Metal artifact reduction through MVCBCT and kVCT in radiotherapy

Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy

This paper proposes a metal artifact reduction method of using MV-CBCT images to correct metal artifacts in kV-CT images, especially for the complex metal artifacts caused by multi-metal interaction of patients with head and neck tumors. The different tissue regions are segmented in the MV-CBCT images to obtain template images and the metal region is segmented in the kV-CT images. Forward projection is performed to get sinogram of the template images, kV-CT images and metal region images. Artifact images can be reconstructed through those sonograms. Corrected images is generated by subtracting the artifact images from the original kV-CT images. After the first correction, the template images are generated again and brought into the previous step for iteration to get better correction result. CT data set of 7 patients are used in this study, compared with linear interpolation metal artifact (LIMAR) and normalized metal artifact reduction method, mean relative error of CT value is reduced by 50.5% and 63.3%, noise is reduced by 56.2% and 58.9%. The Identifiability Score of the tooth, upper/lower jaw, tongue, lips, masseter muscle and cavity in the corrected images by the proposed method have significantly improved (P < 0.05) than original images. The artifacts correction method proposed in this paper can effectively remove the metal artifacts in the images and greatly improve the CT value accuracy, especially in the case of multi-metal and complex metal implantation.

Metal artifact reduction in kV CT images throughout two-step sequential deep convolutional neural networks by combining multi-modal imaging (MARTIAN)

This work attempted to construct a new metal artifact reduction (MAR) framework in kilo-voltage (kV) computed tomography (CT) images by combining (1) deep learning and (2) multi-modal imaging, defined as MARTIAN (Metal Artifact Reduction throughout Two-step sequentIAl deep convolutional neural Networks). Most CNNs under supervised learning require artifact-free images to artifact-contaminated images for artifact correction. Mega-voltage (MV) CT is insensitive to metal artifacts, unlike kV CT due to different physical characteristics, which can facilitate the generation of artifact-free synthetic kV CT images throughout the first network (Network 1). The pairs of true kV CT and artifact-free kV CT images after post-processing constructed a subsequent network (Network 2) to conduct the actual MAR process. The proposed framework was implemented by GAN from 90 scans for head-and-neck and brain radiotherapy and validated with 10 independent cases against commercial MAR software. The artifact-free kV CT images following Network 1 and post-processing led to structural similarity (SSIM) of 0.997, and mean-absolute-error (MAE) of 10.2 HU, relative to true kV CT. Network 2 in charge of actual MAR successfully suppressed metal artifacts, relative to commercial MAR, while retaining the detailed imaging information, yielding the SSIM of 0.995 against 0.997 from the commercial MAR.

A novel approach for eliminating metal artifacts based on MVCBCT and CycleGAN

PURPOSE

To develop a metal artifact reduction (MAR) algorithm and eliminate the adverse effects of metal artifacts on imaging diagnosis and radiotherapy dose calculations.

METHODS

Cycle-consistent adversarial network (CycleGAN) was used to generate synthetic CT (sCT) images from megavoltage cone beam CT (MVCBCT) images. In this study, there were 140 head cases with paired CT and MVCBCT images, from which 97 metal-free cases were used for training. Based on the trained model, metal-free sCT (sCT_MF) images and metal-containing sCT (sCT_M) images were generated from the MVCBCT images of 29 metal-free cases and 14 metal cases, respectively. Then, the sCT_MF and sCT_M images were quantitatively evaluated for imaging and dosimetry accuracy.

RESULTS

The structural similarity (SSIM) index of the sCT_MF and metal-free CT (CT_MF) images were 0.9484, and the peak signal-to-noise ratio (PSNR) was 31.4 dB. Compared with the CT images, the sCT_MF images had similar relative electron density (RED) and dose distribution, and their gamma pass rate (1 mm/1%) reached 97.99% ± 1.14%. The sCT_M images had high tissue resolution with no metal artifacts, and the RED distribution accuracy in the range of 1.003 to 1.056 was improved significantly. The RED and dose corrections were most significant for the planning target volume (PTV), mandible and oral cavity. The maximum correction of Dmean and D50 for the oral cavity reached 90 cGy.

CONCLUSIONS

Accurate sCT_M images were generated from MVCBCT images based on CycleGAN, which eliminated the metal artifacts in clinical images completely and corrected the RED and dose distributions accurately for clinical application.

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.

Characterization of the Megavoltage Cone-Beam Computed Tomography (MV-CBCT) System on HalcyonTM for IGRT: Image Quality Benchmark, Clinical Performance, and Organ Doses

Purpose: The Varian Halcyon includes an ultrafast 6 MV flattening filter free (FFF) cone-beam computed tomography (MV-CBCT). Although a kV-CBCT add-on is available, in the basic configuration MV is used for image guided radiotherapy (IGRT). We characterized the MV-CBCT imager in terms of reproducibility, linearity, field of view (FOV) dependence, detectability of soft-tissue, and the effect of metal implants. The performance of the MV-CBCT in the clinic, including resulting dose to organs, is also discussed herein.

Methods: A Gammex phantom was scanned using a Halcyon MV-CBCT and a 120 kVp Siemens Definition Edge CT. Mean and standard deviation of Hounsfield Units (HUs) for different electron density relative to water (ρeW) inserts were extracted. Doses to clinical patients due to MV-CBCT are calculated within Eclipse during treatment planning.

Results: A stable and near-linear HU-to-ρeW curve was obtained using the MV-CBCT. As the scan length increased from 10 to 28cm, the linearity of curve improved while the mean HUs decreased by 30%. All soft tissue inserts in the Gammex phantom were distinguishable. A crescent artifact affected HU measurements by up to 40 HUs. Soft-tissue contrast was sufficient for clinical online image-guidance in the low dose (5 MU) mode. Mean doses per fraction to organs-at-risk (OARs) were as high as 6 cGy for head and neck, 5 cGy for breast, and 4 cGy for pelvis patients. Metal rods did not affect HU values or introduce noticeable artifacts.

Conclusions: Halcyon's MV-CBCT has sufficient soft tissue contrast for IGRT and lacks metal-induced artifacts. Even though the absolute HU values vary with phantom size and scanning length, the HU-to-ρeW conversions are linear and stable day-to-day. In clinical cases, highest tissue doses from MV-CBCT ranged from 2-7cGy per fraction for various treatment sites, which could be significant for some organs at risk. Dose to out-of-treatment-field organs can be limited by reducing the scan length definition during planning and using the low dose mode. The high quality imaging mode did not provide material advantages over the low dose mode. Adequate IGRT was successfully delivered to multiple tumor sites using MV-CBCT.

Evaluation of the Effect of a Tracheal Stent on Radiation Dose Distribution via Micro-CT Imaging

PURPOSE

To study the effect of a metal tracheal stent on radiation dose distribution.

METHOD

A metal tube bracket is placed in a self-made foam tube sleeve, and micro-computed tomography scanning is performed directly. The foam sleeve containing the metal bracket is placed in a nonuniform phantom for a routine computed tomography scan. The stents in conventional computed tomography images are replaced by the stents in micro-computed tomography images. Subsequently, 2 sets of computed tomography images are obtained and then imported to a radiotherapy treatment planning system. A single photon beam at 0° is designed in a field size of 10 cm × 10 cm, a photon beam of 6 MV, and a monitor unit of 200 MU. Monte Carlo algorithm is used to calculate the dose distribution and obtain the dose curve of the central axis of the field. The dose is verified with thermoluminescence dose tablets.

RESULTS

The micro-computed tomography images of the tracheal stent are clearer and less false-like than its conventional computed tomography images. The planned dose curves of the 2 groups are similar. In comparison with the images without any stents in place, the doses at the incident surface of the stent in the conventional computed tomography images and at the stent exit surface in the rear of the stent increase by 1.86% and 2.76%, respectively. In the micro-computed tomography images, the doses at the incident surface of the stent and at the exit surface behind the stent increase by 1.32% and 1.19%, respectively. Conventional computed tomography reveals a large deviation between the measured and calculated values.

CONCLUSION

Tracheal stent based on micro-computed tomography imaging has a less effect on radiotherapy calculation than that based on conventional computed tomography imaging.

VMAT Optimization and Dose Calculation in the Presence of Metallic Hip Prostheses

INTRODUCTION

This research quantifies and compares the effect of hip prostheses on dose distributions calculated using collapsed cone convolution superposition and Monte Carlo (with and without correcting for the density of the implant and surrounding tissues). The use of full volumetric modulated arc therapy arcs versus volumetric modulated arc therapy arcs avoiding the hip implants (skip arcs) was also studied.

MATERIALS AND METHODS

Six prostate patients with hip prostheses were included in this study. The hip prostheses and the streaking artifacts on the computed tomography images were contoured by a single physician, and full volumetric modulated arc therapy arcs were created in the Pinnacle3 TPS. Copies of each plan were made, and the doses were recalculated with the densities of the prostheses and surrounding tissues overridden. The plans were then exported to Monaco and recalculated using a Monte Carlo dose calculation algorithm, with and without densities of the prosthesis and surrounding tissues overridden.

RESULTS

With density overrides, Pinnacle3 had a 4.4% error for ion chamber measurements. Monaco was within 0.2% of ion chamber measurement when density overrides were used. On average, when density overrides were used in Pinnacle3 for patient dose calculations, the planning target volume D95 value dropped from 99.3% to 82.7%. Monaco also showed decreased planning target volume coverage when plans were recalculated with correct density information. Full arc plans (with density overrides) for the patient with a bilateral prosthesis provided significant bladder sparing and some rectal sparing compared to skip arc plans.

CONCLUSION

When planning for prostate patients with hip prostheses, correct density information for implants and surrounding tissues should be used to optimize the plan and ensure optimal accuracy. If available, a Monte Carlo algorithm should be used as a second check. Full arcs could be used to spare dose to organs at risk, while maintaining adequate planning target volume coverage, when using a Monte Carlo dose calculation algorithm.

Dose uncertainties associated with a set density override of unknown hip prosthetic composition

The dosimetric uncertainties associated with radiotherapy through hip prostheses while overriding the implant to a set density within the TPS has not yet been reported. In this study, the uncertainty in dose within a PTV resulting from this planning choice was investigated. A set of metallic hip prosthetics (stainless steel, titanium, and two different Co‐Cr‐Mo alloys) were CT scanned in a water bath. Within the TPS, the prosthetic pieces were overridden to densities between 3 and 10 g/cm³ and irradiated on a linear accelerator. Measured dose maps were compared to the TPS to determine which density was most appropriate to override each metal. This was shown to be in disagreement with the reported literature values of density which was attributed to the TPS dose calculation algorithm and total mass attenuation coefficient differences in water and metal. The dose difference was then calculated for a set density override of 6 g/cm³ in the TPS and used to estimate the dose uncertainty beyond the prosthesis. For beams passing through an implant, the dosimetric uncertainty in regions of the PTV may be as high as 10% if the implant composition remains unknown and a set density override is used. These results highlight limitations of such assumptions and the need for careful consideration by radiation oncologist, therapist, and physics staff.