Evaluation of a system for high-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery.

Daniel J Mirota, Ali Uneri, Sebastian Schafer, Sajendra Nithiananthan, Douglas D Reh, Masaru Ishii, Gary L Gallia, Russell H Taylor, Gregory D Hager, Jeffrey H Siewerdsen
Author Information
  1. Daniel J Mirota: Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA. dan@cs.jhu.edu

Abstract

The safety of endoscopic skull base surgery can be enhanced by accurate navigation in preoperative computed tomography (CT) or, more recently, intraoperative cone-beam CT (CBCT). The ability to register real-time endoscopic video with CBCT offers an additional advantage by rendering information directly within the visual scene to account for intraoperative anatomical change. However, tracker localization error (  ∼ 1-2 mm ) limits the accuracy with which video and tomographic images can be registered. This paper reports the first implementation of image-based video-CBCT registration, conducts a detailed quantitation of the dependence of registration accuracy on system parameters, and demonstrates improvement in registration accuracy achieved by the image-based approach. Performance was evaluated as a function of parameters intrinsic to the image-based approach, including system geometry, CBCT image quality, and computational runtime. Overall system performance was evaluated in a cadaver study simulating transsphenoidal skull base tumor excision. Results demonstrated significant improvement in registration accuracy with a mean reprojection distance error of 1.28 mm for the image-based approach versus 1.82 mm for the conventional tracker-based method. Image-based registration was highly robust against CBCT image quality factors of noise and resolution, permitting integration with low-dose intraoperative CBCT.

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Grants

  1. R01 CA127444/NCI NIH HHS
  2. R01-CA127444/NCI NIH HHS

MeSH Term

Cone-Beam Computed Tomography
Humans
Imaging, Three-Dimensional
Phantoms, Imaging
Skull Base
Surgery, Computer-Assisted

Word Cloud

Created with Highcharts 10.0.0registrationCBCTimage-basedaccuracysystemendoscopicskullbaseCTintraoperativevideommapproachsurgerycancone-beamerrorparametersimprovementevaluatedimagequality1safetyenhancedaccuratenavigationpreoperativecomputedtomographyrecentlyabilityregisterreal-timeoffersadditionaladvantagerenderinginformationdirectlywithinvisualsceneaccountanatomicalchangeHowevertrackerlocalization ∼ 1-2limitstomographicimagesregisteredpaperreportsfirstimplementationvideo-CBCTconductsdetailedquantitationdependencedemonstratesachievedPerformancefunctionintrinsicincludinggeometrycomputationalruntimeOverallperformancecadaverstudysimulatingtranssphenoidaltumorexcisionResultsdemonstratedsignificantmeanreprojectiondistance28versus82conventionaltracker-basedmethodImage-basedhighlyrobustfactorsnoiseresolutionpermittingintegrationlow-doseEvaluationhigh-accuracy3DC-armimage-guided

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