To Örebro University

PURPOSE: To evaluate two commercial CT metal artifact reduction (MAR) algorithms for use in proton treatment planning in the head and neck (H&N) area.

METHODS: An anthropomorphic head phantom with removable metallic implants (dental fillings or neck implant) was CT-scanned to evaluate the O-MAR (Philips) and the iMAR (Siemens) algorithms. Reference images were acquired without any metallic implants in place. Water equivalent thickness (WET) was calculated for different path directions and compared between image sets. Images were also evaluated for use in proton treatment planning for parotid, tonsil, tongue base, and neck node targets. The beams were arranged so as to not traverse any metal prior to the target, enabling evaluation of the impact on dose calculation accuracy from artifacts surrounding the metal volume. Plans were compared based on γ analysis (1 mm distance-to-agreement/1% difference in local dose) and dose volume histogram metrics for targets and organs at risk (OARs). Visual grading evaluation of 30 dental implant patient MAR images was performed by three radiation oncologists.

RESULTS: In the dental fillings images, ΔWET along a low-density streak was reduced from -17.0 to -4.3 mm with O-MAR and from -16.1 mm to -2.3 mm with iMAR, while for other directions the deviations were increased or approximately unchanged when the MAR algorithms were used. For the neck implant images, ΔWET was generally reduced with MAR but residual deviations remained (of up to -2.3 mm with O-MAR and of up to -1.5 mm with iMAR). The γ analysis comparing proton dose distributions for uncorrected/MAR plans and corresponding reference plans showed passing rates >98% of the voxels for all phantom plans. However, substantial dose differences were seen in areas of most severe artifacts (γ passing rates of down to 89% for some cases). MAR reduced the deviations in some cases, but not for all plans. For a single patient case dosimetrically evaluated, minor dose differences were seen between the uncorrected and MAR plans (γ passing rate approximately 97%). The visual grading of patient images showed that MAR significantly improved image quality (P < 0.001).

CONCLUSIONS: O-MAR and iMAR significantly improved image quality in terms of anatomical visualization for target and OAR delineation in dental implant patient images. WET calculations along several directions, all outside the metallic regions, showed that both uncorrected and MAR images contained metal artifacts which could potentially lead to unacceptable errors in proton treatment planning. ΔWET was reduced by MAR in some areas, while increased or unchanged deviations were seen for other path directions. The proton treatment plans created for the phantom images showed overall acceptable dose distributions differences when compared to the reference cases, both for the uncorrected and MAR images. However, substantial dose distribution differences in the areas of most severe artifacts were seen for some plans, which were reduced by MAR in some cases but not all. In conclusion, MAR could be beneficial to use for proton treatment planning; however, case-by-case evaluations of the metal artifact-degraded images are always recommended.