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Erschienen in:
10.07.2019 | Original Article
A comparative analysis of intensity-based 2D–3D registration for intraoperative use in pedicle screw insertion surgeries
Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 10/2019
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Abstract
Purpose
Although multiple algorithms have been reported that focus on improving the accuracy of 2D–3D registration techniques, there has been relatively little attention paid to quantifying their capture range. In this paper, we analyze the capture range for a number of variant formulations of the 2D–3D registration problem in the context of pedicle screw insertion surgery.
Methods
We tested twelve 2D–3D registration techniques for capture range under different clinically realistic conditions. A registration was considered as successful if its error was less than 2 mm and 2° in 95% of the cases. We assessed the sensitivity of capture range to a variety of clinically realistic parameters including: X-ray contrast, number and configuration of X-rays, presence or absence of implants in the image, inter-subject variability, intervertebral motion and single-level vs multi-level registration.
Results
Gradient correlation + Powell optimizer had the widest capture range and the least sensitivity to X-ray contrast. The combination of 4 AP + lateral X-rays had the widest capture range (725 mm2). The presence of implant projections significantly reduced the registration capture range (up to 84%). Different spine shapes resulted in minor variations in registration capture range (SD 78 mm2). Intervertebral angulations of less than 1.5° had modest effects on the capture range.
Conclusions
This paper assessed capture range of a number of variants of intensity-based 2D–3D registration algorithms in clinically realistic situations (for the use in pedicle screw insertion surgery). We conclude that a registration approach based on the gradient correlation similarity and the Powell’s optimization algorithm, using a minimum of two C-arm images, is likely sufficiently robust for the proposed application.