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A Fast and Efficient Method to Compensate for Brain Shift for Tumor Resection Therapies Measured Between Preoperative and Postoperative Tomograms

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7 Author(s)
Dumpuri, P. ; Dept. of Biomed. Eng., Vanderbilt Univ., Nashville, TN, USA ; Thompson, R.C. ; Aize Cao ; Siyi Ding
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In this paper, an efficient paradigm is presented to correct for brain shift during tumor resection therapies. For this study, high resolution preoperative (pre-op) and postoperative (post-op) MR images were acquired for eight in vivo patients, and surface/subsurface shift was identified by manual identification of homologous points between the pre-op and immediate post-op tomograms. Cortical surface deformation data were then used to drive an inverse problem framework. The manually identified subsurface deformations served as a comparison toward validation. The proposed framework recaptured 85% of the mean subsurface shift. This translated to a subsurface shift error of 0.4 ± 0.4 mm for a measured shift of 3.1 ± 0.6 mm. The patient's pre-op tomograms were also deformed volumetrically using displacements predicted by the model. Results presented allow a preliminary evaluation of correction both quantitatively and visually. While intraoperative (intra-op) MR imaging data would be optimal, the extent of shift measured from pre- to post-op MR was comparable to clinical conditions. This study demonstrates the accuracy of the proposed framework in predicting full-volume displacements from sparse shift measurements. It also shows that the proposed framework can be extended and used to update pre-op images on a time scale that is compatible with surgery.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:57 ,  Issue: 6 )

Date of Publication:

June 2010

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