CT metal artifact reduction algorithms: Toward a framework for objective performance assessment

Metal artifact reduction on musculoskeletal CT: a phantom and clinical study

BACKGROUND

Artifacts caused by metal implants are challenging when undertaking computed tomography (CT). Dedicated algorithms have shown promising results although with limitations. Tin filtration (Sn) in combination with high tube voltage also shows promise but with limitations. There is a need to examine these limitations in more detail. The purpose of this study was to investigate the impact of different metal artefact reduction (MAR) algorithms, tin filtration, and ultra-high-resolution (UHR) scanning, alone or in different combinations in both phantom and clinical settings.

METHODS

An ethically approved clinical and phantom study was conducted. A modified Catphan® phantom with titanium and stainless-steel inserts was scanned with six different MAR protocols with tube voltage ranging from 80 to 150 kVp. Other scan parameters were kept identical. The differences (∆) in mean HU and standard deviation (SD) in images, with and without metal, were measured and compared. In the clinical study, three independent readers performed visual image quality assessments on eight different protocols using retrospectively acquired images.

RESULTS

Iterative MAR had the lowest ∆HU and ∆SD in the phantom study. For images of the forearm, the soft tissue noise for Sn-based 150-kVp UHR protocol with was significantly higher (p = 0.037) than for single-energy MAR protocols. All Sn-based 150-kVp protocols were rated significantly higher (p < 0.046 than the single-energy MAR protocols in the visual assessment.

CONCLUSIONS

All Sn-based 150-kVp UHR protocols showed similar objective MAR in the phantom study, and higher objective MAR and significantly improved visual image quality than single-energy MAR.

RELEVANCE STATEMENT

Images with less metal artifacts and higher visual image quality may be more clinically optimal in CT examination of musculoskeletal patients with metal implants.

KEY POINTS

• Metal artifact reduction algorithms and Sn filter combined with high kVp reduce artifacts. • Metal artifact reduction algorithms introduce new artifacts in certain metals. • Sn-based protocols alone may be considered as low metal artifact protocols.

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.

Reducing metal artifacts by restricting negative pixels

When the object contains metals, its x-ray computed tomography (CT) images are normally affected by streaking artifacts. These artifacts are mainly caused by the x-ray beam hardening effects, which deviate the measurements from their true values. One interesting observation of the metal artifacts is that certain regions of the metal artifacts often appear as negative pixel values. Our novel idea in this paper is to set up an objective function that restricts the negative pixel values in the image. We must point out that the naïve idea of setting the negative pixel values in the reconstructed image to zero does not give the same result. This paper proposes an iterative algorithm to optimize this objective function, and the unknowns are the metal affected projections. Once the metal affected projections are estimated, the filtered backprojection algorithm is used to reconstruct the final image. This paper applies the proposed algorithm to some airport bag CT scans. The bags all contain unknown metallic objects. The metal artifacts are effectively reduced by the proposed algorithm.

Comparison of metal artifact reduction using single-energy CT and dual-energy CT with various metallic implants in cadavers

OBJECTIVES

The purpose of this study was to compare the effectiveness of metal artifact reduction using Single Energy Metal Artifact Reduction (SEMAR) and Dual Energy CT (DECT).

MATERIALS AND METHODS

Six cadavers containing metal implants in the head, neck, abdomen, pelvis, and extremities were scanned with Standard, SEMAR, and DECT protocols on a 320-slice CT scanner. Four specialized radiologists blinded to acquisition methods rated severity of metal artifacts, visualization of anatomic structures, diagnostic interpretation, and image preference with a 5-point grading scale.

RESULTS

Scores were significantly better for SEMAR than Standard images in the hip, knee, pelvis, abdomen, and maxillofacial scans (3.25 ± 0.88 versus 2.14 ± 0.93, p < 0.001). However, new reconstruction artifacts developed in SEMAR images that were not present in Standard images. Scores for severity of metal artifacts and visualization of smooth structures were significantly better for DECT than Standard images in the cervical spine (3.50±0.50 versus 2.0±0.58, p < 0.001) and was preferred over Standard images by one radiologist. In all other cases, radiologists preferred the Standard image over the DECT image due to increased image noise and reduced low-contrast resolution with DECT. In all cases, SEMAR was preferred over Standard and DECT images.

CONCLUSION

SEMAR was more effective at reducing metal artifacts than DECT. Radiologists should be aware of new artifacts and review both the original and SEMAR images. When the anatomy or implant is relatively small, DECT may be superior to SEMAR without additional artifacts. However, radiologist should be aware of a reduction in soft tissue contrast.