MR‐based CT metal artifact reduction for head‐and‐neck photon, electron, and proton radiotherapy

Abstract

Purpose: We investigated the impact on Computed Tomography (CT) image quality and photon, electron and proton head-and-neck (H&N) radiotherapy (RT) dose calculations of three CT metal artifact reduction (MAR) approaches: A CT-based algorithm (oMAR Philips Healthcare), manual water override and our recently presented, Magnetic Resonance (MR)-based kerMAR algorithm. We considered three hypotheses: I: Manual water override improves MAR over the CT- and MR-based alternatives; II: The automatic algorithms (oMAR and kerMAR) improve MAR over the uncorrected CT; III: kerMAR improves MAR over oMAR. Methods: We included a veal shank phantom with/without 6 metal inserts and 9 H&N RT patients with dental implants. We quantified the MAR capabilities by the reduction of outliers in the CT value distribution in regions of interest, and the change in particle range and photon depth at maximum dose. Results: Water override provided apparent image improvements in the soft tissue region but insignificantly or negatively influenced the dose calculations. We however found significant improvements in image quality and particle range impact, compared to the uncorrected CT, when using oMAR and kerMAR. kerMAR in turn provided superior improvements in terms of high intensity streak suppression compared to oMAR, again with associated impacts on the particle range estimates. Conclusion: We found no benefits of the water override compared to the rest, and tentatively reject hypothesis I. We however found improvements with the automatic algorithms, and thus support for hypothesis II, and found the MR-based kerMAR to improve upon oMAR, supporting hypothesis III.

The application of metal artifact reduction methods on computed tomography scans for radiotherapy applications: A literature review

“…Based on the intensity values of pixels on the paired MRI slice and HU values from the artifact‐free CT slice, HU values of pixels on CT art slice are calculated. Nielsen et al evaluated their proposed MR‐based MAR algorithm (kerMAR) 80 to reduce the metal artifacts 84 . kerMAR requires aligned CT and MRI scans of the same anatomy.…”

“…The comparison of CT art and CT cor with CT ref showed a reduction in absolute mean HU difference from 495 HU to 108 HU in the brain, and from 370 HU to 92 HU in the H&N. The HU of CT ref was not reported. Nielsen et al evaluated their kerMAR method for image quality improvements 84 . During the image quality evaluation, CT scans from a custom‐made veal shank phantom with metal inserts and clinical H&N CT scans with dental implants were used.…”

“…On clinical CT scans of a brain and H&N, the application of this proposed method improved the absolute ΔWET from 2.4 cm in brain and 1.7 cm in H&N to less than 2 mm for both cases. In a study by Nielsen et al, 84 the performance of kerMAR was studied and compared with O‐MAR for dosimetric impact in photon, electron, and proton therapy. In the phantom evaluation, a depth/range calculation on CT cor for the proton, photons, and electrons did not show any significant difference ( P > 0.05 ) between the O‐MAR and kerMAR.…”

“…Research-based MAR algorithms based on traditional image processing methods were evaluated for their ability to restore HU values and their ability to improve image quality of CT scans which will be used for RT applications. 84 During the image quality evaluation, CT scans from a custom-made veal shank phantom with metal inserts and clinical H&N CT scans with dental implants were used. In addition to kerMAR, also O-MAR was applied to the CT scans for a comparison.…”

“…On clinical CT scans of a brain and H&N, the application of this proposed method improved the absolute ΔWET from 2.4 cm in brain and 1.7 cm in H&N to less than 2 mm for both cases. In a study by Nielsen et al, 84 ALIR was studied by Ziemann et al 92 To simulate a pelvis with bilateral hip prostheses, a polymethylmethacrylate phantom with two SS rods was CT scanned. Then, ALIR, linear interpolation (LI), and density correction MAR methods were applied to create corresponding CT cor .…”