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.
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.
Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA. dan@cs.jhu.edu
Daniel J
DJ
Mirota
Ali
A
Uneri
Sebastian
S
Schafer
Sajendra
S
Nithiananthan
Douglas D
DD
Reh
Masaru
M
Ishii
Gary L
GL
Gallia
Russell H
RH
Taylor
Gregory D
GD
Hager
Jeffrey H
JH
Siewerdsen
D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D019047:Phantoms, Imaging; D019291:Skull Base / Q000000981:diagnostic imaging* / Q000601:surgery*; D025321:Surgery, Computer-Assisted / Q000379:methods*