Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress

Liu, Patrick T.; Pavlicek, William; Peter, Mary Beth; Spangehl, Mark J.; Roberts, Catherine C.; Paden, Robert G.

doi:10.1007/s00256-008-0630-5

Cited by 72 publications

(51 citation statements)

References 13 publications

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“…2 The maximum width measured on a CT scan for a 7-mm screw is shown. purpose but has been shown to produce significant metal artifact when imaging stainless steel implants, making image interpretation difficult [2,14,17,24,26]. Since volume, or size, of implant adversely affects image quality, surgeons can choose to downsize spinal implants trading fixation strength for improved postoperative imaging capability [26,31].…”

Section: Discussionmentioning

confidence: 99%

“…Plain radiographs may show gross screw malposition, but advanced imaging is required to truly verify screw position in three dimensions [1]. Numerous authors have reported significant metal artifact when imaging stainless steel implants with CT or MRI making image interpretation difficult [2,14,17,24,26]. The degree of artifact produced is dependent on the cross-sectional area of the implant imaged.…”

Section: Introductionmentioning

confidence: 99%

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CT Provides Precise Size Assessment of Implanted Titanium Alloy Pedicle Screws

Elliott

Slakey

2014

Clinical Orthopaedics &Amp; Related Research

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Background After performing instrumented spinal fusion with pedicle screws, postoperative imaging using CT to assess screw position may be necessary. Stainless steel implants produce significant metal artifact on CT, and the degree of distortion is at least partially dependent on the cross-sectional area of the implanted device. If the same effect occurs with titanium alloy implants, ability to precisely measure proximity of screws to adjacent structures may be adversely affected as screw size increases. Questions/purposes We therefore asked whether (1) CT provides precise measurements of true screw widths; and (2) precision degrades based on the size of the titanium implant imaged.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CT Provides Precise Size Assessment of Implanted Titanium Alloy Pedicle Screws

Elliott

Slakey

2014

Clinical Orthopaedics &Amp; Related Research

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“…A study by Liu et. al (19) . noted that the MAR reconstruction algorithm improved CT image quality for patients with large metal orthopedic implants, but introduced blurring artifact when used on patients with small metal implants.…”

Section: Discussionmentioning

confidence: 99%

“…A major prerequisite of using fiducial markers for this purpose is clear identification of the markers on the images without introducing a significant amount of artifacts. The reduction of artifacts on the planning CT is especially desirable, since extensive artifacts could interfere with structure delineation and dose calculations, especially if an inhomogeneity correction treatment planning algorithm is used 13 , 19 . Given the plethora of imaging systems available for positioning verification, questions remain about the optimal choice of fiducial marker material for any given imaging system and the effects of various imaging parameters on image quality.…”

Section: Introductionmentioning

confidence: 99%

Determination of optimal fiducial marker across image‐guided radiation therapy (IGRT) modalities: visibility and artifact analysis of gold, carbon, and polymer fiducial markers

Handsfield¹,

Yue²,

Zhou³

et al. 2012

J Applied Clin Med Phys

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The purpose of this study was to evaluate the visibility and artifact created by gold, carbon, and polymer fiducial markers in a simple phantom across computed tomography (CT), kilovoltage (kV), and megavoltage (MV) linear accelerator imaging and MV tomotherapy imaging. Three types of fiducial markers (gold, carbon, and polymer) were investigated for their visibility and artifacts in images acquired with various modalities and with different imaging parameters (kV, mAs, slice thickness). The imaging modalities include kV CT, 2D linac‐based kilovoltage and megavoltage X‐ray imaging systems, kV cone‐beam CT, and normal and fine tomotherapy imaging. The images were acquired on a phantom constructed using Superflab bolus in which markers of each type were inserted into the center layer. The visibility and artifacts produced by each marker were assessed qualitatively and quantitatively. All tested markers could be identified clearly on the acquired CT and linac‐based kV images; gold markers demonstrated the highest contrast. On the CT images, gold markers produced a significant artifact, while no artifacts were observed with polymer markers. Only gold markers were visible when using linac‐based MV and tomotherapy imaging. For linac‐based kV images, the contrast increased with kV and mAs values for all the markers, with the gold being the most pronounced. On CT images, the contrast increased with kV for the gold markers, while decreasing for the polymer and carbon marker. With the bolus phantom used, we found that when kV imaging‐based treatment verification equipment is available, polymer and carbon markers may be the preferred choice for target localization and patient treatment positioning verification due to less image artifacts. If MV imaging will be the sole modality for positioning verification, it may be necessary to use gold markers despite the artifacts they create on the simulation CT images.PACS number: 87

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“…While sufficient for diagnosis, radiographs do not capture the 3D distribution of periprosthetic tissues, where computed tomography (CT) remains the imaging modality of choice [7,8]. Unfortunately, CT suffers from image degradation in the vicinity of metal prostheses [9,10]. Image degradation makes the 3D classification of periprosthetic tissues a difficult taskespecially for low-contrast tissues other than cortical bone.…”

Section: Introductionmentioning

confidence: 99%

Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

2012

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Purpose Automated patient-specific image-based segmentation of tissues surrounding aseptically loose hip prostheses is desired. For this we present an automated segmentation pipeline that labels periprosthetic tissues in computed tomography (CT). The intended application of this pipeline is in pre-operative planning. Methods Individual voxels were classified based on a set of automatically extracted image features. Minimum-cost graph cuts were computed on the classification results. The graphcut step enabled us to enforce geometrical containment constraints, such as cortical bone sheathing the femur's interior. The solution's novelty lies in the combination of voxel classification with multilabel graph cuts and in the way label costs were defined to enforce containment constraints.Results The segmentation pipeline was tested on a set of twelve manually segmented clinical CT volumes. The distribution of healthy tissue and bone cement was automatically determined with sensitivities greater than 82% and pathological fibrous interface tissue with a sensitivity exceeding 73%. Specificity exceeded 96% for all tissues. Conclusions The addition of a graph-cut step improved segmentation compared to voxel classification alone. The pipeline described in this paper represents a practical approach to segmenting multitissue regions from CT.

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Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress

Abstract: The experimental MAR reconstruction algorithm significantly improved CT image quality for patients with large metal implants. However, the MAR algorithm introduced blurring artifact that reduced image quality with small metal implants.

Cited by 72 publications

References 13 publications

CT Provides Precise Size Assessment of Implanted Titanium Alloy Pedicle Screws

CT Provides Precise Size Assessment of Implanted Titanium Alloy Pedicle Screws

Determination of optimal fiducial marker across image‐guided radiation therapy (IGRT) modalities: visibility and artifact analysis of gold, carbon, and polymer fiducial markers

Voxel classification and graph cuts for automated segmentation of pathological periprosthetic hip anatomy

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