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BACKGROUND AND PURPOSE:Two techniques for metal artefact reduction for computed tomography were studied in order to identify their impact on tumour delineation in radiotherapy. MATERIALS AND METHODS:Using specially designed phantoms containing metal implants (dental, spine and hip) as well as patient images, we investigated the impact of two methods for metal artefact reduction on (A) the size and severity of metal artefacts and the accuracy of Hounsfield Unit (HU) representation, (B) the visual impact of metal artefacts on image quality and (C) delineation accuracy. A metal artefact reduction algorithm (MAR) and two types of dual energy virtual monochromatic (DECT VM) reconstructions were used separately and in combination to identify the optimal technique for each implant site. RESULTS:The artefact area and severity was reduced (by 48-76% and 58-79%, MAR and DECT VM respectively) and accurate Hounsfield-value representation was increased by 22-82%. For each energy, the observers preferred MAR over non-MAR reconstructions (p < 0.01 for dental and hip cases, p < 0.05 for the spine case). In addition, DECT VM was preferred for spine implants (p < 0.01). In all cases, techniques that improved target delineation significantly (p < 0.05) were identified. CONCLUSIONS:DECT VM and MAR techniques improve delineation accuracy and the optimal of reconstruction technique depends on the type of metal implant.

Original publication




Journal article


Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

Publication Date





479 - 486


Department of Oncology, Copenhagen University Hospital Rigshospitalet, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Biomedical Engineering, Department of Electrical Engineering, Technical University of Denmark, Lyngby, Denmark. Electronic address:


Heart, Humans, Breast Neoplasms, Metals, Tomography, X-Ray Computed, Radiotherapy Planning, Computer-Assisted, Artifacts, Sensitivity and Specificity, Cohort Studies, Prospective Studies, Reproducibility of Results, Phantoms, Imaging, Prostheses and Implants, Algorithms, Female