Improvement of dose calculation in radiation therapy due to metal artifact correction using the augmented likelihood image reconstruction

Prediction of proton beam range in phantom with metals based on monochromatic energy CT images

The purpose of the study was to evaluate the accuracy of monochromatic energy (MonoE) computed tomography (CT) images reconstructed by spectral CT in predicting the stopping power ratio $( SP{R}_w)$ of materials in the presence of metal. The CIRS062 phantom was scanned three times using spectral CT. In the first scan, a solid water insert was placed at the center of the phantom $(C{T}_{no\ metal})$. In the second scan, the solid water insert was replaced with a titanium alloy femoral head $(C{T}_{metal})$. The metal artifact reduction (MAR) algorithm was used in the last scan $(C{T}_{metal+ MAR})$. The MonoE-CT images of 40 keV and 80 keV were reconstructed. Finally, the single-energy CT method (SECT) and the dual-energy CT method (DECT) were used to calculate the $SP{R}_w$. The mean absolute error (MAE) of the $SP{R}_w$ of the inner layer inserts calculated by the SECT method were 3.19%, 13.88% and 2.71%, corresponding to $C{T}_{no\ metal}$, $C{T}_{metal}$ and $C{T}_{metal+ MAR}$, respectively. For the outer layer inserts, the MAE of $SP{R}_w$ were 3.43%, 5.42% and 2.99%, respectively. Using the DECT method, the MAE of the $SP{R}_w$ of the inner layer inserts was 1.30%, 3.69% and 1.46% and the MAE of the outer layer inserts- was 1.34%, 1.36% and 1.05%. The studies shows that, compared with the SECT method, the accuracy of the DECT method in predicting the $SP{R}_w$ of a material is more robust to the presence of metal. Using the MAR algorithm when performing CT scans can further improve the accuracy of predicting the SPR of materials in the presence of metal.

Neural Network Performance Evaluation of Simulated and Genuine Head-and-Neck Computed Tomography Images to Reduce Metal Artifacts

Background

This study evaluated the performances of neural networks in terms of denoizing metal artifacts in computed tomography (CT) images to improve diagnosis based on the CT images of patients.

Methods

First, head-and-neck phantoms were simulated (with and without dental implants), and CT images of the phantoms were captured. Six types of neural networks were evaluated for their abilities to reduce the number of metal artifacts. In addition, 40 CT patients' images with head-and-neck cancer (with and without teeth artifacts) were captured, and mouth slides were segmented. Finally, simulated noisy and noise-free patient images were generated to provide more input numbers (for training and validating the generative adversarial neural network [GAN]).

Results

Results showed that the proposed GAN network was successful in denoizing artifacts caused by dental implants, whereas more than 84% improvement was achieved for images with two dental implants after metal artifact reduction (MAR) in patient images.

Conclusion

The quality of images was affected by the positions and numbers of dental implants. The image quality metrics of all GANs were improved following MAR comparison with other networks.

To Study the Impact of Different Optimization Methods on Intensity-Modulated Radiotherapy and Volumetric-Modulated Arc Therapy Plans for Hip Prosthesis Patients

Purpose

To study the impact of different optimization methods in dealing with metallic hip implant using intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT) techniques.

Materials and Methods

A cohort of 16 patients having metallic implants was selected for the study. Three sets of IMRT and VMAT plans were generated. Set 1 IMRT (IM_Base), VMAT (VM_Base) without any restrictions on beam entry and exit, set 2 (IM_ENT and VM_ENT) optimizer restricts the beam entry and set 3 (IM_EXT+ENT), neither entry nor exit doses were allowed toward the metallic implant.

Results

There was no significant difference in target (D95%) and organ-at-risk doses between IM_Base and IM_ENT. There were significant (P = 0.002) improvements in planning target volume (PTV) V95% and homogeneity from IM_EXT+ENT to IM_ENT. There was no significant difference in plan quality between VM_Base and VM_ENT. There were significant (P = 0.005) improvements in PTV, V95%, homogeneity from VM_EXT+ENT to VM_ENT. V40Gy, V30Gy for bladder, rectum, bowel, and bowel maximum dose decreases significantly (P < 0.005) in IM_ENT compared to IM_EXT+ENT, but not significant for VMAT plans. Similarly, there was a significant decrease in dose spill outside target (P < 0.05) comparing 40%, 50%, 60%, and 70% dose spills for IM_ENT compared to IM_EXT+ENT, but variations among VMAT plans are insignificant. VMAT plans were always superior to IMRT plans for the same optimization methods.

Conclusion

The best approach is to plan hip prosthesis cases with blocked entry of radiation beam for IMRT and VMAT. The VMAT plans had more volumetric coverage, fewer hotspots, and lesser heterogeneity.

Bilateral metallic hip implants: Are avoidance sectors necessary for pelvic VMAT treatments?

PURPOSE

Metallic hip implants (MHI) are common in elderly patients. For pelvic cancers radiotherapy, conventional approaches consist of MHI avoidance during treatment planning, which leads, especially in case of bilateral MHI, to a decreased quality or increased complexity of the treatment plan. The aim of this study is to investigate the necessity of using avoidance sectors (AvSe) using a 2-arcs coplanar pelvic volumetric modulated arc-therapy (VMAT) planning.

METHODS

We evaluated: (1) The dose calculation error of a static 6MV open beam traversing a MHI; (2) The magnitude of an error's decrease within the planning target volume (PTV) for a 360° VMAT treatment without AvSe as compared to the static open beam; (3) The dosimetric influence of MHI misalignment generated by patient's repositioning rolls during image-guided radiotherapy (IGRT).

RESULTS

(1) In the static 6MV beam configuration, for distances between 0.5cm and 6cm from the MHI, the median (maximum, number of points) dose calculation error was -1.55% (-2.5%, 11); (2) Compared to the static open beam, in the 360° VMAT treatment without AvSe a simulated error was decreased by a factor of 4.4/2.4 (median/minimum); (3) MHI anterior-posterior misalignment exceeding 0.6cm, resulted in error at PTV surface of >2%.

CONCLUSIONS

A standard 2 coplanar arcs 360° VMAT treatment, with dedicated artifact reduction algorithms applied, decreased the error of static beam traversing MHI, in patients presenting a bilateral MHI and might be used to treat the pelvic region without MHI avoidance.

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

Metal artifact reduction (MAR) methods are used to reduce artifacts from metals or metal components in computed tomography (CT). In radiotherapy (RT), CT is the most used imaging modality for planning, whose quality is often affected by metal artifacts. The aim of this study is to systematically review the impact of MAR methods on CT Hounsfield Unit values, contouring of regions of interest, and dose calculation for RT applications. This systematic review is performed in accordance with the PRISMA guidelines; the PubMed and Web of Science databases were searched using the main keywords "metal artifact reduction", "computed tomography" and "radiotherapy". A total of 382 publications were identified, of which 40 (including one review article) met the inclusion criteria and were included in this review. The selected publications (except for the review article) were grouped into two main categories: commercial MAR methods and research-based MAR methods. Conclusion: The application of MAR methods on CT scans can improve treatment planning quality in RT. However, none of the investigated or proposed MAR methods was completely satisfactory for RT applications because of limitations such as the introduction of other errors (e.g., other artifacts) or image quality degradation (e.g., blurring), and further research is still necessary to overcome these challenges.

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

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 the following 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 six metal inserts and nine 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 in the automatic algorithms, and thus support for hypothesis II, and found the MR-based kerMAR to improve upon oMAR, supporting hypothesis III.

The effects of the orthopedic metal artifact reduction (O-MAR) algorithm on contouring and dosimetry of head and neck radiotherapy patients

Metallic objects, such as dental fillings, cause artifacts in computed tomography (CT) scans. We quantify the contouring and dosimetric effects of Orthopedic Metal Artifact Reduction (O-MAR), in head and neck radiotherapy. The ease of organ contouring was assessed by having a radiation oncologist identify the CT data set with or without O-MAR for each of 28 patients that was easier to contour. The effect on contouring was quantified further by having the physician recontour parotid glands, previously drawn by him on the O-MAR scans, on uncorrected scans, and calculating the Dice coefficent (a measure of overlap) for the contours. Radiotherapy plans originally generated on scans reconstructed with O-MAR were recalculated on scans without metal artifact correction. The study was done using the Analytical Anisotropic Algorithm (AAA) dose calculation algorithm. The 15 patients with a planning target volume (PTV) extending to the same slice as the artifacts were used for this part of the study. The normal tissue doses were not significantly affected. The PTV mean dose and V95 were not affected, but the cold spots became less severe in the O-MAR corrected plans, with the minimum point dose on average being 4.1% higher. In 79% of the cases, the radiation oncologist identified the O-MAR scan as easier to contour; in 11% he chose the uncorrected scan and in 11% the scans were judged to have equal quality. A total of nine parotid glands (on both scans-18 contours in total) in 5 patients were recontoured. The average Dice coefficient for parotids drawn with and without O-MAR was found to be 0.775 +/- 0.045. The O-MAR algorithm does not produce a significant dosimetric effect in head and neck plans when using the AAA dose calculation algorithm. It can therefore be used for improved contouring accuracy without updating the critical structure tolerance doses and target coverage expectations.