Metal artefact reduction for accurate tumour delineation in radiotherapy

Research output: Contribution to journalJournal articleResearchpeer-review

David Gergely Kovacs, Laura A. Rechner, Ane L. Appelt, Anne K. Berthelsen, Junia C. Costa, Jeppe Friborg, Gitte F. Persson, Jens Peter Bangsgaard, Lena Specht, Marianne C. Aznar

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 languageEnglish
JournalRadiotherapy and Oncology
Volume126
Issue number3
Pages (from-to)479-486
ISSN0167-8140
DOIs
Publication statusPublished - 2018

    Research areas

  • Delineation uncertainty, Dual energy CT, IGRT, Iterative metal artefact reduction

ID: 189150907