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A Novel Method for Segmentation-Based Semiautomatic Quantitative Evaluation of Metal Artifact Reduction Algorithms

Do, Thuy D., MD*; Sommer, Christof M., MD*,†; Melzig, Claudius, MD*; Nattenmüller, Johanna, MD*; Vollherbst, Dominik, MD; Kauczor, Hans-Ulrich, MD*; Stiller, Wolfram, PhD*; Skornitzke, Stephan, PhD*

doi: 10.1097/RLI.0000000000000549
Original Articles

Objectives The aim of this study was to establish an objective segmentation-based evaluation of metal artifact reduction algorithms in the context of percutaneous microwave ablation in a porcine model.

Materials and Methods Five computed tomography acquisitions from a previous animal study on computed tomography–guided percutaneous applicator positioning for microwave antenna were reconstructed with 6 different algorithms (30 image series total): standard filtered backprojection (B30f) and iterative reconstruction (ADMIRE-I30–1, ADMIRE-I30–3), all with and without metal artifact reduction. For artifact quantification, 3-dimensional segmentation of liver parenchyma without visible artifacts (VLiverReference) and liver volume surrounding the antenna (VLiverVOI) was performed, determining thresholds for artifact segmentation and calculating volume of voxels influenced by artifacts. Objective image analysis was based on relative volume of artifacts, and subjective image quality (ie, metal artifact extent) was evaluated by 2 independent observers. Correlation between objective and subjective evaluation was calculated.

Results Both objective and subjective evaluations showed a significant reduction in metal artifacts when using dedicated metal artifact reduction algorithms (both P < 0.05). No significant reduction in metal artifacts was found when using iterative reconstruction (both P > 0.05). A good correlation between subjective and objective image quality was found (Spearman rank correlation coefficient rs = 0.65; P < 0.05). Interreader agreement was substantial (κ = 0.67).

Conclusions Segmentation-based objective evaluation of metal artifacts shows good agreement with conventional subjective evaluations and offers a promising quantitative and precise approach with limited time expenditure.

From the *Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg;

Clinic for Diagnostic and Interventional Radiology, Klinikum Stuttgart, Stuttgart; and

Clinic for Neuroradiology, University Hospital Heidelberg, Heidelberg, Germany.

Received for publication November 14, 2018; and accepted for publication, after revision, December 22, 2018.

The corresponding author declares that all authors have read the manuscript and gave permission to submit the work in its current version.

Author contribution: All authors have made substantial contributions to conception and design of the study, or acquisition data, or analysis and interpretation of data, as well as to drafting the article or revising it.

Conflicts of interest and sources of funding: Stephan Skornitzke has ownership interests in investment funds containing stock of healthcare companies.

Correspondence to: Stephan Skornitzke, PhD, Clinic for Diagnostic and Interventional Radiology, University Hospital Heidelberg, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany. E-mail:

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