Metal artifact reduction (MAR) based on two-compartment physical modeling: evaluation in patients with hip implants

Impact of different iterative metal artifact reduction (iMAR) algorithms on PET/CT attenuation correction after port implementation

PURPOSE

To evaluate the effect of various interactive metal artifact reduction (iMAR) algorithms on attenuation correction in the vicinity of port chambers in PET/CT.

MATERIAL AND METHODS

In this prospective study, 30 oncological patients (12 female, 18 male, mean age 59.6 ± 10.5y) with implanted port chambers undergoing 18F-FDG PET/CT were included. CT images were reconstructed with standard weighted filtered back projection (WFBP) and three different iMAR algorithms (hip, dental filling (DF) and pacemaker (PM)). PET attenuation correction was performed with all four CT datasets. SUVmean, SUVmax and HU measurements were performed in fat and muscle tissue in the vicinity of the port chamber at the location of the strongest bright and dark band artifacts. Differences between HU and SUV values across all CT- and PET-images were investigated using a paired t-test. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.008).

RESULTS

In comparison to WFBP (fat: 94.2 ± 53.9 HU, muscle: 197.6 ± 49.2 HU) all three iMAR algorithms led to a decrease of HU in bright band artifacts. iMAR-DF led to a decrease of 159.2 % (fat: -51.9 ± 58.5 HU, muscle: 94.5 ± 55.3 HU), iMAR-hip of 138.3 % (fat: -30.3 ± 58.5, muscle: 70.4 ± 28.8) and iMAR-PM of 122.3 % (fat: -21.2 ± 47.2 HU, muscle: 72.5 ± 25.1 HU; for all p < 0.008). There was no significant effect of iMAR on SUV measurements in comparison to WFBP.

CONCLUSION

iMAR leads to a significant change of HU values in artifacts caused by port catheter chambers in comparison to WFBP. However, no significant differences in attenuation correction and consecutive changes in SUV measurements can be observed.

Impact of different metal artifact reduction techniques on attenuation correction in 18F-FDG PET/CT examinations

OBJECTIVE

To evaluate the impact of different metal artifact reduction (MAR) algorithms on Hounsfield unit (HU) and standardized uptake values (SUV) in a phantom setting and verify these results in patients with metallic implants undergoing oncological PET/CT examinations.

METHODS AND MATERIALS

In this prospective study, PET-CT examinations of 28 oncological patients (14 female, 14 male, mean age 69.5 ± 15.2y) with 38 different metal implants were included. CT datasets were reconstructed using standard weighted filtered back projection (WFBP) without MAR, MAR in image space (MARIS) and iterative MAR (iMAR, hip algorithm). The three datasets were used for PET attenuation correction. SUV and HU measurements were performed at the site of the most prominent bright and dark band artifacts. Differences between HU and SUV values across the different reconstructions were compared using paired t-tests. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.017).

RESULTS

For bright band artifacts, MARIS led to a non-significant mean decrease of 12.0% (345 ± 315 HU) in comparison with WFBP (391 ± 293 HU), whereas iMAR led to a significant decrease of 68.3% (125 ± 185 HU, p < 0.017). For SUVmean, MARIS showed no significant effect in comparison with WFBP (WFBP: 0.99 ± 0.40, MARIS: 0.96 ± 0.39), while iMAR led to a significant decrease of 11.1% (0.88 ± 0.35, p < 0.017). Similar results were observed for dark band artifacts.

CONCLUSION

iMAR significantly reduces artifacts caused by metal implants in CT and thus leads to a significant change of SUV measurements in bright and dark band artifacts compared with WFBP and MARIS, thus probably improving PET quantification.

ADVANCES IN KNOWLEDGE

The present work indicates that MAR algorithms such as iMAR algorithm in integrated PET/CT scanners are useful to improve CT image quality as well as PET quantification in the evaluation of tracer uptake adjacent to large metal implants. A detailed analysis of oncological patients with various large metal implants using different MAR algorithms in PET/CT has not been conducted yet.

Iterative metal artefact reduction (MAR) in postsurgical chest CT: comparison of three iMAR-algorithms

OBJECTIVES

The purpose of this study was to evaluate the impact of three novel iterative metal artefact (iMAR) algorithms on image quality and artefact degree in chest CT of patients with a variety of thoracic metallic implants.

METHODS

27 postsurgical patients with thoracic implants who underwent clinical chest CT between March and May 2015 in clinical routine were retrospectively included. Images were retrospectively reconstructed with standard weighted filtered back projection (WFBP) and with three iMAR algorithms (iMAR-Algo1 = Cardiac algorithm, iMAR-Algo2 = Pacemaker algorithm and iMAR-Algo3 = ThoracicCoils algorithm). The subjective and objective image quality was assessed.

RESULTS

Averaged over all artefacts, artefact degree was significantly lower for the iMAR-Algo1 (58.9 ± 48.5 HU), iMAR-Algo2 (52.7 ± 46.8 HU) and the iMAR-Algo3 (51.9 ± 46.1 HU) compared with WFBP (91.6 ± 81.6 HU, p < 0.01 for all). All iMAR reconstructed images showed significantly lower artefacts (p < 0.01) compared with the WFPB while there was no significant difference between the iMAR algorithms, respectively. iMAR-Algo2 and iMAR-Algo3 reconstructions decreased mild and moderate artefacts compared with WFBP and iMAR-Algo1 (p < 0.01).

CONCLUSION

All three iMAR algorithms led to a significant reduction of metal artefacts and increase in overall image quality compared with WFBP in chest CT of patients with metallic implants in subjective and objective analysis. The iMARAlgo2 and iMARAlgo3 were best for mild artefacts. IMARAlgo1 was superior for severe artefacts. Advances in knowledge: Iterative MAR led to significant artefact reduction and increase image-quality compared with WFBP in CT after implementation of thoracic devices. Adjusting iMAR-algorithms to patients' metallic implants can help to improve image quality in CT.

Dual energy CT angiography: pros and cons of dual-energy metal artifact reduction algorithm in patients after endovascular aortic repair

PURPOSE

To evaluate the value of metal artifact reduction (MAR) post-processing and iodine MD images in fast kV-switching dual-energy computed tomography (DECT) in patients after endovascular aortic repair (EVAR).

MATERIALS AND METHODS

Twenty-four consecutive EVAR patients (age 76 ± 9 years, 7/24 (29%) with coils, 9/24 (37.5%) with 10 endoleaks) who underwent DECT angiography were included in this HIPAA-compliant, IRB-approved retrospective study. Monochromatic reconstructions included 55, 60, 65, 70, and 75 keV with and without MAR and iodine MD images. Near field, far field, and vessel artifacts were assessed subjectively (1 = none; 5 = severe) and objectively by measuring noise and contrast-to-noise ratio. Visibility of endoleak was evaluated (1 = optimal; 5 = not visible).

RESULTS

MAR objectively decreased artifacts from EVAR stents in the near field (60.7 ± 25.4 HU vs. 70.1 ± 34.2; p = .002) and subjectively increased near field (3.2 ± 0.9 vs. 2.8 ± 0.6; p < .001), far field (2.2 ± 0.6 vs. 1.6 ± 0.6; p < .001), and vessel (3.1 ± 1.1 vs. 2.5 ± 0.9; p < .001) artifacts. Near-field artifacts from coils were reduced by the MAR objectively (72.4 ± 24.8 vs. 182.7 ± 57.3 HU; p < .001) and subjectively (4.5 ± 0.5 vs. 4.9 ± 0.4; p = .02). CNR of standard reconstructions was optimal at 60 keV (38.3 ± 16.8). Reconstructions without MAR and iodine MD images provided improved endoleak visualization in 6/10 (60%) of cases (median 1 for both) compared to MAR (median 3) (p < 0.001). However, MAR improved visualization in 1/10 (10%) cases due to endoleak location adjacent to a coil.

CONCLUSION

DECT with MAR reduced artifacts from coils and improved endoleak visualization in 1/10 (10%) cases due to location adjacent to a coil. However, MAR impaired endoleak visualization in 6/10 (60%) cases and should be reviewed combined with 60 keV standard reconstructions and iodine MD images.

Clinical evaluation of the iterative metal artefact reduction algorithm for post-operative CT examination after maxillofacial surgery

OBJECTIVES

Metal artefacts present challenges to both radiologists and clinicians during post-operative imaging. Such artefacts reduce the diagnostic effectiveness of CT scans and mask findings that could be vital for patient management. Thus, a powerful artefact reduction tool is necessary when imaging patients with metal implants. Our aim was to test the recently introduced iterative metal artefact reduction (iMAR) algorithm in patients with maxillofacial implants.

METHODS

Images from 17 patients with diverse maxillofacial metal implants who had undergone CT scans were qualitatively and quantitatively analyzed before and after metal artefact reduction with iMAR.

RESULTS

After iMAR application, images exhibited decreased artefacts and improved image quality, leading to detection of lesions that were previously masked by artefacts. The application of iMAR did not affect image quality in regions distant from the metal implants.

CONCLUSIONS

The application of iMAR to CT examinations of patients with maxillofacial metal implants leads to artefact reduction, improvement of image quality and increased diagnostic utility. Routine implementation of iMAR during imaging of patients with metal hardware implants could add diagnostic value to their CT examinations.

Iterative metal artefact reduction in CT: can dedicated algorithms improve image quality after spinal instrumentation?

AIM

To investigate the value of dedicated computed tomography (CT) iterative metal artefact reduction (iMAR) algorithms in patients after spinal instrumentation.

MATERIALS AND METHODS

Post-surgical spinal CT images of 24 patients performed between March 2015 and July 2016 were retrospectively included. Images were reconstructed with standard weighted filtered back projection (WFBP) and with two dedicated iMAR algorithms (iMAR-Algo1, adjusted to spinal instrumentations and iMAR-Algo2, adjusted to large metallic hip implants) using a medium smooth kernel (B30f) and a sharp kernel (B70f). Frequencies of density changes were quantified to assess objective image quality. Image quality was rated subjectively by evaluating the visibility of critical anatomical structures including the central canal, the spinal cord, neural foramina, and vertebral bone.

RESULTS

Both iMAR algorithms significantly reduced artefacts from metal compared with WFBP (p<0.0001). Results of subjective image analysis showed that both iMAR algorithms led to an improvement in visualisation of soft-tissue structures (median iMAR-Algo1=3; interquartile range [IQR]:1.5-3; iMAR-Algo2=4; IQR: 3.5-4) and bone structures (iMAR-Algo1=3; IQR:3-4; iMAR-Algo2=4; IQR:4-5) compared to WFBP (soft tissue: median 2; IQR: 0.5-2 and bone structures: median 2; IQR: 1-3; p<0.0001). Compared with iMAR-Algo1, objective artefact reduction and subjective visualisation of soft-tissue and bone structures were improved with iMAR-Algo2 (p<0.0001).

CONCLUSION

Both iMAR algorithms reduced artefacts compared with WFBP, however, the iMAR algorithm with dedicated settings for large metallic implants was superior to the algorithm specifically adjusted to spinal implants.