Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Nov;46(11):5326-5335.
doi: 10.1002/mp.13819. Epub 2019 Sep 26.

Effects of metal implants and a metal artifact reduction tool on calculation accuracy of AAA and Acuros XB algorithms in small fields

Affiliations

Effects of metal implants and a metal artifact reduction tool on calculation accuracy of AAA and Acuros XB algorithms in small fields

Yucel Akdeniz et al. Med Phys. 2019 Nov.

Abstract

Purpose: In this study, the dosimetric accuracy of analytical anisotropic algorithm (AAA) and Acuros XB (AXB) dose calculation algorithms (Varian Medical Systems, Palo Alto, CA) was investigated for small radiation fields incident on phantoms of various metals that include stainless steel grade 316L (SS316L) and titanium alloy grade 5 (Ti5) implants. In addition, the effects of using metal artifact reduction for orthopedic implants (O-MAR, Philips Healthcare, Cleveland, OH) were evaluated.

Methods: The evaluations of AAA and AXB were performed by comparing the crossline profiles calculated by AAA and AXB with GafChromicTM EBT3 film measurements at the phantom-implant interfaces and in close vicinity of implant materials for small field sizes (1 × 1 cm2 , 2 × 2 cm2 , 3 × 3 cm2 , and 4 × 4 cm2 ) of a 6 MV flattening filter free photon beam. O-MAR corrected and uncorrected (UC) computed tomography (CT) images were used for dose calculations. The values of average and standard deviations (SD) of Hounsfield unit (HU) for selected regions of each case were evaluated. The differences in average dose percentages in defined regions were calculated to quantify the relative dosimetric changes between doses calculated on UC and O-MAR corrected CT images.

Results: Compared to UC images, the values of SD were reduced, and the average HU became closer to its reference value in the O-MAR images. There was some discrepancy in average dose percentage differences between calculations using UC and O-MAR images at 1 cm above the SS316L implant (average dose percentage differences were AXB/UC = 5.9% and AXB/O-MAR = -1.2%; AAA/UC = 2.2%, and AAA/O-MAR = -0.8%). Neither AAA nor AXB algorithms predict increase in dose at upper phantom-implant interface (4.9%, 9.9%. 13.5%, and 13.8% for the fields from 1 × 1 cm2 to 4 × 4 cm2 , respectively). At the side of the SS316L implant (where dark streak artifacts exist), dose difference averages were estimated as - 1.1% and 22.3% when AXB/O-MAR and AXB/UC calculations are compared with EBT3 measurements, respectively. Dose predictions at 1 cm below the SS316L implant were underestimated by AXB/O-MAR (average -0.5%) and AXB/UC (average 2.0%).

Conclusions: The O-MAR tool was shown to have a favorable dosimetric effect or no effect on the calculations in the upper proximity of the implant materials. The dose differences between EBT3 film measurements and calculations at upper phantom-implant interfaces were smaller when they were calculated using O-MAR images. However, the dose differences increased when O-MAR corrected images were used for AAA calculations at lower phantom-implant interfaces. Use of O-MAR enabled closer agreement for the AXB algorithm, especially in the dark streak artifact regions. The O-MAR algorithm should be used when the dose is calculated with the AXB algorithm in cases of patients with the metal implants. The estimations using AAA and AXB algorithms, in phantom setups, with Ti5 implant material were found to be closer to the EBT3 film measurements, when compared with the same estimations using SS316L implant material.

Keywords: AAA; Acuros XB; implant materials; metal artifact reduction; small fields.

PubMed Disclaimer

Similar articles

Cited by

References

    1. Wagenaar D, van der Graaf ER, van der Schaaf A, Greuter MJW. Quantitative comparison of commercial and non-commercial metal artifact reduction techniques in computed tomography. PLoS ONE. 2015;10(6):e0127932.
    1. Kidoh M, Nakaura T, Nakamura S, et al. Reduction of dental metallic artefacts in CT: value of a newly developed algorithm for metal artefact reduction (O-MAR). Clin Radiol. 2014;69:e11-e16.
    1. Yasaka K, Maeda E, Hanaoka S, Katsura M, Sato J, Ohtomo K. Single-energy metal artifact reduction for helical computed tomography of the pelvis in patients with metal hip prostheses. Jpn J Radiol. 2016;34:625-632.
    1. Subhas N, Primak AN, Obuchowski NA, et al. Iterative metal artifact reduction: evaluation and optimization of technique. Skeletal Radiol. 2014;43:1729-1735.
    1. Kwon H, Kim KS, Chun YM, et al. Evaluation of a commercial orthopaedic metal artefact reduction tool in radiation therapy of patients with head and neck cancer. Br J Radiol. 2015;88:13-22.

LinkOut - more resources