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Endoscopic navigation in the clinic: registration in the absence of preoperative imaging

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

Abstract

Purpose

Clinical examinations that involve endoscopic exploration of the nasal cavity and sinuses often do not have a reference preoperative image, like a computed tomography (CT) scan, to provide structural context to the clinician. The aim of this work is to provide structural context during clinical exploration without requiring additional CT acquisition.

Methods

We present a method for registration during clinical endoscopy in the absence of CT scans by making use of shape statistics from past CT scans. Using a deformable registration algorithm that uses these shape statistics along with dense point clouds from video, we simultaneously achieve two goals: (1) register the statistically mean shape of the target anatomy with the video point cloud, and (2) estimate patient shape by deforming the mean shape to fit the video point cloud. Finally, we use statistical tests to assign confidence to the computed registration.

Results

We are able to achieve submillimeter errors in registrations and patient shape reconstructions using simulated data. We establish and evaluate the confidence criteria for our registrations using simulated data. Finally, we evaluate our registration method on in vivo clinical data and assign confidence to these registrations using the criteria established in simulation. All registrations that are not rejected by our criteria produce submillimeter residual errors.

Conclusion

Our deformable registration method can produce submillimeter registrations and reconstructions as well as statistical scores that can be used to assign confidence to the registrations.

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Acknowledgements

This work was funded by NIH R01-EB015530, JHU Provost’s Postdoctoral Fellowship, and JHU internal funds. We would also like to acknowledge the comments and input from Seth D. Billings and Mathias Unberath.

Funding

The National Institutes of Health provided a research Grant (NIH R01-EB015530) to conduct the study that yielded the clinical dataset used in our in vivo experiment. A. Sinha was supported partly by the Johns Hopkins University (JHU) Provost’s Postdoctoral Fellowship and partly by other JHU internal funds.

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Authors and Affiliations

  1. Laboratory for Computational and Sensing Robotics, The Johns Hopkins University, Baltimore, MD, 21218, USA

    Ayushi Sinha, Gregory D. Hager & Russell H. Taylor

  2. Department of Otolaryngology - Head and Neck Surgery, Johns Hopkins Medical Institutions, Baltimore, MD, 21205, USA

    Masaru Ishii

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  1. Ayushi Sinha
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Correspondence to Ayushi Sinha.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the clinical study under JHU IRB NA_00074677.

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Sinha, A., Ishii, M., Hager, G.D. et al. Endoscopic navigation in the clinic: registration in the absence of preoperative imaging. Int J CARS 14, 1495–1506 (2019). https://doi.org/10.1007/s11548-019-02005-0

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