Observer Evaluation of a Metal Artifact Reduction Algorithm Applied to Head and Neck Cone Beam Computed Tomographic
Mark Korpics1, Murat Surucu1, Ibrahim Mescioglu1
1Department of Radiation Oncology, Loyola University Medical Center, Maywood, Illinois.
Purpose And Objectives:
To quantify, through an observer study, the reduction in metal artifacts on cone beam computed tomographic (CBCT) images using a projection-interpolation algorithm, on images containing metal artifacts from dental fillings and implants in patients treated for head and neck (H&N) cancer.
Methods And Materials:
An interpolation-substitution algorithm was applied to H&N CBCT images containing metal artifacts from dental fillings and implants. Image quality with respect to metal artifacts was evaluated subjectively and objectively. First, 6 independent radiation oncologists were asked to rank randomly sorted blinded images (before and after metal artifact reduction) using a 5-point rating scale (1 = severe artifacts; 5 = no artifacts). Second, the standard deviation of different regions of interest (ROI) within each image was calculated and compared with the mean rating scores.
Results:
The interpolation-substitution technique successfully reduced metal artifacts in 70% of the cases. From a total of 60 images from 15 H&N cancer patients undergoing image guided radiation therapy, the mean rating score on the uncorrected images was 2.3 ± 1.1, versus 3.3 ± 1.0 for the corrected images. The mean difference in ranking score between uncorrected and corrected images was 1.0 (95% confidence interval: 0.9-1.2, P<.05). The standard deviation of each ROI significantly decreased after artifact reduction (P<.01). Moreover, a negative correlation between the mean rating score for each image and the standard deviation of the oral cavity and bilateral cheeks was observed.
Conclusion:
The interpolation-substitution algorithm is efficient and effective for reducing metal artifacts caused by dental fillings and implants on CBCT images, as demonstrated by the statistically significant increase in observer image quality ranking and by the decrease in ROI standard deviation between uncorrected and corrected images.
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