Application of a Metal Artifact Reduction Algorithm for C-Arm Cone-Beam CT: Impact on Image Quality and Diagnostic
Arne Estler1, Malte Bongers2, Christoph Thomas3
1Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Hoppe-Seyler-Strasse 3, 72076, Tübingen, Germany. arne.estler@med.uni-tuebingen.de.
Objective:
The objective of this study was to evaluate the potential benefit of a dedicated cone-beam-CT streak metal artifact removal technique (SMART) in terms of both image quality and diagnostic confidence in patients undergoing bronchial artery embolization.
Methods:
A total of 17 patients were included in this retrospective study. The SMART algorithm was applied to images containing streak artifacts generated by a radiopaque intra-arterial catheter tip. Quantitative evaluation of artifact severity was performed via measurement of the Hounsfield units along a closed loop surrounding the catheter tip and was conducted in the frequency domain following the application of the discrete Fourier transform to the measured data. A high proportion of power in the low frequencies of the resulting spectrum indicated a high level of streak artifacts. Qualitative evaluation of diagnostic confidence was performed using a 4-point Likert scale.
Results:
Both quantitative and qualitative evaluation demonstrated a significant reduction in artifact severity using the SMART algorithm. Quantitative evaluation demonstrated a mean artifact reduction of 22.5% using SMART compared to non-SMART images (p < 0.001). Qualitative evaluation demonstrated the greatest artifact reduction at the inner and outer aortic curvature, as well as immediately surrounding the tip of the catheter. In 6 of 17 cases, the use of the SMART algorithm yielded additional clinical information, increasing mean diagnostic confidence from 3.17 to 3.78 (p < 0.001).
Conclusion:
The SMART algorithm allows for efficient reduction of metal artifacts introduced by radiopaque catheter tips during cone-beam CT. Using this algorithm, diagnostic images of the aortic arch were significantly improved both quantitatively and qualitatively, yielding clinically relevant levels of enhanced diagnostic confidence. These results demonstrate that the SMART algorithm improves diagnostic and clinical characterization of the course of bronchial arteries on CBCT images, potentially improving the accuracy and clinical efficacy of bronchial artery embolization.
Level Of Evidence:
3.
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