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

• Published in: Journal of Nuclear Medicine Vol. 56; no. 1; pp. 93 - 97
• Main Authors: Burger, Irene A., Wurnig, Moritz C., Becker, Anton S., Kenkel, David, Delso, Gaspar, Veit-Haibach, Patrick, Boss, Andreas
• Format: Journal Article
• Language: English
• Published: United States Society of Nuclear Medicine 01.01.2015
• Subjects: Algorithms; Dental care; Dental Implants; Female; Humans; Image Processing, Computer-Assisted - methods; Magnetic Resonance Imaging; Male; Metals; Multimodal Imaging; NMR; Nuclear magnetic resonance; Nuclear medicine; Oncology; Positron-Emission Tomography; Retrospective Studies; Tomography, X-Ray Computed; Transplants & implants; μ maps; MRI based attenuation correction; signal void
• ISSN: 0161-5505; 1535-5667; 2159-662X; 2159-662X; 1535-5667
• DOI: 10.2967/jnumed.114.145862

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. 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. 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 mm(2) to 202 ± 119 mm(2) (P = 0.016). 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.