RESEARCH ARTICLE


Accuracy and Precision of a Surgical Navigation System: Effect of Camera and Patient Tracker Position and Number of Active Markers



Kenneth R. Gundle1, 2, *, Jedediah K. White3, Ernest U. Conrad3, 4, Randal P. Ching5
1 Oregon Health & Science University, Department of Orthopaedics & Rehabilitation, Portland, USA
2 Portland VA Medical Center, Operative Care Division, Portland, USA
3 University of Washington Medical Center, Department of Orthopaedics & Sports Medicine, Washington, USA
4 Seattle Children’s Hospital, Department of Orthopaedic Surgery, Washington, USA
5 University of Washington Applied Biomechanics Laboratory, Washington, USA


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© 2017 Gundle et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Oregon Health & Science University, Department of Orthopaedics & Rehabilitation, 3181 SW Sam Jackson Park Road, OP31. Portland, OR 97239, Portland, USA; Tel: 503-494-6400; E-mail: gundle@ohsu.edu


Abstract

Introduction:

Surgical navigation systems are increasingly used to aid resection and reconstruction of osseous malignancies. In the process of implementing image-based surgical navigation systems, there are numerous opportunities for error that may impact surgical outcome. This study aimed to examine modifiable sources of error in an idealized scenario, when using a bidirectional infrared surgical navigation system.

Materials and Methods:

Accuracy and precision were assessed using a computerized-numerical-controlled (CNC) machined grid with known distances between indentations while varying: 1) the distance from the grid to the navigation camera (range 150 to 247cm), 2) the distance from the grid to the patient tracker device (range 20 to 40cm), and 3) whether the minimum or maximum number of bidirectional infrared markers were actively functioning. For each scenario, distances between grid points were measured at 10-mm increments between 10 and 120mm, with twelve measurements made at each distance. The accuracy outcome was the root mean square (RMS) error between the navigation system distance and the actual grid distance. To assess precision, four indentations were recorded six times for each scenario while also varying the angle of the navigation system pointer. The outcome for precision testing was the standard deviation of the distance between each measured point to the mean three-dimensional coordinate of the six points for each cluster.

Results:

Univariate and multiple linear regression revealed that as the distance from the navigation camera to the grid increased, the RMS error increased (p<0.001). The RMS error also increased when not all infrared markers were actively tracking (p=0.03), and as the measured distance increased (p<0.001). In a multivariate model, these factors accounted for 58% of the overall variance in the RMS error. Standard deviations in repeated measures also increased when not all infrared markers were active (p<0.001), and as the distance between navigation camera and physical space increased (p=0.005). Location of the patient tracker did not affect accuracy (0.36) or precision (p=0.97)

Conclusion:

In our model laboratory test environment, the infrared bidirectional navigation system was more accurate and precise when the distance from the navigation camera to the physical (working) space was minimized and all bidirectional markers were active. These findings may require alterations in operating room setup and software changes to improve the performance of this system.

Keywords: Surgical Navigation, Computer-assisted surgery, Bone tumors, Registration, Accuracy, Error.