Comparison of Metal Artifact Reduction Algorithms in Patients with Hip Prostheses: Virtual Monoenergetic Images vs. Orthopedic Metal Artifact Reduction

Photon-Counting Detector CT: Clinical Utility of Virtual Monoenergetic Imaging Combined With Tin Prefiltration to Reduce Metal Artifacts in the Postoperative Ankle

OBJECTIVES

The aim of this study was to compare the effectiveness and clinical utility of virtual monoenergetic image (VMI) reconstructions in computed tomography (CT) scans with and without tin prefiltration on a photon-counting detector (PCD) CT system to reduce metal implant artifacts in the postoperative ankle.

MATERIALS AND METHODS

This retrospective study included patients with internal fixation of the ankle scanned with and without tin prefiltration (Sn) on a PCD CT scanner between March and October 2023. Virtual monoenergetic images between 60 and 190 keV were reconstructed with a 10-keV increment in a bone kernel for both acquisitions (VMI Sn and VMI Std , respectively). Noise measurements assessed artifact reduction in the most prominent near-metal image distortions and were compared between acquisitions modes as well as between polychromatic images and VMIs. Three readers assessed the visibility of osseous healing along with interpretability and artifact extent for 5 reconstruction levels.

RESULTS

A total of 48 patients (21 females, 27 males; mean age, 55.1 ± 19.4 years) were included in this study. Tin-prefiltered acquisitions (n = 30) had a lower artifact level for polychromatic images and VMIs compared with non-tin-prefiltered acquisitions (n = 18; P ≤ 0.043). A significant reduction of metal artifacts was observed for VMI Sn ≥120 keV compared with polychromatic images (hyperdense artifacts: 40.2 HU [interquartile range (IQR) 39.8] vs 14.0 HU [IQR 11.1]; P ≤ 0.01 and hypodense artifacts: 91.2 HU [IQR 82.4] vs 29.7 HU [IQR 39.6]; P ≤ 0.001). For VMI Std , this applied to reconstructions ≥100 keV (hyperdense artifacts: 57.7 HU [IQR 33.4] vs 19.4 HU [IQR 27.6]; P ≤ 0.001 and hypodense artifacts: 106.9 HU [IQR 76.1] vs 57.4 HU [IQR 55.7]; P ≤ 0.021). For visibility of osseous healing, VMI Sn at 120 keV yielded higher ratings compared with polychromatic images ( P ≤ 0.001), whereas image interpretability was rated better ( P = 0.023), and artifact extent was rated lower ( P ≤ 0.001) compared with polychromatic images.

CONCLUSIONS

Tin-prefiltered VMI at 120 keV showed a significant reduction in metal artifacts compared with polychromatic images, whereas visibility of osseous healing and image interpretability was improved. Therefore, tin-prefiltration PCD CT with VMI reconstructions may be a helpful complement to postsurgical CT imaging of the ankle in patients with metal implants.

Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction

BACKGROUND

To compare image quality, metal artifacts, and diagnostic confidence of conventional computed tomography (CT) images of unilateral total hip arthroplasty patients (THA) with deep learning-based metal artifact reduction (DL-MAR) to conventional CT and 130-keV monoenergetic images with and without orthopedic metal artifact reduction (O-MAR).

METHODS

Conventional CT and 130-keV monoenergetic images with and without O-MAR and DL-MAR images of 28 unilateral THA patients were reconstructed. Image quality, metal artifacts, and diagnostic confidence in bone, pelvic organs, and soft tissue adjacent to the prosthesis were jointly scored by two experienced musculoskeletal radiologists. Contrast-to-noise ratios (CNR) between bladder and fat and muscle and fat were measured. Wilcoxon signed-rank tests with Holm-Bonferroni correction were used.

RESULTS

Significantly higher image quality, higher diagnostic confidence, and less severe metal artifacts were observed on DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001 for all comparisons). Higher image quality, higher diagnostic confidence for bone and soft tissue adjacent to the prosthesis, and less severe metal artifacts were observed on DL-MAR when compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.014). CNRs were higher for DL-MAR and images with O-MAR compared to images without O-MAR (p < 0.001). Higher CNRs were observed on DL-MAR images compared to conventional images and 130-keV monoenergetic images with O-MAR (p ≤ 0.010).

CONCLUSIONS

DL-MAR showed higher image quality, diagnostic confidence, and superior metal artifact reduction compared to conventional CT images and 130-keV monoenergetic images with and without O-MAR in unilateral THA patients.

RELEVANCE STATEMENT

DL-MAR resulted into improved image quality, stronger reduction of metal artifacts, and improved diagnostic confidence compared to conventional and virtual monoenergetic images with and without metal artifact reduction, bringing DL-based metal artifact reduction closer to clinical application.

KEY POINTS

• Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. • A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. • DL-MAR showed best image quality and diagnostic confidence. • Highest contrast-to-noise ratios were observed on the DL-MAR images.

Advances in metal artifact reduction in CT images: A review of traditional and novel metal artifact reduction techniques

Metal artifacts degrade CT image quality, hampering clinical assessment. Numerous metal artifact reduction methods are available to improve the image quality of CT images with metal implants. In this review, an overview of traditional methods is provided including the modification of acquisition and reconstruction parameters, projection-based metal artifact reduction techniques (MAR), dual energy CT (DECT) and the combination of these techniques. Furthermore, the additional value and challenges of novel metal artifact reduction techniques that have been introduced over the past years are discussed such as photon counting CT (PCCT) and deep learning based metal artifact reduction techniques.

Combining iterative metal artifact reduction and virtual monoenergetic images severely reduces hip prosthesis-associated artifacts in photon-counting detector CT

Aim of this study was to assess the impact of virtual monoenergetic images (VMI) in combination and comparison with iterative metal artifact reduction (IMAR) on hip prosthesis-associated artifacts in photon-counting detector CT (PCD-CT). Retrospectively, 33 scans with hip prosthesis-associated artifacts acquired during clinical routine on a PCD-CT between 08/2022 and 09/2022 were analyzed. VMI were reconstructed for 100-190 keV with and without IMAR, and compared to polychromatic images. Qualitatively, artifact extent and assessment of adjacent soft tissue were rated by two radiologists using 5-point Likert items. Quantitative assessment was performed measuring attenuation and standard deviation in most pronounced hypodense and hyperdense artifacts, artifact-impaired bone, muscle, vessels, bladder and artifact-free corresponding tissue. To quantify artifacts, an adjusted attenuation was calculated as the difference between artifact-impaired tissue and corresponding tissue without artifacts. Qualitative assessment improved for all investigated image reconstructions compared to polychromatic images (PI). VMI_100keV in combination with IMAR achieved best results (e.g. diagnostic quality of the bladder: median PI: 1.5 (range 1-4); VMI_100keV+IMAR: 5 (3-5); p < 0.0001). In quantitative assessment VMI_100keV with IMAR provided best artifact reduction with an adjusted attenuation closest to 0 (e.g. bone: PI: 302.78; VMI_100keV+IMAR: 51.18; p < 0.0001). The combination of VMI and IMAR significantly reduces hip prosthesis-associated artifacts in PCD-CT and improves the diagnostic quality of surrounding tissue.