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A New Iterative Metal Artifact Reduction Algorithm for Both Energy-Integrating and Photon-Counting CT Systems.
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- Author(s): Anhaus JA;Anhaus JA;Anhaus JA;Anhaus JA; Heider M; Killermann P; Hofmann C; Mahnken AH
- Source:
Investigative radiology [Invest Radiol] 2024 Jul 01; Vol. 59 (7), pp. 526-537. Date of Electronic Publication: 2024 Jan 09.- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0045377 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-0210 (Electronic) Linking ISSN: 00209996 NLM ISO Abbreviation: Invest Radiol Subsets: MEDLINE
- Publication Information: Publication: 1998- : Hagerstown, MD : Lippincott Williams & Wilkins
Original Publication: Philadelphia. - Subject Terms: Artifacts* ; Metals* ; Phantoms, Imaging* ; Algorithms* ; Tomography, X-Ray Computed*/methods ; Photons*; Humans ; Radiographic Image Interpretation, Computer-Assisted/methods ; Reproducibility of Results ; Radiographic Image Enhancement/methods ; Sensitivity and Specificity ; Prostheses and Implants
- Abstract: 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.
Competing Interests: Conflicts of interest and sources of funding: none declared.
(Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.) - References: Boas FE, Fleischmann D. CT artifacts: causes and reduction techniques. J Med Imaging . 2012;4:229–240.
Kalender WA, Hebel R, Ebersberger J. Reduction of CT artifacts caused by metallic implants. Radiology . 1987;164:576–577.
Meyer E, Raupach R, Lell M, et al. Normalized metal artifact reduction (NMAR) in computed tomography. Med Phys . 2010;37:5482–5493.
Meyer E, Raupach R, Lell M, et al. Frequency split metal artifact reduction (FSMAR) in computed tomography. Med Phys . 2012;39:1904–1916.
Krauss A, Raupach R, Schmidt B, et al. Iterative metal artifact reduction in computed tomography. In: Radiological Society of North America 2013 Scientific Assembly and Annual Meeting . Chicago, IL: Radiological Society of North America; 2013.
Kachelrieß M, Krauss A. Whitepaper. Iterative Metal Artifact Reduction (iMAR): Technical Principles and Clinical results in Radiation Therapy. 2016. [Online]. Available at: https://cdn0.scrvt.com/39b415fb07de4d9656c7b516d8e2d907/1800000004904518/83085a287878/RO_Internet_Whitepaper_iMAR_1800000004904518.pdf . Accessed February 2, 2023.
Aissa J, Boos J, Sawicki LM, et al. Iterative metal artefact reduction (MAR) in postsurgical chest CT: comparison of three iMAR-algorithms. Br J Radiol . 2017;90:20160778.
Long Z, Bruesewitz MR, DeLone DR, et al. Evaluation of projection- and dual-energy-based methods for metal artifact reduction in CT using a phantom study. J Appl Clin Med Phys . 2018;19:252–260.
Maerz M, Mittermair P, Krauss A, et al. Iterative metal artifact reduction improves dose calculation accuracy. Strahlenther Onkol . 2016;192:403–413.
Lim P, Barber J, Sykes J. Evaluation of dual energy CT and iterative metal artefact reduction (iMAR) for artefact reduction in radiation therapy. Australas Phys Eng Sci Med . 2019;42:1025–1032.
Andersson KM, Dahlgren CV, Reizenstein J, et al. Evaluation of two commercial CT metal artifact reduction algorithms for use in proton radiotherapy treatment planning in the head and neck area. Med Phys . 2018;45:4329–4344.
Bongers MN, Schabel C, Thomas C, et al. Comparison and combination of dual-energy- and iterative-based metal artefact reduction on hip prosthesis and dental implants. PLoS One . 2015;10:e0143584.
Wuest W, May MS, Brand M, et al. Improved image quality in head and neck CT using a 3D iterative approach to reduce metal artifact. AJNR Am J Neuroradiol . 2015;36:1988–1993.
Weiß J, Schabel C, Bongers M, et al. Impact of iterative metal artifact reduction on diagnostic image quality in patients with dental hardware. Acta Radiol . 2017;58:279–285.
Marcus RP, Morris JM, Matsumoto JM, et al. Implementation of iterative metal artifact reduction in the pre-planning-procedure of three-dimensional physical modeling. 3D Print Med . 2017;3:5.
Młynarski R, Sosna M, Honkowicz M, et al. Usefulness of metal artifact reduction algorithms from the pacemaker lead in diagnosis of late perforation: the right choice makes it easier to make a decision. Kardiol Pol . 2023;81:310–311.
Shinohara Y, Ohmura T, Sasaki F, et al. Appropriate iMAR presets for metal artifact reduction from surgical clips and titanium burr hole covers on postoperative non-contrast brain CT. Eur J Radiol . 2021;141:109811.
Halaweish AF, Schmidt B, Grant K, et al. Automatic adaptive iterative metal artifact reduction. In: The European Congress of Radiology (ECR) . Vienna, Austria: European Congress of Radiology; 2018.
Jacobsen M, Thompson E, Liu X, et al. Comparison of iMAR and AiMAR techniques for metal artifact reduction in CT-guided microwave studies. In: The 2020 Joint AAPM | COMP Virtual Meeting . Online; 2020. Available at: https://w3.aapm.org/meetings/2020AM/programInfo/programAbs.php?sid=8489&aid=52740 . Accessed December 6, 2023.
Hagen JA, Hofmamn C, Mohammadinejad P, et al. Ability of a single adaptive iterative metal artifact reduction algorithm to improve CT image quality in patients with multiple metal implants. In: The 105th Scientific Assembly and Annual Meeting of the Radiological Society of North America . Chicago, IL: Radiological Society of North America; 2019.
Long Z, Tiegs-Heiden CA, Anderson TL, et al. Clinical evaluation of a new adaptive iterative metal artifact reduction method in whole-body low-dose CT skeletal survey examinations. Skeletal Radiol . 2021;50:149–157.
Mohammadinejad P, Khandelwal AR, Inoue A, et al. 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. Abdom Radiol (NY) . 2022;47:2158–2167.
Anhaus JA, Schmidt S, Killermann P, et al. Iterative metal artifact reduction on a clinical photon counting system—technical possibilities and reconstruction selection for optimal results dependent on the metal scenario. Phys Med Biol . 2022;67:115018.
Subhas N, Primak AN, Obuchowski NA, et al. Iterative metal artifact reduction: evaluation and optimization of technique. Skeletal Radiol . 2014;43:1729–1735.
Anhaus JA, Killermann P, Sedlmair M, et al. Nonlinearly scaled prior image-controlled frequency split for high-frequency metal artifact reduction in computed tomography. Med Phys . 2022;49:5870–5885.
Anhaus JA, Killermann P, Mahnken AH, et al. A nonlinear scaling-based normalized metal artifact reduction to reduce low-frequency artifacts in energy-integrating and photon-counting CT. Med Phys . 2023;50:4721–4733.
Constantinou C, Harrington JC, DeWerd LA. An electron density calibration phantom for CT-based treatment planning computers. Med Phys . 1992;19:325–327.
Axente M, Paidi A, Von Eyben R, et al. Clinical evaluation of the iterative metal artifact reduction algorithm for CT simulation in radiotherapy. Med Phys . 2015;42:1170–1183.
Higashigaito K, Angst F, Runge VM, et al. Metal artifact reduction in pelvic computed tomography with hip prostheses: comparison of virtual monoenergetic extrapolations from dual-energy computed tomography and an iterative metal artifact reduction algorithm in a phantom study. Invest Radiol . 2015;50:828–834.
Layer YC, Mesropyan N, Kupczyk PA, et al. Combining iterative metal artifact reduction and virtual monoenergetic images severely reduces hip prosthesis-associated artifacts in photon-counting detector CT. Sci Rep . 2023;13:8955.
Schreck J, Laukamp KR, Niehoff JH, et al. Metal artifact reduction in patients with total hip replacements: evaluation of clinical photon counting CT using virtual monoenergetic images. Eur Radiol . 2023. Available at: https://pubmed.ncbi.nlm.nih.gov/37436505/ . Accessed December 6, 2023.
Patzer TS, Kunz AS, Huflage H, et al. Combining virtual monoenergetic imaging and iterative metal artifact reduction in first-generation photon-counting computed tomography of patients with dental implants. Eur Radiol . 2023;33:7818–7829.
Risch F, Decker JA, Popp D, et al. Artifact reduction from dental material in photon-counting detector computed tomography data sets based on high-keV monoenergetic imaging and iterative metal artifact reduction reconstructions—can we combine the best of two worlds? Invest Radiol . 2023;58:691–696.
Skornitzke S, Mergen V, Biederer J, et al. Metal artifact reduction in photon-counting detector CT: quantitative evaluation of artifact reduction techniques. Invest Radiol . 2023. Available at: https://pubmed.ncbi.nlm.nih.gov/37812482/ . Accessed December 6, 2023.
Byl A, Klein L, Hardt J, et al. Metal artifact reduction in photon counting CT using pseudo-monochromatic images. In: The 6th International Conference on Image Formation in X-Ray Computed Tomography . 2020. Available at: https://www.ct-meeting.org/data/ProceedingsCTMeeting2020.pdf . Accessed December 6, 2023.
Zhou W, Bartlett DJ, Diehn FE, et al. Reduction of metal artifacts and improvement in dose efficiency using photon-counting detector computed tomography and tin filtration. Invest Radiol . 2019;54:204–211.
Byl A, Klein L, Sawall S, et al. Photon counting normalized metal artifact reduction (NMAR) in diagnostic CT. Med Phys . 2021;48:3572–3582.
Schmidt TG, Barber RF, Sidky EY. Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm. In: Medical Imaging 2017: Physics of Medical Imaging . Orlando, FL; 2017. Available at: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10132/1/Spectral-CT-metal-artifact-reduction-with-an-optimization-based-reconstruction/10.1117/12.2249079.short?SSO=1 . Accessed December 6, 2023.
Runge VM, Marquez H, Andreisek G, et al. Recent technological advances in computed tomography and the clinical impact therein. Invest Radiol . 2015;50:119–127.
McCollough CH, Leng S, Yu L, et al. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology . 2015;276:637–653.
Mahnken AH, Raupach R, Wildberger JE, et al. A new algorithm for metal artifact reduction in computed tomography: in vitro and in vivo evaluation after total hip replacement. Invest Radiol . 2003;38:769–775.
Zhang Y, Yu H. Convolutional neural network based metal artifact reduction in x-ray computed tomography. IEEE Trans Med Imaging . 2018;37:1370–1381.
Bauer DF, Ulrich C, Russ T, et al. End-to-end deep learning CT image reconstruction for metal artifact reduction. Appl Sci . 2021;12:404.
Lin WA, Liao H, Peng C, et al. Dudonet: dual domain network for CT metal artifact reduction. Proc IEEE/CVF Conf Comput Vis Pattern Recognit . 2019;10512–10521. - Accession Number: 0 (Metals)
- Publication Date: Date Created: 20240109 Date Completed: 20240607 Latest Revision: 20240621
- Publication Date: 20240622
- Accession Number: 10.1097/RLI.0000000000001055
- Accession Number: 38193772
- Source:
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