (iSV). The amount of tissue resection was estimated from iSV using a "trial-and-error" approach, and the cortical shift was measured from iSV through a surface registration method using projected images and an optical flow (OF) motion tracking algorithm. The measured displacements were employed to drive the biomechanical brain deformation model, and the estimated whole-brain deformation was subsequently used to deform pMR and produce uMR. We illustrate the method using one patient example. The results show that the uMR aligned well with iSV and the overall misfit between model estimates and measured displacements was 1.46 mm. The overall computational time was ~5 min, including iSV image acquisition after resection, surface registration, modeling, and image warping, with minimal interruption to the surgical flow. Furthermore, we compare uMR against intraoperative MR (iMR) that was acquired following iSV acquisition.

Paper Details

Date Published: 18 March 2016
PDF: 8 pages
Proc. SPIE 9786, Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, 97862A (18 March 2016); doi: 10.1117/12.2217223
Show Author Affiliations
Xiaoyao Fan, Thayer School of Engineering, Dartmouth College (United States)
Songbai Ji, Geisel School of Medicine, Dartmouth College (United States)
Jonathan D. Olson, Thayer School of Engineering, Dartmouth College (United States)
David W. Roberts, Geisel School of Medicine, Dartmouth College (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)
Alex Hartov, Thayer School of Engineering, Dartmouth College (United States)
Keith D. Paulsen, Geisel School of Medicine, Dartmouth College (United States)
Norris Cotton Cancer Ctr. (United States)
Dartmouth-Hitchcock Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 9786:
Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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