NDLI: Accuracy Assessment of Percutaneous Pedicle Screw Placement Using Cone Beam Computed Tomography with Metal Artifact Reduction

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Accuracy Assessment of Percutaneous Pedicle Screw Placement Using Cone Beam Computed Tomography with Metal Artifact Reduction

Content Provider	MDPI
Author	Dirk, Schäfer Charles, Yann Philippe Ansari, Rawan Al Collinet, Arnaud Marini, Pierre De Schwartz, Jean Nachabe, Rami Brendel, Bernhard Gangi, Afshin Cazzato, Roberto Luigi
Copyright Year	2022
Description	Metal artifact reduction (MAR) algorithms are used with cone beam computed tomography (CBCT) during augmented reality surgical navigation for minimally invasive pedicle screw instrumentation. The aim of this study was to assess intra- and inter-observer reliability of pedicle screw placement and to compare the perception of baseline image quality (NoMAR) with optimized image quality (MAR). CBCT images of 24 patients operated on for degenerative spondylolisthesis using minimally invasive lumbar fusion were analyzed retrospectively. Images were treated using NoMAR and MAR by an engineer, thus creating 48 randomized files, which were then independently analyzed by 3 spine surgeons and 3 radiologists. The Gertzbein and Robins classification was used for screw accuracy rating, and an image quality scale rated the clarity of pedicle screw and bony landmark depiction. Intra-class correlation coefficients (ICC) were calculated. NoMAR and MAR led to similarly good intra-observer (ICC > 0.6) and excellent inter-observer (ICC > 0.8) assessment reliability of pedicle screw placement accuracy. The image quality scale showed more variability in individual image perception between spine surgeons and radiologists (ICC range 0.51–0.91). This study indicates that intraoperative screw positioning can be reliably assessed on CBCT for augmented reality surgical navigation when using optimized image quality. Subjective image quality was rated slightly superior for MAR compared to NoMAR.
Starting Page	4615
e-ISSN	14248220
DOI	10.3390/s22124615
Journal	Sensors
Issue Number	12
Volume Number	22
Language	English
Publisher	MDPI
Publisher Date	2022-06-18
Access Restriction	Open
Subject Keyword	Sensors Orthopedics Augmented Reality Surgical Navigation Cone Beam Computed Tomography Metal Artifact Reduction Algorithm Screw Accuracy Image Quality
Content Type	Text
Resource Type	Article

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