Iterative algorithms for metal artifact reduction in children with orthopedic prostheses: preliminary results

Severe metallosis following catastrophic failure of total shoulder arthroplasty - a case report

Metallosis is an unusual but consequential complication arising from orthopedic hardware implantation, characterized by the deposition of metallic particles in the periprosthetic soft tissues. The incidence of metallosis associated with shoulder arthroplasties is exceptionally rare since the shoulder is not a weight-bearing joint, making it less susceptible to mechanical wear and, consequently, to conditions like particle disease and metallosis. Nevertheless, anomalous metal-on-metal interactions can develop in total shoulder arthroplasties if the polyethylene component fails due to wear, fracture, or dissociation. If left unaddressed, metallosis can incite an adverse immune-mediated local tissue response, culminating in joint destruction and adjacent soft tissues and muscle necrosis. In this case report, the diagnosis of metallosis was made in a patient with an anatomic total shoulder arthroplasty using a state-of-the-art photon counting detector CT supplemented by post-processing metal artifact reduction algorithms. This advanced imaging approach was effective in discerning the source of implant failure and in identifying manifestations of severe metallosis including osteolysis and pseudotumor formation. Advanced imaging methods can accurately characterize the severity and extent of metallosis, thereby helping guide surgical planning to mitigate serious complications associated with this condition.

Metal implants on abdominal CT: does split-filter dual-energy CT provide additional value over iterative metal artifact reduction?

PURPOSE

To assess image quality and metal artifact reduction in split-filter dual-energy CT (sfDECT) of the abdomen with hip or spinal implants using virtual monoenergetic images (VMI) and iterative metal artifact reduction algorithm (iMAR).

METHODS

102 portal-venous abdominal sfDECTs of patients with hip (n = 71) or spinal implants (n = 31) were included in this study. Images were reconstructed as 120kVp-equivalent images (Mixed) and VMI (40-190 keV), with and without iMAR. Quantitative artifact and image noise was measured using 12 different ROIs. Subjective image quality was rated by two readers using a five-point Likert-scale in six categories, including overall image quality and vascular contrast.

RESULTS

Lowest quantitative artifact in both hip and spinal implants was measured in VMI_190keV-iMAR. However, it was not significantly lower than in Mixed_iMAR (for all ROIs, p = 1.00), which were rated best for overall image quality (hip: 1.00 [IQR: 1.00-2.00], spine: 3.00 [IQR:2.00-3.00]). VMI_50keV-iMAR was rated best for vascular contrast (hip: 1.00 [IQR: 1.00-2.00], spine: 2.00 [IQR: 1.00-2.00]), which was significantly better than Mixed (both, p < 0.001). VMI_50keV-iMAR provided superior overall image quality compared to Mixed for hip (1.00 vs 2.00, p < 0.001) and similar diagnostic image quality for spinal implants (2.00 vs 2.00, p = 0.51).

CONCLUSION

For abdominal sfDECT with hip or spinal implants Mixed_iMAR images should be used. High keV VMI do not further improve image quality. IMAR allows the use of low keV images (VMI_50keV) to improve vascular contrast, compared to Mixed images.

CT in Patients With External Fixation for Complex Lower Extremity Fractures: Impact of Iterative Metal Artifact Reduction Techniques on Metal Artifact Burden and Subjective Quality

Background: Lower extremity external fixators have complex geometries that induce pronounced metal artifact on CT. Iterative metal artifact reduction (iMAR) algorithms help reduce such artifact, though no dedicated iMAR preset exists for external fixators. Objective: To compare iMAR presets for CT examinations in terms of quantitative metal artifact burden and subjective image quality in patients with external fixators for complex lower extremity fractures. Methods: This retrospective study included 72 CT examinations in 56 patients (20 female, 36 male; mean age 56±18 years) with lower extremity external fixators (regular, hybrid, or monotube tube). Examinations were reconstructed without iMAR (noMAR) and with three iMAR presets (iMARspine, iMARhip, iMARextremity). A radiology resident quantified metal artifact burden using software. Two radiology residents indepenently assessed overall image quality and diagnostic confidence using 4-point scales (4=highest quality). Techniques were compared using Bonferroni-corrected post-hoc tests. Interreader agreement was assessed by intraclass correlation coefficients (ICCs). Post-hoc multinomial regression model was used for predicting overall image quality. Results: Mean quantitative metal artifact burden burden was 100816±45558 (noMAR), 88889±44028 (iMARspine), 82295±41983 (iMARhip), and 81956±41890 (iMARextremity). Overall image quality demonstrated ICC ≥0.94. Using pooled reader data, median overall image quality was, for regular fixator, 2 (noMAR), 3 (iMARspine and iMARhip), and 4 (iMARextremity); for hybrid, 1 (noMAR), 2 (iMARspine), and 3 (iMARhip and iMARextremity); and for monotube, 2 (noMAR), 3 (iMARspine and iMARhip), and 4 (iMARextremity). Metal artifact burden and overall image quality were higher (p<.05) for iMARhip and iMARextremity versus noMAR and iMARspine for all fixators (aside from image quality of iMARhip and iMARextremity vs iMARspine for regular fixators) but not different (all p>.05) between iMARhip and iMARextremity. Median diagnostic confidence was 4 for all fixators and reconstructions. Independent predictors of overall quality relative to noMAR were iMARspine [odds ratio (OR)=1.92-5.51], iMARhip (OR=5.56-31.10), and iMARextremity (OR=7.07-38.21). All iMAR presets introduced new reconstruction artifacts for all examinations for both readers. Conclusion: For the three fixator types, iMARhip and iMARextremity achieved greatest metal artifact burden reduction and highest subjective image quality, though introduced new reconstruction artifacts. Clinical Impact: CT using the two identified iMAR presets may facilitate perioperative management of external fixators.

Diagnostic Value of Model-Based Iterative Reconstruction Combined with a Metal Artifact Reduction Algorithm during CT of the Oral Cavity

BACKGROUND AND PURPOSE

Metal artifacts reduce the quality of CT images and increase the difficulty of interpretation. This study compared the ability of model-based iterative reconstruction and hybrid iterative reconstruction to improve CT image quality in patients with metallic dental artifacts when both techniques were combined with a metal artifact reduction algorithm.

MATERIALS AND METHODS

This retrospective clinical study included 40 patients (men, 31; women, 9; mean age, 62.9 ± 12.3 years) with oral and oropharyngeal cancer who had metallic dental fillings or implants and underwent contrast-enhanced ultra-high-resolution CT of the neck. Axial CT images were reconstructed using hybrid iterative reconstruction and model-based iterative reconstruction, and the metal artifact reduction algorithm was applied to all images. Finally, hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithm data were obtained. In the quantitative analysis, SDs were measured in ROIs over the apex of the tongue (metal artifacts) and nuchal muscle (no metal artifacts) and were used to calculate the metal artifact indexes. In a qualitative analysis, 3 radiologists blinded to the patients' conditions assessed the image-quality scores of metal artifact reduction and structural depictions.

RESULTS

Hybrid iterative reconstruction + metal artifact reduction algorithms and model-based iterative reconstruction + metal artifact reduction algorithms yielded significantly different metal artifact indexes of 82.2 and 73.6, respectively (95% CI, 2.6-14.7; P < .01). The latter algorithms resulted in significant reduction in metal artifacts and significantly improved structural depictions(P < .01).

CONCLUSIONS

Model-based iterative reconstruction + metal artifact reduction algorithms significantly reduced the artifacts and improved the image quality of structural depictions on neck CT images.

The effect of the reconstruction algorithm for the pulmonary nodule detection under the metal artifact caused by a pacemaker

The aim was to compare the effects of metal artifacts from a pacemaker on pulmonary nodule detection among computed tomography (CT) images reconstructed using filtered back projection (FBP), single-energy metal artifact reduction (SEMAR), and forward-projected model-based iterative reconstruction solution (FIRST).Nine simulated nodules were placed inside a chest phantom with a pacemaker. CT images reconstructed using FBP, SEMAR, and FIRST were acquired at low and standard dose, and were evaluated by 2 independent radiologists.FIRST demonstrated the most significantly improved metal artifact and nodule detection on low dose CT (P < .0032), except at 10 mA and 5-mm thickness. At standard-dose CT, SEMAR showed the most significant metal artifact reduction (P < .00001). In terms of nodule detection, no significant differences were observed between FIRST and SEMAR (P = .161).With a pacemaker present, FIRST showed the best nodule detection ability at low-dose CT and SEMAR is comparable to FIRST at standard dose CT.

Application of Iterative Metal Artifact Reduction Algorithm to CT Urography for Patients With Hip Prostheses

OBJECTIVE. The purpose of this study is to retrospectively assess the impact of iterative metal artifact reduction (IMAR) with iterative reconstruction (IR) on the image quality and diagnostic performance of CT urography in the evaluation of patients with hip prostheses, compared with IR alone. MATERIALS AND METHODS. CT urography examinations that were reconstructed using IR with and without IMAR were analyzed for 57 patients (29 women and 28 men; mean age, 74 years [range, 22-94 years]) with hip prostheses (40 unilateral and 17 bilateral). For quantitative analysis, image noise within the bladder was measured. Two radiologists (radiologist 1 [RAD1] and radiologist 2 [RAD2]) qualitatively evaluated the images using both a 5-point scale to assess the degree of visualization of artifacts and a 6-point scale to determine diagnostic confidence in visualization of the bladder, ureters, prostate or uterus, pelvic calcifications, and genitourinary abnormalities involving the bladder, distal ureters, prostate, uterus, and ovaries. RESULTS. The combination of IMAR and an IR technique provided improvement in quantitative and qualitative measurements (p < 0.05). Forty-three genitourinary abnormalities were detected in 29 patients. Quantitative and qualitative comparisons of scans obtained with and without the use of IMAR, respectively, revealed image noise of 99.6 versus 173.3 HU and the following radiologist scores: for improvement of artifacts, 3.2 versus 1.6 (for RAD1) and 3.1 versus 1.6 (for RAD2); for visualization of the bladder, 3.6 versus 1.5 (RAD1) and 3.8 versus 1.6 (RAD2); visualization of the ureters, 3.8 versus 1.6 (RAD1) and 3.9 versus 1.7 (RAD2); visualization of the uterus, 4.3 versus 2.8 (RAD1) and 4.3 versus 2.6 (RAD2); visualization of the prostate, 4.5 versus 2.3 (RAD1) and 4.5 versus 2.2 (RAD2); diagnostic confidence for calcifications, 4.7 versus 3.5 (RAD1) and 4.7 versus 3.3 (RAD2); and diagnostic confidence for genitourinary abnormalities, 5.0 versus 3.2 (RAD1) and 4.8 versus 2.9 (RAD2), respectively. CONCLUSION. The addition of IMAR to IR led to statistically significant improvement in the retrospective diagnostic performance and image quality of CT urography for patients with hip prostheses, compared with IR alone.