| | A Review of Factors That Affect Artifact From Metallic Hardware on Multi-Row Detector Computed TomographyArtifact arising from metallic hardware can present a major obstacle to computed tomographic imaging of bone and soft tissue and can preclude its use for answering a variety of important clinical questions. The advent of multirow detector computed tomography offers new opportunities to address the challenge of imaging in the presence of metallic hardware. This pictorial essay highlights current strategies for reducing metallic hardware artifacts and presents some illustrative clinical cases. Artifact arising from metallic hardware can degrade computed tomographic (CT) images, limiting their clinical utility. The advent of multirow detector computed tomography (MDCT) provides new opportunities to address the challenge of artifact from orthopedic or other metallic hardware.1, 2, 3 Metal artifacts appear as a streaking effect on an image, with areas of increased and decreased density obscuring adjacent structures (Fig 1). These artifacts occur because metal hardware causes beam hardening and severely attenuates the X-ray beam, resulting in incomplete projection data and subsequent reconstruction artifacts.4, 5 (Fig 2). This pictorial essay reviews current strategies for reducing metallic artifacts. Materials and Methods  Two phantoms were constructed using a ham bone and surrounding musculature, fitted with a buttress plate and screws. One phantom was constructed using titanium hardware; the other was constructed using stainless steel. Imaging was performed on a 64-row detector CT scanner (Aquillion 64; Toshiba America Medical Systems, Tustin, CA). Intrinsic factors contributing to hardware artifact were investigated by imaging both types of hardware, keeping imaging parameters constant. The effect of user-determined technical factors on artifact were examined by imaging the stainless steel phantom and varying, respectively, kVp, mAs, position of phantom within the scanner, reconstruction algorithm, acquisition thickness, reconstruction thickness, alignment of multiplanar reformat displays, image reconstruction method, and postprocessing filter. Factors Affecting Metal Artifact—Intrinsic Factors  Type of Metal Artifact is worse with stainless steel (Fig 3A) than with titanium (Fig 3B) because steel has a higher mass attenuation coefficient than titanium. Among metals currently used for orthopedic hardware and other surgical implants, titanium causes the least amount of artifact on CT images.1 Less attenuating hardware material generates less missing projection data and therefore causes fewer artifacts.6 Shape/Geometry of Metal The number of interfaces between an X-ray beam and a piece of metal can also influence the amount of artifact produced. More artifact can be expected with more complex shapes or greater numbers of hardware parts. In Fig 4A, the shape of the nail is symmetric in cross section, the attenuation of the x-ray beam is relatively uniform, and the artifacts become more pronounced in one direction. In Fig 4B, multiple screws in same cross section create more interfaces and the artifacts are dispersed across the entire image. Factors Affecting Metal Artifact—Technical Factors  kVp Contrast in an image depends on the difference in mass attenuation coefficients between different substances. Raising kVp results in smaller differentials among mass attenuation coefficients and thus lower contrast in the image. Increasing the X-ray tube potential (kVp) will increase penetration of the X-ray beam through metal4 and theoretically can reduce the metal artifact. However, use of a higher kVp results in lower contrast in the image, because the differential of mass attenuation coefficients that causes the objects to become visible becomes smaller. Lowering image contrast using higher kVp has the effect of dampening the normally great differences in mass attenuation coefficients between metal and tissue, thereby reducing artifact (Fig 5). Of note, some authors do not find additional value in using exposures greater than 120 kVp.7 It is also important to note that increasing kVp will have the effect of increasing radiation dose to the patient. mAs Higher mAs result in more photons detected. When more photons are detected, there is less noise in the image and, therefore, metallic artifacts are decreased (FIG 6, FIG 7). As with kVp, it should be noted that use of higher mAs results in higher radiation dose to the patient. Positioning Artifact from metal will vary as the hardware orientation within the scanner is varied. Change in position of the hardware within the scanner may vary the number of interfaces between an X-ray beam and the metal, thus altering the resultant artifact. For example, the orientation of metal artifact with respect to an area of interest in the body may change if the body part is rotated within the scanner (Fig 8). If possible, the body part should be positioned so the X-ray beam traverses the minimum cross-sectional length of the metal (ie, the long axis of the metal should be placed perpendicular to the plane of the gantry). Reconstruction Algorithm Bone algorithm is generally preferred for display of fine bone detail, when no hardware is present, because of its edge-enhancing effect. However, edge-enhancement algorithms can exacerbate the appearance of metal artifact.4 Soft-tissue algorithms, which are not designed to promote edge enhancement, can help to minimize hardware artifact4 (Fig 9). Acquisition Thickness In general, thin-section acquisitions help to minimize artifact by reducing partial volume averaging.8 MDCT aids in reducing artifact by allowing acquisition of very thin individual sections (eg, 0.5 mm) (Fig 10). Although thinner sections can be degraded by increased noise, in this instance, the advantage of decreased partial volume artifact generally predominates.9 Reconstruction Thickness Use of thicker reconstruction, here performed together with MIP technique, helps to minimize the effect of artifacts by better averaging of the signal within the voxel and by increasing the available signal-to-noise ratio (Fig 11). By contrast, too thick reconstructions increase blurring in the image, and image details can be lost. Multiplanar Reformat Displays Artifact generated from interaction between the X-ray beam and hardware has a 3-dimensional (3D) “shape.” Artifact will therefore be worse in some image orientations and better in others. Reformats along certain planes can help to minimize interference from the artifact over the area of interest (Fig 12). Image Reconstruction Method Use of specific image reconstruction techniques can affect the severity of metal artifact. While MDCT can help minimize artifact (specifically, by allowing acquisition of very thin sections), its wide area coverage can introduce a new kind of artifact. As the z-axis coverage gets wider with an increasing number of slices, cone beam artifacts can be introduced. The cone beam effect results in the displacement and misregistration of anatomy at the borders of high-density and low-density objects and can obscure important details10 (Fig 13). The effect is worse proportional to the increasing cone angle. Artifacts are often more pronounced for the data collected by outer detector rows than inner detector rows.8 This cone beam effect can worsen existing metal artifacts. A modified Feldkamp-based cone beam reconstruction algorithm, in this instance, a proprietary technique called True Cone Beam Tomography (Toshiba Medical Systems) is used to compensate for cone beam artifacts from MDCT. Use of 3D back projection in helical scanning (as in the Feldkamp method11) can help compensate for the divergence of the X-ray beam, consequently minimizing the cone beam artifact (Fig 14). Postprocessing Image Filters Metal artifact results in areas of raw data with low photon count. Fewer photons can traverse metal, because of its higher attenuation. This results in areas of raw data with a lower photon count, which, in turn, contribute to the effect that is perceived as metal artifact. Postprocessing image filters can help to correct raw data in areas of low photon count. In this example, a proprietary adaptive raw data filter that works in all 3 spatial dimensions (in this instance, Boost 3D, Toshiba Medical Systems) identifies portions of the raw projection data where there is a disproportionate loss in X-ray signal and applies a local 3D filter with smoothing effect to reduce image noise and streak artifacts. In areas of normal signal, no correction is applied and native image quality is preserved (Mather R, personal communication). Note that the use of such a filter can also result in subtle blurring of the image (Fig 15). Sample Cases  Clinically relevant images combining all the factors mentioned above are shown in FIG 16, FIG 17, FIG 18. Conclusions  Several conventional strategies are available for minimizing artifact from metallic hardware: use of higher kVp, higher mAs, patient positioning, and soft-tissue reconstruction algorithm. In addition, MDCT provides new opportunities for addressing artifacts from metallic hardware, including use of thinner section (0.5 mm) acquisitions; thicker reconstructions and multiplanar reformat technique; and choice of multiplanar reformat plane. Certain image reconstruction or filtering algorithms may also contribute to reduction of metallic artifacts. Acknowledgments  The authors thank Yukihiro Ogawa for the schematic illustrations used in this article; Chloe Stevenson, Jeff Hall, and Steven Hopkins for assistance in data acquisition; Rich Mather for comments in physics; Carol Wilcox, Ann Cunha, Ron Kukla, and Hisashi Tachizaki for help in preparation of this project; and Clotell Forde and Giulia Zamboni for support and assistance in completion of this article. References  1. 1Vande BB, Malghem J, Maldague B, et al. Multi-detector CT imaging in the postoperative orthopedic patient with metal hardware. Eur J Radiol. 2006;60:470–479.
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