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

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). 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. iMAR effectively reduced hypo- and hyperdense artifacts by solitary application and in combination with VMI. In contrast, solitary application of VMI did not yield sufficient artifact reduction. Optimal quantitative reduction was achieved in VMIiMAR 100 keV for hypodense artifacts and 70 keV for hyperdense artifacts. VMIiMAR 190 keV provided optimal artifact reduction in bones and vessels. In the qualitative evaluation, the extent of artifact reduction received significantly higher ratings on VMIiMAR than CI. VMIiMAR 190 keV was rated best for evaluation of artifact-affected soft tissue and bone, VMI did not yield significant improvements. 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. 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.