Dental implant artifacts: Evaluation of photon counting CT-derived virtual monoenergetic images in combination with iterative metal artifact reduction algorithms

OBJECTIVES: To examine photon counting-CT (PCCT)-derived virtual monoenergetic images (VMI) in combination with iterative metal artifacts reduction algorithms (iMAR) for artifact reduction in patients with dental implants (DI). METHODS: 49 patients with DI were retrospectively included in the study. Polyenergetic CT images (CI), VMIs with different energy levels (70-190 keV) without and the same images with iMAR were examined. ROI-based measurements of hypo- and hyperdense artifacts in different tissues (soft tissues, bones, vessels) were performed. Qualitative assessment of the extent of artifacts, surrounding bone and soft tissue was performed by two radiologists using a Likert scale. RESULTS: 190 keV was rated best for evaluation of artifact-affected soft tissue and bone, VMI did not yield significant improvements. CONCLUSIONS: iMAR as a standalone approach and the combination of iMAR and VMI significantly reduce artifacts by DI and improve the assessability of adjacent tissue. Combination of iMAR and VMI worked best at keV levels higher than 100 keV. CLINICAL RELEVANCE STATEMENT: Combination of iMAR and PCCT-derived VMI is a useful approach for enhancing the diagnostic assessability of the maxillofacial area in patients with dental implants.