The application of metal artifact reduction methods on computed tomography scans for radiotherapy applications: A literature review

Puvanasunthararajah, Sathyathas; Fontanarosa, Davide; Wille, Marie‐Luise; Camps, Saskia

doi:10.1002/acm2.13255

Cited by 29 publications

(23 citation statements)

References 99 publications

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“…In case of adjuvant radiotherapy, it is important to provide zygomatic implantspecific information to the radiotherapy team. This enables adjustments of the radiotherapy treatment plan and the dosimetric accuracy in radiotherapy [21,22].…”

Section: Discussionmentioning

confidence: 99%

Three-Dimensional Guided Zygomatic Implant Placement after Maxillectomy

Vosselman

Glas

Merema

et al. 2022

JPM

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Zygomatic implants are used in patients with maxillary defects to improve the retention and stability of obturator prostheses, thereby securing good oral function. Prosthetic-driven placement of zygomatic implants is even difficult for experienced surgeons, and with a free-hand approach, deviation from the preplanned implant positions is inevitable, thereby impeding immediate implant-retained obturation. A novel, digitalized workflow of surgical planning was used in 10 patients. Maxillectomy was performed with 3D-printed cutting, and drill guides were used for subsequent placement of zygomatic implants with immediate placement of implant-retained obturator prosthesis. The outcome parameters were the accuracy of implant positioning and the prosthetic fit of the obturator prosthesis in this one-stage procedure. Zygomatic implants (n = 28) were placed with good accuracy (mean deviation 1.73 ± 0.57 mm and 2.97 ± 1.38° 3D angle deviation), and in all cases, the obturator prosthesis fitted as pre-operatively planned. The 3D accuracy of the abutment positions was 1.58 ± 1.66 mm. The accuracy of the abutment position in the occlusal plane was 2.21 ± 1.33 mm, with a height accuracy of 1.32 ± 1.57 mm. This feasibility study shows that the application of these novel designed 3D-printed surgical guides results in predictable zygomatic implant placement and provides the possibility of immediate prosthetic rehabilitation in head and neck oncology patients after maxillectomy.

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Section: Discussionmentioning

confidence: 99%

Three-Dimensional Guided Zygomatic Implant Placement after Maxillectomy

Vosselman

Glas

Merema

et al. 2022

JPM

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“…In another study, different implant types were shown to respond differently to DECT and projection-based algorithms with varying MAR efficacy; a combination of the two provided the best artifact suppression from spine implants [91]. While these MAR techniques are useful for followup imaging post instrumentation in MSCC, a recent systemic review showed that they have a limited role in radiotherapy applications due to various factors including the introduction of additional artifacts, and more research is needed to overcome these limitations [92]. While projection-based MAR algorithms address artifacts related to photon starvation, DECT can be utilized to reduce beam hardening artifacts without significant additional radiation exposure [37,77,86,87].…”

Section: Challenges Of Ct: Metal-related Artifactsmentioning

confidence: 99%

State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression

Kuah

Vellayappan

Makmur

et al. 2022

Cancers

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Metastatic Spinal Cord Compression (MSCC) is a debilitating complication in oncology patients. This narrative review discusses the strengths and limitations of various imaging modalities in diagnosing MSCC, the role of imaging in stereotactic body radiotherapy (SBRT) for MSCC treatment, and recent advances in deep learning (DL) tools for MSCC diagnosis. PubMed and Google Scholar databases were searched using targeted keywords. Studies were reviewed in consensus among the co-authors for their suitability before inclusion. MRI is the gold standard of imaging to diagnose MSCC with reported sensitivity and specificity of 93% and 97% respectively. CT Myelogram appears to have comparable sensitivity and specificity to contrast-enhanced MRI. Conventional CT has a lower diagnostic accuracy than MRI in MSCC diagnosis, but is helpful in emergent situations with limited access to MRI. Metal artifact reduction techniques for MRI and CT are continually being researched for patients with spinal implants. Imaging is crucial for SBRT treatment planning and three-dimensional positional verification of the treatment isocentre prior to SBRT delivery. Structural and functional MRI may be helpful in post-treatment surveillance. DL tools may improve detection of vertebral metastasis and reduce time to MSCC diagnosis. This enables earlier institution of definitive therapy for better outcomes.

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“…[1][2][3] Existing methods have demonstrated improved image quality such as reduced standard deviation, improved CT number accuracy, and improved subjective image quality evaluation. 3 However, existing methods can result in residual artifacts and CT number inaccuracies. [1][2][3][4][5][6][7] Many different approaches have been proposed for reducing metal artifacts.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous metal artifact reduction methods have been proposed and clinically implemented to reduce the severity of metal artifacts 1–3 . Existing methods have demonstrated improved image quality such as reduced standard deviation, improved CT number accuracy, and improved subjective image quality evaluation 3 . However, existing methods can result in residual artifacts and CT number inaccuracies 1–7 …”

Section: Introductionmentioning

confidence: 99%

Addressing CT metal artifacts using photon‐counting detectors and one‐step spectral CT image reconstruction

et al. 2022

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The constrained one-step spectral CT image reconstruction (cOSS-CIR) algorithm with a nonconvex alternating direction method of multipliers optimizer is proposed for addressing computed tomography (CT) metal artifacts caused by beam hardening, noise, and photon starvation. The quantitative performance of cOSSCIR is investigated through a series of photon-counting CT simulations. Methods: cOSSCIR directly estimates basis material maps from photoncounting data using a physics-based forward model that accounts for beam hardening. The cOSSCIR optimization framework places constraints on the basis maps, which we hypothesize will stabilize the decomposition and reduce streaks caused by noise and photon starvation. Another advantage of cOSSCIR is that the spectral data need not be registered, so that a ray can be used even if some energy window measurements are unavailable. Photon-counting CT acquisitions of a virtual pelvic phantom with low-contrast soft tissue texture and bilateral hip prostheses were simulated. Bone and water basis maps were estimated using the cOSSCIR algorithm and combined to form a virtual monoenergetic image for the evaluation of metal artifacts. The cOSSCIR images were compared to a "two-step" decomposition approach that first estimated basis sinograms using a maximum likelihood algorithm and then reconstructed basis maps using an iterative total variation constrained least-squares optimization (MLE+TV min ). Images were also compared to a nonspectral TV min reconstruction of the total number of counts detected for each ray with and without normalized metal artifact reduction (NMAR) applied. The simulated metal density was increased to investigate the effects of increasing photon starvation. The quantitative error and standard deviation in regions of the phantom were compared across the investigated algorithms. The ability of cOSSCIR to reproduce the soft-tissue texture, while reducing metal artifacts, was quantitatively evaluated. Results: Noiseless simulations demonstrated the convergence of the cOSS-CIR and MLE+TV min algorithms to the correct basis maps in the presence of beam-hardening effects. When noise was simulated, cOSSCIR demonstrated a quantitative error of −1 HU, compared to 2 HU error for the MLE+TV min algorithm and −154 HU error for the nonspectral TV min +NMAR algorithm. For the cOSSCIR algorithm, the standard deviation in the central iodine region of interest was 20 HU, compared to 299 HU for the MLE+TV min algorithm, 41 HU for the MLE+TV min +Mask algorithm that excluded rays through metal, and 55 HU for the nonspectral TV min +NMAR algorithm. Increasing levels of photon starvation did not impact the bias or standard deviation of the cOSSCIR images. cOSSCIR was able to reproduce the soft-tissue texture when an appropriate regularization constraint value was selected.

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The application of metal artifact reduction methods on computed tomography scans for radiotherapy applications: A literature review

Cited by 29 publications

References 99 publications

Three-Dimensional Guided Zygomatic Implant Placement after Maxillectomy

Three-Dimensional Guided Zygomatic Implant Placement after Maxillectomy

State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression

Addressing CT metal artifacts using photon‐counting detectors and one‐step spectral CT image reconstruction

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