Optimal number and distribution of points selected on the vertebra for surface matching in CT-based spinal navigation.
OBJECTIVE
CT-based spinal navigation systems have widespread clinical applications, and spatial registration is a major source of the application error for these systems. However, the feedback that a surgeon may receive from the system, i.e., the surface registration error (SRE), is misleading, and it is still unclear how to achieve an optimal registration. The objective of this study was to investigate how the number and distribution of the points selected on the posterior surface of the vertebra influence the spatial registration accuracy, and how an optimal distribution can be achieved.


METHODS
We simulated the spatial registration in the image space to investigate how the number and distribution of points selected on the vertebra influenced the target registration error (TRE). First, we divided the posterior side of the vertebra into five zones and chose 30 points, evenly distributed in different combinations of zones, to simulate the points selected on the vertebra during real navigation. We registered these points to a point cloud representing the surface of the vertebra and calculated the SRE and TRE in the region of interest to determine which combination of zones was optimal. We then chose different numbers of points in the optimal zone combination to study the influence of the number of points on the registration accuracy.


RESULTS
The combination including the lamina, both sides of the spinous process, and the four articular processes resulted in a smaller TRE than those combinations including only the lamina or the lamina with one other zone. Further enlarging the area by adding the transverse processes made no difference. In addition, the TRE decreased with the increase in the number of points, while the SRE remained almost unchanged.


CONCLUSIONS
Surgeons should select approximately 30 points distributed evenly across the lamina, both sides of the spinous process, and the four articular processes for surface matching in CT-based spinal navigation.
Digital Medical Research Center of Shanghai Medical School, Fudan University, Shanghai, China.
Manning
M
Wang
Zhijian
Z
Song
D000465:Algorithms; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008159:Lumbar Vertebrae / Q000000981:diagnostic imaging* / Q000601:surgery; D008875:Middle Aged; D013122:Spinal Diseases / Q000000981:diagnostic imaging* / Q000601:surgery; D013123:Spinal Fusion / Q000379:methods*; D025321:Surgery, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*