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Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Sites that use ultrasound (US) in image-guided neurosurgery (IGNS) of brain tumors generally have three sets of imaging data: preoperative magnetic resonance (MR) image, pre-resection US, and post-resection US. The MR image is usually acquired days before the surgery, the pre-resection US is obtained after the craniotomy but before the resection, and finally, the post-resection US scan is performed after the resection of the tumor. The craniotomy and tumor resection both cause brain deformation, which significantly reduces the accuracy of the MR–US alignment.

Method

Three unknown transformations exist between the three sets of imaging data: MR to pre-resection US, pre- to post-resection US, and MR to post-resection US. We use two algorithms that we have recently developed to perform the first two registrations (i.e., MR to pre-resection US and pre- to post-resection US). Regarding the third registration (MR to post-resection US), we evaluate three strategies. The first method performs a registration between the MR and pre-resection US, and another registration between the pre- and post-resection US. It then composes the two transformations to register MR and post-resection US; we call this method compositional registration. The second method ignores the pre-resection US and directly registers the MR and post-resection US; we refer to this method as direct registration. The third method is a combination of the first and second: it uses the solution of the compositional registration as an initial solution for the direct registration method. We call this method group-wise registration.

Results

We use data from 13 patients provided in the MNI BITE database for all of our analysis. Registration of MR and pre-resection US reduces the average of the mean target registration error (mTRE) from 4.1 to 2.4 mm. Registration of pre- and post-resection US reduces the average mTRE from 3.7 to 1.5 mm. Regarding the registration of MR and post-resection US, all three strategies reduce the mTRE. The initial average mTRE is 5.9 mm, which reduces to 3.3 mm with the compositional method, 2.9 mm with the direct technique, and 2.8 mm with the group-wise method.

Conclusion

Deformable registration of MR and pre- and post-resection US images significantly improves their alignment. Among the three methods proposed for registering the MR to post-resection US, the group-wise method gives the lowest TRE values. Since the running time of all registration algorithms is less than 2 min on one core of a CPU, they can be integrated into IGNS systems for interactive use during surgery.

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Acknowledgments

The authors would like to thank anonymous reviewers for their constructive feedback. This work was financed by the Fonds Québécois de la recherche sur la nature et les technologies, the Canadian Institute of Health Research (MOP-97820), and the Natural Science and Engineering Research Council of Canada. H. Rivaz is supported by a postdoctoral fellowship from the Natural Sciences and Engineering Research Council of Canada.

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Authors and Affiliations

  1. PERFORM Centre, Department of Electrical and Computer Engineering, Concordia University, 1455 Maisonneuve West, Montreal, QC, H3G 1M8, Canada

    Hassan Rivaz

  2. McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada

    D. Louis Collins

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  1. Hassan Rivaz
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Correspondence to Hassan Rivaz or D. Louis Collins.

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Rivaz, H., Collins, D.L. Deformable registration of preoperative MR, pre-resection ultrasound, and post-resection ultrasound images of neurosurgery. Int J CARS 10, 1017–1028 (2015). https://doi.org/10.1007/s11548-014-1099-4

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  • DOI: https://doi.org/10.1007/s11548-014-1099-4

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