Utility of an automatic adaptive iterative metal artifact reduction AiMAR algorithm in improving CT imaging of patients with hip prostheses evaluated for suspected bladder malignancy

Mohammadinejad, Payam; Khandelwal, Ashish; Inoue, Akitoshi; Takahashi, Hiroaki; Yalon, Mariana; Long, Zaiyang; Halaweish, Ahmed F.; Leng, Shuai; Yu, Lifeng; Lee, Yong S; McCollough, Cynthia H.; Fletcher, Joel G.

doi:10.1007/s00261-022-03475-8

Cited by 3 publications

(3 citation statements)

References 28 publications

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“…The complete removal of implant-specific strength settings and the application of a single set of correction parameters to different metallic implants increase the variance of artifact correction, as previous studies of the AiMAR prototype have shown. As introduced in the introduction, several studies demonstrated the preference of the dedicated iMAR reconstructions over the generic AiMAR reconstructions in certain body regions, 20,22 also leading to “anatomy blurring in 40% of the implants.” 21 Nevertheless, the benefits of a framework for correcting metal artifacts without additional user input are obvious, as it would optimize the clinical workflow. This was one of the main goals of AiMAR.…”

Section: Discussion and Outlookmentioning

confidence: 99%

“…AiMAR has been shown to provide stable results for most metal cases, particularly in patients with multiple metal implants, 20,21 but it has not been able to match the image quality of the dedicated iMAR presets in individual metal scenarios, apart from its parameter adaption; for example, a first study showed that the AiMAR reconstructions of cases with dental fillings and coils in the head and neck still contained more artifacts than their iMAR counterparts, implying that the artifact reduction was too weak. 20 In contrast, other studies have shown a preference for iMAR reconstructions over AiMAR reconstructions in patients with hip implants 22 or an overcorrection in endoprostheses. 21 To keep the flexibility of adjustable strength settings but to provide dedicated image quality, this work introduced a new iMARv2 framework and performed its first clinical evaluation.…”

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confidence: 98%

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A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems

Anhaus,

Heider,

Killermann

et al. 2024

Invest Radiol

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Objectives The aim of this study was to introduce and evaluate a new metal artifact reduction framework (iMARv2) that addresses the drawbacks (residual artifacts after correction and user preferences for image quality) associated with the current clinically applied iMAR. Materials and Methods A new iMARv2 has been introduced, combining the current iMAR with new modular components to remove residual metal artifacts after image correction. The postcorrection image impression is adjustable with user-selectable strength settings. Phantom scans from an energy-integrating and a photon-counting detector CT were used to assess image quality, including a Gammex phantom and anthropomorphic phantoms. In addition, 36 clinical cases (with metallic implants such as dental fillings, hip replacements, and spinal screws) were reconstructed and evaluated in a blinded and randomized reader study. Results The Gammex phantom showed lower HU errors compared with the uncorrected image at almost all iMAR and iMARv2 settings evaluated, with only minor differences between iMAR and the different iMARv2 settings. In addition, the anthropomorphic phantoms showed a trend toward lower errors with higher iMARv2 strength settings. On average, the iMARv2 strength 3 performed best of all the clinical reconstructions evaluated, with a significant increase in diagnostic confidence and decrease in artifacts. All hip and dental cases showed a significant increase in diagnostic confidence and decrease in artifact strength, and the improvements from iMARv2 in the dental cases were significant compared with iMAR. There were no significant improvements in the spine. Conclusions This work has introduced and evaluated a new method for metal artifact reduction and demonstrated its utility in routine clinical datasets. The greatest improvements were seen in dental fillings, where iMARv2 significantly improved image quality compared with conventional iMAR.

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Section: Discussion and Outlookmentioning

confidence: 99%

mentioning

confidence: 98%

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems

Anhaus,

Heider,

Killermann

et al. 2024

Invest Radiol

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“…At worst, these artifacts lead to completely non-assessable datasets. To meet this challenge, several metal-artifacts-reduction (MAR) algorithms have been developed not only for FD-CTA [12][13][14][15], but also, for example, for mobile cone beam CT imaging of the spine [16], for CT imaging in patients with head and neck cancer and dental implants [17], or patients with suspected bladder malignancy and hip prostheses [18], and even patients with complex lower extremity fractures and external fixators [19]. In all examples, the MAR algorithms demonstrated significant artifact reduction with improved diagnostic quality.…”

Section: Introductionmentioning

confidence: 99%

Clinical Evaluation of an Innovative Metal-Artifact-Reduction Algorithm in FD-CT Angiography in Cerebral Aneurysms Treated by Endovascular Coiling or Surgical Clipping

et al. 2022

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Treated cerebral aneurysms (IA) require follow-up imaging to ensure occlusion. Metal artifacts complicate radiologic assessment. Our aim was to evaluate an innovative metal-artifact-reduction (iMAR) algorithm for flat-detector computed tomography angiography (FD-CTA) regarding image quality (IQ) and detection of aneurysm residua/reperfusion in comparison to 2D digital subtraction angiography (DSA). Patients with IAs treated by endovascular coiling or clipping underwent both FD-CTA and DSA. FD-CTA datasets were postprocessed with/without iMAR algorithm (MAR+/MAR−). Evaluation of all FD-CTA and DSA datasets regarding qualitative (IQ, MAR) and quantitative (coil package diameter/CPD) parameters was performed. Aneurysm occlusion was assessed for each dataset and compared to DSA findings. In total, 40 IAs were analyzed (ncoiling = 24; nclipping = 16). All iMAR+ datasets demonstrated significantly better IQ (pIQ coiling < 0.0001; pIQ clipping < 0.0001). iMAR significantly reduced the metal-artifact burden but did not affect the CPD. iMAR significantly improved the detection of aneurysm residua/reperfusion with excellent agreement with DSA (naneurysm detection MAR+/MAR−/DSA = 22/1/26). The iMAR algorithm significantly improves IQ by effective reduction of metal artifacts in FD-CTA datasets. The proposed algorithm enables reliable detection of aneurysm residua/reperfusion with good agreement to DSA. Thus, iMAR can help to reduce the need for invasive follow-up in treated IAs.

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

Selles,

van Osch,

Maas

et al. 2024

European Journal of Radiology

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Utility of an automatic adaptive iterative metal artifact reduction AiMAR algorithm in improving CT imaging of patients with hip prostheses evaluated for suspected bladder malignancy

Cited by 3 publications

References 28 publications

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems

A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems

Clinical Evaluation of an Innovative Metal-Artifact-Reduction Algorithm in FD-CT Angiography in Cerebral Aneurysms Treated by Endovascular Coiling or Surgical Clipping

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

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