Hybrid PET/MR Imaging: An Algorithm to Reduce Metal Artifacts from Dental Implants in Dixon-Based Attenuation Map Generation Using a Multiacquisition Variable-Resonance Image Combination Sequence

It was the aim of this study to implement an algorithm modifying Dixon-based MR imaging datasets for attenuation correction in hybrid PET/MR imaging with a multiacquisition variable resonance image combination (MAVRIC) sequence to reduce metal artifacts. Methods: After ethics approval, in 8 oncologic patients with dental implants data were acquired in a trimodality setup with PET/CT and MR imaging. The protocol included a whole-body 3-dimensional dual gradient-echo sequence (Dixon) used for MR imaging–based PET attenuation correction and a high-resolution MAVRIC sequence, applied in the oral area compromised by dental implants. An algorithm was implemented correcting the Dixon-based μ maps using the MAVRIC in areas of Dixon signal voids. The artifact size of the corrected μ maps was compared with the uncorrected MR imaging μ maps. Results: The algorithm was robust in all patients. There was a significant reduction in mean artifact size of 70.5% between uncorrected and corrected μ maps from 697 ± 589 mm2 to 202 ± 119 mm2 (P = 0.016). Conclusion: The proposed algorithm could improve MR imaging–based attenuation correction in critical areas, when standard attenuation correction is hampered by metal artifacts, using a MAVRIC.