13 September 2017 Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery
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J. of Medical Imaging, 4(3), 035003 (2017). doi:10.1117/1.JMI.4.3.035003
Abstract
Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of n=9 tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift (<3  mm, n=13±6 measurements per case), the alignment error due to brain shift reduced from 5.7±2.6 to 2.3±1.1  mm, representing ∼59% correction. These first steps toward validation are promising for model-based strategies.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Ma Luo, Sarah F. Frisken, Jared A. Weis, Logan W. Clements, Prashin Unadkat, Reid C. Thompson, Alexandra J. Golby, Michael I. Miga, "Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery," Journal of Medical Imaging 4(3), 035003 (13 September 2017). http://dx.doi.org/10.1117/1.JMI.4.3.035003 Submission: Received 17 April 2017; Accepted 21 August 2017
Submission: Received 17 April 2017; Accepted 21 August 2017
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