Metal Artifact Reduction Research Articles

Effectiveness of single-energy metal artifact reduction algorithm in CT: application to contrast-enhanced CT with EVAR and coil embolization.

This study aimed to evaluate the efficacy of the single-energy metal artifact reduction (SEMAR) algorithm in reducing metal artifacts and enhancing image quality in contrast-enhanced computed tomography (CT) for patients undergoing endovascular aneurysm repair (EVAR) with coil embolization. Thirty-eight patients (mean age 81.0 ± 6 years; 31 men, 7 women) who underwent contrast-enhanced CT following EVAR and internal iliac artery coil embolization between September 2022 and May 2023 were retrospectively analyzed. The Artifact Index (AI) quantified metallic artifacts from internal iliac artery aneurysm coils in CT images, calculated from the standard deviation of the artifact-containing region relative to a reference region. CT values of the external iliac artery at the same slice were also evaluated and compared. Two radiologists independently performed qualitative assessments of SEMAR and non-SEMAR images. SEMAR significantly reduced metal artifacts, decreasing the AI from 171.9 ± 74.5 HU to 35.8 ± 16.9 HU (p < 0.001). The mean CT values of the external iliac artery were similar for SEMAR (259.4 ± 63.7 HU) and non-SEMAR (257.1 ± 63.6 HU, indicating no significant difference. Qualitative assessment scores improved significantly with SEMAR (from 1.0 ± 0.0 to 2.5 ± 0.5; p < 0.001), enhancing visualization of internal iliac artery aneurysms. Interobserver agreement was high (κ = 0.83). The SEMAR algorithm effectively reduces metal artifacts in contrast-enhanced CT, significantly enhancing image quality without altering adjacent artery CT values. These improvements enhance the image quality of post-operative assessments in patients undergoing EVAR with coil embolization.

A comprehensive dual energy method for CBCT metal artifact reduction

Objective.A major limitation in cone beam CT (CBCT) application is the presence of metal artifacts when scanning metal-embedded objects or high attenuation materials. This study aims to develop a dual-energy based method for effective metal artifact reduction.Approach.The proposed method comprised three steps. Initially, the virtual monoenergetic (VM) projections were generated by combining high- and low-energy projections to mitigate metal artifacts caused by the beam hardening effect. Subsequently, the normalized metal artifact reduction (NMAR) projections were created using the VM projections through the NMAR method. Then, the NMAR CBCT was produced by reintegrating metal into the CBCT reconstructed from NMAR projections. Finally, the iterative reconstruction was employed to obtain the final CBCT, utilizing VM projections and the NMAR CBCT as the initial input. Validation of the proposed method was achieved through Monte Carlo (MC) simulations on digital dental and abdominal phantoms, and CBCT scanning on CIRS Model 062M head and body phantoms. The structural similarity index measurement (SSIM) and the root mean square error (RMSE) calculated within a metal-containing ROI were employed for image quality evaluation.Main Results.Both the MC simulation and phantom scanning demonstrated that the proposed method was superior to the frequency split metal artifact reduction (FSMAR) method in mitigating artifacts and preserving anatomic details around metal. Averaged over four phantoms, the SSIM was enhanced from 99.48% with FSMAR to 99.86% with our proposed method, and the RMSE was reduced from 93.62 HU to 70.75 HU. Furthermore, the proposed method could be implemented with less than two minutes after GPU acceleration.Significance.The proposed dual-energy based metal artifact correction method effectively corrects metal artifacts and preserves tissue details surrounding the metal region by leveraging the strengths of VM, projection interpolation and iterative reconstruction techniques. It has strong potential of clinical implementation due to the superior performance in image quality and process efficiency.

The value of dual-energy computed tomography angiography-based virtual monoenergetic imaging for evaluations after cerebral aneurysm clipping.

This study aimed to research the optimal energy range of dual-energy computed tomography angiography (DECTA)-based virtual monoenergetic imaging (VMI) for evaluations after cerebral aneurysm clipping. Sixty patients who underwent DECTA after cerebral aneurysm clipping were analyzed retrospectively. Conventional computed tomography angiography (CTA) was compared with VMIs at 60, 70, 80, 90, and 100 keV. The mean attenuation and standard deviation values within the regions of interest placed in the brain parenchyma and arteries with the worst artifact were measured, respectively. The ΔCT and artifact index (AI) values were calculated to assess the artifact severity. The contrast-to-noise ratio (CNR) was calculated to assess vascular contrast. Two radiologists assessed brain parenchyma and cerebrovascular scores qualitatively using a five-point Likert scale. Quantitative analysis showed that the artifacts of VMIs were significantly reduced compared with conventional CTA (P ≤ 0.014), except for the ΔCT and AI of 60 keV and the ΔCT of 70 keV. However, there was no significant difference in the vascular contrast on VMIs compared with conventional CTA, except for the CNR of 60 keV (P = 0.008). In qualitative analysis, the proportions of brain parenchyma scores and cerebrovascular scores ≥4 on the VMIs of 70 and 80 keV were higher than those of conventional CTA and other VMIs. For the patients who underwent DECTA after cerebral aneurysm clipping, the 70-80 keV VMIs are expected to be the optimal energy range for balancing clip artifacts and visibility of adjacent vessels. Studying the optimal energy range of DECTA-based VMI for post-operative assessment of aneurysm clipping can reduce metal artifacts in images and increase vascular contrast. This facilitates the follow-up of patients after aneurysm clipping, offers timely and accurate detection of postoperative complications, provides assistance to clinicians in diagnosis and treatment, and improves patient prognosis.

Fabrication of an In-house Phantom for Evaluation of Metal Artifact Reduction in Computed Tomography

Purpose: This study aims to fabricate an in-house phantom for evaluating effectiveness of a metal artifact reduction (MAR) algorithm in computed tomography (CT) images. Methods: The in-house phantom was made from polyester-resin (PESR) with methyl ethyl ketone peroxide (MEKP) as a catalyst. The dimension of the phantom was 160 mm in diameter and 50 mm in length with seven insert holes ranging from 10 to 20 mm. The titanium representing a metal implant and calcium carbonate representing the bone were inserted into the holes of the phantom. The phantom was scanned using a GE Revolution Apex CT scanner, slice thickness of 1.25 mm, and tube current of 200 and 370 mA. Images were reconstructed using filtered back projection (FBP) and MAR algorithm for reducing metal artifact. Artifact evaluation was characterized by changing in CT number and image noise. Results: Titanium material increases metal artifact in the in-house phantom. Metal artifact from titanium decreases CT number around 5% and increases noise level around 60%. MAR implementation can reduce metal artifacts, which is indicated by an increase in the CT number around 0.7% and a decrease in noise level around 30%. Conclusion: The in-house phantom for evaluating MAR algorithm was successfully developed. The presence of titanium increases metal artifacts, which is characterized by a decrease in the CT number and an increase in noise level in the area around the titanium. It is found that the MAR succeeded in reducing metal artifacts.

Evaluation of Pedicle Screw Position on Computerized Tomography Using Three-Dimensional Reconstruction Software.

Background and Objectives: Recent advances in intraoperative navigation systems have improved the accuracy of pedicle screw placement in spine surgery. However, many hospitals have limited access to these advanced technologies due to resource constraints. In such settings, postoperative computed tomography (CT) evaluation remains crucial for assessing screw placement and related potential complications. Metal artifacts in CT scans often compromise the diagnostic accuracy. This study aimed to develop and validate three-dimensional (3-D) reconstruction software to enhance screw localization accuracy and facilitate its practical clinical application. Materials and Methods: This study included two phases: 3-D software development utilizing specific threshold values of Hounsfield units for titanium screws followed by internal validation. For validation, fifty pedicle screws were inserted into porcine lumbar vertebrae with random violation (superior, inferior, medial, or lateral). Three fellowship-trained surgeons evaluated screw positions using both conventional CT bone window settings and the developed software. Additional clinical validation involving 386 pedicle screws from cervical to lumbar spine was performed by two surgeons. Results: The software demonstrated significantly higher specificity (83% vs. 63%) and positive predictive value (96% vs. 91%) compared to conventional CT bone window settings, while maintaining 100% sensitivity and negative predictive value. Interobserver reliability was excellent for both methods (0.961 for bone window vs. 0.990 for software). In clinical validation, the software showed superior intraobserver (0.83 vs. 0.74) and interobserver reliability (0.855 vs. 0.513) compared to picture archiving and communication system (PACS) workstation evaluation. Conclusions: The developed software provides improved accuracy and reliability in pedicle screw position evaluation through distinct screw outline visualization and metal artifact reduction. Its equipment-independent nature and cost-effectiveness make it particularly valuable for clinical implementation.

Analysis of software methods for metal computed tomography artifact reduction: experimental research

X‑ray density of biological tissues is an important diagnostic parameter. Metal structures in the CT scanning area distort it, creating artifacts. Thus, hip joint endoprostheses (HJE) often complicate visualization of nearby soft tissue structures of the pelvic organs, which can interfere with the qualitative and quantitative analysis of changes when assessing the prevalence of the oncological process in this area. It is possible to correct these distortions using software methods, bringing the Hounsfield units (HU) values closer to the true ones. Purpose of the study. To conduct a visual (qualitative) and quantitative assessment of metal artifacts in CT images using software methods for their reduction. Materials and methods. A phantom was used for quantitative assessment: a plexiglass cylinder with a HJE in the center and test tubes with potassium hydrophosphate solution around it. The study was performed on a CT scanner with (FBP, iDose, iMR) reconstruction algorithms and O‑MAR technology for artifact suppression. The mean values and standard deviation of HU, the degree of susceptibility to artifacts were measured. Image quality was visually assessed using a five‑point Likert scale. Results. The use of the O‑MAR algorithm does not distort HU in the absence of an HJE and smoothens the HU distribution in its presence. Deviation from the specified values at the level of the HJE neck decreased from 32–36 HU without O‑MAR to ‑1.5 – ‑4.7 HU with O‑MAR. The minimum noise was observed for iMR with O‑MAR at the level of the neck (31.6 HU) and stem (6.2 HU) of the HJE, the maximum – for FBP without O‑MAR (77.0 and 33.2 HU, respectively). The quality assessment was best for iMR with O‑MAR (3 points), the worst for FBP without O‑MAR (1.4 points). It was also shown that O‑MAR forms additional artifacts near the HJE. Conclusion. Metal artifact reduction algorithms do not distort the X‑ray density without an artifact source. In the presence of metal structures, the algorithms reduce HU deviations and improve visualization, but they can form additional artifacts in the form of areas of increased and decreased density, so it is necessary to combine them with reconstruction without artifact reduction. To reduce the noise level, as well as to increase the contrast sensitivity, the use of model iterative reconstruction technology is optimal.

Evaluation of MRI Safety of Ru-106 Eye Applicators

Introduction: Ruthenium-106 brachytherapy is a primary treatment for uveal melanoma (UM), the most common intra-ocular malignancy in adults. This study evaluated the safety of Ru-106 applicators at 3 Tesla (T) MRI and their impact on image quality. Methods: Magnetic attraction and eddy currents were tested on a 20-mm-diameter Ru-106 applicator using a nylon string and a porcine eye. Safety criteria were defined by ocular oncologists, comparing magnetic field interactions to the forces exerted on the eye during surgery. Five UM patients were scanned at 3T MRI with the applicator in situ using both conventional anatomical sequences and scans optimised to reduce metal artefacts. Results: Minimal magnetic interactions were observed. Eddy currents caused slight lagging during fast movements and temporary detachment of the applicator of the porcine eye in conditions that were considered unrealistic for clinical scans. Significant susceptibility artefacts compromised image quality of the affected eye. Conclusion: Patients with Ru-106 applicators can be safely used in 3T MRI with some simple precautions. MR image quality of the eye was poor due to major susceptibility artefacts; however, imaging of extra-ocular anatomy is feasible.

Development and Evaluation of a Deep Learning Model to Reduce Exomass-Related Metal Artefacts in Cone-Beam Computed Tomography of the Jaws.

To develop and evaluate a deep learning (DL) model to reduce metal artefacts originating from the exomass in cone-beam computed tomography (CBCT) of the jaws. Five porcine mandibles, each featuring six tubes filled with a radiopaque solution, were scanned using four CBCT units before and after the incremental insertion of up to three titanium, titanium-zirconium, and zirconia dental implants in the exomass of a small field of view. A conditional denoising diffusion probabilistic model, using DL techniques, was employed to correct images from exomass-related metal artefacts across the CBCT units and implant scenarios. Three examiners independently scored the image quality of all datasets, including those without an implant (ground truth), with implants in the exomass (original), and DL-generated ones. Quantitative analysis compared contrast-to-noise ratio (CNR) to validate artefact reduction using repeated measures analysis of variance in a factorial design followed by Tukey test (α = 0.05). The visualisation of the hard tissues and overall image quality was reduced in the original and increased in the DL-generated images. The score variation observed in the original images was not observed in the DL-generated images, which generally scored higher than the original images. DL-generated images revealed significantly greater CNR than both the ground truth and their corresponding original images, regardless of the material and quantity of dental implants and the CBCT unit (p < 0.05). Original images revealed significantly lower CNR than the ground truth (p < 0.05). The developed DL model demonstrated promising performance in correcting exomass-related metal artefacts in CBCT of the jaws.

3D-Printed Metacarpal Prosthesis in the Treatment of Primary Osteosarcoma of the First Metacarpal: A Novel Surgical Technique.

Osteosarcoma at the first metacarpal is extremely rare. Reconstructing the metacarpal after tumor resection is essential, as the thumb accounts for approximately 40%-50% of hand function. Although autografts, arthroplasty, and transposition have been reported as reconstruction options, their use is limited by complications such as secondary injury, nonunion, and displacement. In this study, we present a case of a patient with first metacarpal osteosarcoma who underwent tumor resection followed by reconstruction with a 3D-printed metacarpal prosthesis. We tend to introduce a novel strategy to reconstruct the first metacarpal and restore the hand function. A 30-year-old male with 5-month history of first metacarpal swelling in the left hand was admitted to our center. Imaging examinations and incision biopsy confirmed a diagnosis of intramedullary well-differentiated osteosarcoma. A 3D-printed metacarpal prosthesis was then designed to achieve carpometacarpal (CMC) joint fusion and thumb metacarpophalangeal (MCP) joint reconstruction. Postoperative evaluations included X-ray and tomosynthesis-shimadzu metal artifact reduction technology (T-SMART) imaging to assess bone-prosthesis integration. Hand function was measured using the Musculoskeletal Tumor Society (MSTS) score and the Disabilities of the Arm, Shoulder, and Hand (DASH) score. The tumor was completely resected, and a 3D-printed metacarpal prosthesis was performed to reconstruct the tumor defect. Postoperative imaging showed that the interface between bone and prosthesis was integrated and that there was no loose, displacement, or fracture of the implant. At the last follow-up, the patient had an MSTS score of 25/30 and a DASH score of 8/100. The range of motion on thumb MCP joint was 30° of flexion and 0° of extension. The Kapandji thumb opposition score was 4 points. The grip strength was 9 kg (compared to 30 kg on the contralateral side) and the key-pinch strength was 3 kg (compared to 8 kg on the contralateral side). 3D-printed metacarpal prosthesis could be an effective reconstruction option for patients with low-grade malignant tumors. Themulti-planar fixation achieved through 3D surgical planning helps maintain thumb function and restore overall hand function.

Reducing Metal Artifacts in Clinical Photon Counting Detector Computed Tomography-A Phantom Study of an Exemplary Total Hip Arthroplasty.

To examine how different photon-counting detector (PCD) CT scanning and reconstruction methods affect the volume of metal artifacts and image quality for a hip prosthesis phantom. A titanium and cobalt-chromium-molybdenum-alloy total hip prosthesis phantom was scanned using a clinical PCD-CT with a constant tube potential (140kV) and Computed-Tomography-Dose- Index (7mGy). Different scan settings were used: with/without tin-filter (Sn), with/without ultra-high resolution (UHR), both individually and combined, resulting in four modes: Quantumplus (Standard), UHR Quantumplus (HighRes), QuantumSn (Standard-Tin) and UHR QuantumSn (HighRes-Tin). Reconstructions included virtual monoenergetic images (VMI) spanning 40-190keV and polychromatic images, with/without iterative metal artifact reduction (MAR). Artifact volumes rendered in a 3D-printing software were quantified in milliliters (ml), and image quality was evaluated using a Likert score. Polychromatic reconstruction: Tin-filter reduced artifact volumes (298 (Standard-Tin) vs. 347ml (Standard) and 310 (HighRes-Tin) vs. 360ml (HighRes)). The smallest artifact volume was measured in HighRes MAR (150ml). VMI reconstruction: The smallest artifact volume was measured in Standard 130keV (150ml) and HighRes 130keV (164ml) and in Standard-Tin 120keV (169ml) and HighRes-Tin 120keV (172ml). MAR further reduced the artifact volumes to 130ml (Standard 150keV MAR) and 140ml (HighRes 160keV MAR). Image quality was rated best for Standard 65keV MAR, polychromatic HighRes MAR, Standard 100keV MAR, polychromatic Standard-tin MAR, HighRes-tin 100keV and polychromatic HighRes-tin. Combining tin-filter, UHR and MAR in VMI or polychromatic images achieve the strongest artifact reduction.

Influence of Metal Artifact Reduction Tool of Two Cone Beam CT on the Detection of Bone Graft Loss Around Titanium and Zirconium Implants-An ExVivo Diagnostic Accuracy Study.

The objective of this study is to investigate the influence of metal artifact reduction (MAR) on two cone beam computed tomography (CBCT) units in the evaluation of bone graft loss adjacent to titanium (Ti) and zirconium (Zr) implants. Twelve Ti and twelve Zr implants were placed in the posterior region of dry human mandibles. Bone graft was applied to the level of the cover screw. Bone graft loss was simulated in half of the sample (6 Ti and 6 Zr) by removing the graft material up to the third implant thread on the buccal surface. CBCT images were acquired on two units, varying the application of MAR (OP300-off and on; Eagle 3D-standard, intermediate, and extreme). The images were assessed by five evaluators that scored the presence of graft loss according to a 5-point scale. The diagnostic values were calculated and compared by non-parametric tests with a significance level of 5%. Higher diagnostic values were achieved with MAR activated in the OP300 unit, for Ti and Zr (p < 0.05). On the Eagle 3D unit, MAR in extreme mode resulted in lower diagnostic values for both types of implants (p < 0.05). The diagnostic values of Ti implants were higher than Zr implants (p < 0.05). The application of MAR influences the diagnosis of bone graft loss adjacent to Ti and Zr dental implants. However, the extreme mode of MAR in the Eagle 3D unit can impair the diagnostic task in both types of implants and should be avoided.

Comprehensive Image Quality Evaluation and Motion Phantom Studies of an Ultra-Fast (6-Second) Cone-Beam Computed Tomography Imaging System on a Ring Gantry Linear Accelerator

PurposeTo evaluate the image quality of an ultra-fast CBCT system - Varian HyperSight. MethodsIn this evaluation, five-studies were performed to assess the image quality of HyperSight CBCT. First, a HyperSight CBCT image quality evaluation was performed and compared with Siemens simulation-CT and Varian TrueBeam CBCT. Second, a visual comparison of image quality among simulation-CTs, HyperSight CBCT and TrueBeam CBCT was performed for a head-and-neck patient, and patients with metal dental fillings and prosthesis. Third, the HU vs electron density curve of HyperSight CBCT was compared with GE and Siemens simulation-CTs. Fourth, Siemens simulation-CT and HyperSight CBCT scans were acquired on the Catphan setting-up at different locations inside the bore (±10cm in all three principal directions from the center), and the HU variations for different materials were evaluated. Fifth, a 4D lung tumor phantom study was performed to assess moving tumor alignment during image registration. ResultsSignificant improvement of image contrast, HU constancy, and noise level on HyperSight CBCT was observed compared to TrueBeam CBCT. Significant image quality improvement was observed on HyperSight CBCT for patients with dental fillings and prosthesis compared to simulation-CT without metal artifact reduction. The linear fit trend-line of HU vs electron density curves for GE simulation-CT, Siemens simulation-CT and HyperSight CBCT showed 0.6% difference for HU value below 2000. The maximum HU difference for HyperSight CBCT when Catphan positioned within ±10cm in all three principal directions was ≤98 on bone 50%, and ≤29 other than bone, and was ≤31 on bone 50%, and ≤17 other than bone for Siemens simulation-CT. Both tumor shape and tumor alignment discrepancies on CBCT scans were observed in 4D phantom study. ConclusionsThis evaluation shows significant image improvement of HyperSight CBCT over conventional CBCT on image contrast, HU constancy, and noise level with scatter correction and metal artifact reduction reconstruction methods. HyperSight CBCT has similar image quality to simulation-CTs, and shows the potential application for treatment planning. The rapid acquisition of HyperSight CBCT showed both tumor shape and tumor alignment discrepancies of moving target. Careful considerations of patient respiratory motion monitoring and target matching are highly recommended.

Dual-encoder architecture for metal artifact reduction for kV-cone-beam CT images in head and neck cancer radiotherapy

During a radiotherapy (RT) course, geometrical variations of target volumes, organs at risk, weight changes (loss/gain), tumor regression and/or progression can significantly affect the treatment outcome. Adaptive RT has become the effective methods along with technical advancements in imaging modalities including cone-beam computed tomography (CBCT). Planning CT (pCT) can be modified via deformable image registration (DIR), which is applied to the pair of pCT and CBCT. However, the artifact existed in both pCT and CBCT is a vulnerable factor in DIR. The dose calculation on CBCT is also suggested. Missing information due to the artifacts hinders the accurate dose calculation on CBCT. In this study, we aim to develop a deep learning-based metal artifact reduction (MAR) model to reduce the metal artifacts in CBCT for head and neck cancer RT. To train the proposed MAR model, we synthesized the kV-CBCT images including metallic implants, with and without metal artifacts (simulated image data pairs) through sinogram image handling process. We propose the deep learning architecture which focuses on both artifact removal and reconstruction of anatomic structure using a dual-encoder architecture. We designed four single-encoder models and three dual-encoder models based on UNet (for an artifact removal) and FusionNet (for a tissue restoration). Each single-encoder model contains either UNet or FusionNet, while the dual-encoder models have both UNet and FusionNet architectures. In the dual-encoder models, we implemented different feature fusion methods, including simple addition, spatial attention, and spatial/channel wise attention. Among the models, a dual-encoder model with spatial/channel wise attention showed the highest scores in terms of peak signal-to-noise ratio, mean squared error, structural similarity index, and Pearson correlation coefficient. CBCT images from 34 head and neck cancer patients were used to test the developed models. The dual-encoder model with spatial/channel wise attention showed the best results in terms of artifact index. By using the proposed model to CBCT, one can achieve more accurate synthetic pCT for head and neck patients as well as better tissue recognition and structure delineation for CBCT image itself.

Artifactual Subclavian Artery Thrombosis on CTA With Iterative Metal Artifact Reduction.

Artifactual Subclavian Artery Thrombosis on CTA With Iterative Metal Artifact Reduction.

Combining different metal artifact reduction levels with sharpening filters and slice thickness for the visualization of mandibular canals perforated by implants.

To investigate the influence of combining levels of metal artifact reduction (MAR) tool with different filters and slice-thickness in the detection of mandibular canals perforated by implants on CBCT scans and to objectively assess the impact of the aforementioned combinations. Implants were placed above (8 implants) and inside (10 implants) mandibular canals of dried-mandibles. CBCT scans were obtained with the Eagle 3D unit (85 kVp, 8mA, 5 × 5cm FOV, 130μm voxel size, and off/medium/high MAR levels). Examiners evaluated the scans under each MAR level and across different conditions: no filter, Sharpen 1×, Sharpen 2×; 0mm, 1mm, and 2mm slice-thickness. The gray values on axial reconstructions were assessed. Area under the receiver operating characteristic curve (AUC), sensitivity, specificity, mean and standard deviation (SD) for gray values were calculated and compared by multi-way Analysis of Variance. Overall, the AUC and sensitivity decreased with high-level MAR (p < 0.0001), regardless other variables tested. Enabling MAR tool decreased mean gray values (p < 0.01) and increasing MAR levels reduced the SD values on scans with Sharpen 2× (p < 0.012). High-level MAR impairs the visualization of mandibular canals perforated by implants. Moreover, enabling MAR tool decreases the mean gray values. MAR tool, filters, and slice thickness influence the image quality of CBCT scans. Therefore, it is important to evaluate the impact of these parameters on the diagnosis of mandibular canals perforated by implants.

Investigation of the effectiveness of eight different metal artifact reduction algorithms in reducing extracorporeal metal artifacts: a phantom study using the Gumbel method

Investigation of the effectiveness of eight different metal artifact reduction algorithms in reducing extracorporeal metal artifacts: a phantom study using the Gumbel method

Dual Energy Metal Artifact Reduction for Iodine-125 Seed Identification in Postimplant CT after Prostate Brachytherapy.

To assess the metal artifact reductions of dual-energy computed tomography (DECT) high-energy virtual monochromatic images (VMI) combined with the single energy metal artifact reduction (SEMER) (CANON MEDICAL SYSTEMS, Otawara, Japan) processing techniques for iodine (I)-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy. Dual-energy acquisition with fast tube voltage switching was performed on a prostate phantom with simulated seeds and six clinical cases treated with I-125 prostate brachytherapy. The images were retrospectively reconstructed at VMI energy levels of 65-200 keV and with and without SEMAR (SEMAR and non-SEMAR images). To estimate seed swelling, the caliber of iodine-125 seed was calculated as the full width at half maximum. The metal artifacts were evaluated using the artifact index (AI). The dose distributions were calculated and were compared among the high-energy VMI (SEMAR and non-SEMAR images) and low-energy VMI (SEMAR images). The blooming artifacts decreased at higher energy levels. In addition, the SEMAR process markedly reduced AI, which helped reduce overestimation of high dose ranges in the treatment planning dose map. The locations and number of iodine-125 seed were clearly identified in the dose distribution map of the treatment planning using 200keV VMI with SEMAR. The high-energy VMI of the dual energy CT in combination with SEMAR is appropriate for the postimplant planning process of I-125 prostate brachytherapy.

Eliminating metal artifacts in dental computed tomography using an elaborate sinogram normalization interpolation method with CNR-based metal segmentation

Metal artifact reduction (MAR) in dental cone-beam computed tomography (CBCT) is critical for improving its clinical usefulness and remains a challenging problem. This study presents an elaborate sinogram normalization interpolation (SNI) method with contrast-to-noise ratio (CNR)-based metal segmentation to eliminate metal artifacts in dental CBCT. The proposed MAR method involves three main steps: (1) CNR-based segmentation of a metal trace in the sinogram domain; (2) generation of a residual artifact-reduced prior sinogram; and (3) sinogram completion using the prior sinogram, followed by filtered-backprojection (FBP)-based CBCT reconstruction and metal insertion processes. To verify the efficacy of the proposed method, simulations and experiments were performed using numerical and physical dental phantoms with several metal inserts. The quality of the resulting CBCT images was quantitatively evaluated using the structural similarity (SSIM) metric and compared to those obtained with other interpolation-based MAR methods. A tabletop setup for the micro-CT system was used in the experiment, which comprised an X-ray tube operated under tube conditions of 70 kV p and 5 mA and a flat-panel detector with a pixel size of 198 μm. Our results indicate that the CNR-based metal segmentation method precisely identified traces of metallic objects on the sinogram, and thereby, the proposed SNI-based MAR method considerably reduced metal artifacts in dental CBCT images without introducing any contrast anomalies. The SSIM values of the CBCT images obtained with the proposed MAR method were 0.99 and 0.95 for the simulation and experiment, respectively, which are approximately 11% and 9% greater than those with a simple threshold-based linear interpolation method, respectively, improving the image quality. The proposed MAR method can be applied to reduce metal artifacts in real-world dental CBCT systems.

DiffMAR: A Generalized Diffusion Model for Metal Artifact Reduction in CT Images.

X-ray imaging frequently introduces varying degrees of metal artifacts to computed tomography (CT) images when metal implants are present. For the metal artifact reduction (MAR) task, existing end-to-end methods often exhibit limited generalization capabilities. While methods based on multiple iterations often suffer from accumulative error, resulting in lower-quality restoration outcomes. In this work, we innovatively present a generalized diffusion model for Metal Artifact Reduction (DiffMAR). The proposed method utilizes a linear degradation process to simulate the physical phenomenon of metal artifact formation in CT images and directly learn an iterative restoration process from paired CT images in the reverse process. During the reverse process of DiffMAR, a Time-Latent Adjustment (TLA) module is designed to adjust time embedding at the latent level, thereby minimizing the accumulative error during iterative restoration. We also designed a structure information extraction (SIE) module to utilize linear interpolation data in the image domain, guiding the generation of anatomical structures during the iterative restoring. This leads to more accurate and robust shadow-free image generation. Comprehensive analysis, including both synthesized data and clinical evidence, confirms that our proposed method surpasses the current state-of-the-art (SOTA) MAR methods in terms of both image generation quality and generalization.

Universal non-circular cone beam CT orbits for metal artifact reduction imaging during image-guided procedures

Innovation in image-guided procedures has been driven by advances in robotic Cone Beam Computed Tomography (CBCT) systems. A fundamental challenge for CBCT imaging is metal artifacts arising from surgical tools and implanted hardware. Here, we outline how two universal non-circular imaging orbits, optimized for metal artifact reduction, can be implemented in real-time on clinical robotic CBCT systems. Demonstrating potential clinical utility, the universal orbits were implemented during a pedicle screw cervical spine fixation and hip arthroplasty performed on a porcine and ovine cadaver respectively. In both procedures, the universal non-circular orbits noticeably reduced the metal artifacts surrounding the implanted orthopedic hardware, revealing anatomy and soft tissue obscured in current conventional CBCT imaging. This work represents a key step in clinically translating universal orbits, unlocking high quality in-room procedural verification to increase broader use of robotic CBCT systems and reduce the occurrence of secondary corrective surgeries.