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DOI: 10.1055/a-1460-8566
Metallic Implants in MRI – Hazards and Imaging Artifacts
Metallische Implantate im MRT – Gefahren und BildartefakteSupported by: European Regional Development Fund and the Zukunftsprogramm Wirtschaft of Schleswig-Holstein 122-09-053
Abstract
Background Magnetic resonance imaging (MRI) is an examination method for noninvasive soft tissue imaging without the use of ionizing radiation. Metallic implants, however, may pose a risk for the patient and often result in imaging artifacts. Due to the increasing number of implants, reducing these artifacts has become an important goal. In this review, we describe the risks associated with implants and provide the background on how metal-induced artifacts are formed. We review the literature on methods on how to reduce artifacts and summarize our findings.
Method The literature was searched using PubMed and the keywords “MRI metal artifact reduction”, “metallic implants” and “MRI artefacts/artifacts”.
Results and Conclusion The MRI compatibility of implants has to be evaluated individually. To reduce artifacts, two general approaches were found: a) parameter optimization in standard sequences (echo time, slice thickness, bandwidth) and b) specialized sequences, such as VAT, OMAR, WARP, SEMAC and MAVRIC. These methods reduced artifacts and improved image quality, albeit at the cost of a (sometimes significantly) prolonged scan time. New developments in accelerated imaging will likely shorten the scan time of these methods significantly, such that routine use may become feasible.
Key Points:
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Metallic implants may pose a risk for patients and often cause artifacts.
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Imaging artifacts can be reduced by parameter optimization or special sequences.
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Metal artifacts are reduced with a lower TE, smaller voxel size, larger matrix, and higher bandwidth.
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SPI, STIR, VAT, SEMAC, MAVRIC, and MAVRIC-SL are specialized MR sequences that can reduce artifacts further.
Citation Format
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Peschke E, Ulloa P, Jansen O et al. Metallic Implants in MRI – Hazards and Imaging Artifacts. Fortschr Röntgenstr 2021; 193: 1285 – 1293
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Zusammenfassung
Hintergrund Die Magnetresonanztomografie (MRT) ist eine Untersuchungsmethode für die nichtinvasive Bildgebung der Weichteile ohne die Verwendung von ionisierender Strahlung. Metallische Implantate können jedoch ein Risiko für den Patienten darstellen und führen häufig zu Bildgebungsartefakten. Aufgrund der steigenden Anzahl von Implantaten ist die Reduzierung dieser Artefakte zu einem wichtigen Ziel geworden. In dieser Übersichtsarbeit beschreiben wir die mit Implantaten und MRT verbundenen Risiken und liefern den Hintergrund, wie metallinduzierte Artefakte entstehen. Wir erläutern die gängigen Methoden zur Artefaktreduktion aus der Literatur und fassen diese zusammen.
Methoden Für diese Übersichtsarbeit wurde eine PubMed-Literatursuche mit den Stichworten „MRI metal artefact reduction“, „metallic implants“ und „MRI artefacts/artifacts“ durchgeführt.
Ergebnisse und Schlussfolgerung Die MRT-Verträglichkeit von Implantaten muss individuell bewertet werden. Zur Reduzierung von Artefakten wurden 2 generelle Ansätze gefunden: a) Parameteroptimierung in Standardsequenzen (Echozeit, Schichtdicke, Bandbreite) und b) spezialisierte Sequenzen wie VAT, OMAR, WARP, SEMAC und MAVRIC. Diese Methoden reduzierten Artefakte und verbesserten die Bildqualität, wenn auch auf Kosten einer (manchmal deutlich) verlängerten Scanzeit. Neue Entwicklungen in der beschleunigten Bildgebung werden die Scanzeit dieser Methoden wahrscheinlich deutlich verkürzen, sodass ein routinemäßiger Einsatz möglich werden könnte.
Kernaussagen:
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Metallische Implantate können ein Risiko für Patienten darstellen und verursachen oft Artefakte.
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Bildartefakte können durch Parameteroptimierung und spezielle Sequenzen reduziert werden.
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Metallartefakte werden durch kürzere TE, kleinere Voxelgröße, größere Bildmatrix und größere Bandbreite reduziert.
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SPI, STIR, VAT, SEMAC, MAVRIC und MAVRIC-SL sind spezialisierte MRT-Sequenzen, die Artefakte weiter reduzieren können.
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The recent decades have seen a dramatic development in medical technologies. Both diagnostic and treatment options have multiplied and become more accessible. Magnetic resonance imaging (MRI), for instance, has become the gold standard for noninvasive tomographic soft tissue imaging, e. g. for treatment monitoring [1].
MRI features excellent soft tissue contrast and unparalleled rich contrasts, while at the same time requiring no ionizing radiation. MRI is generally widely applicable and there are only a few contraindications, e. g., claustrophobia and some implants.
The latter point is of particular interest because more and more medical implants are being used as treatment options [2]. Examples include active devices such as pacemakers and insulin pumps, or passive ones like metallic screws, nails, stents, and joint replacements.
MRI and implants, however, are not always compatible. They may pose a threat to the patient and affect image quality. These artifacts may cause visual distortions in the MR image, signal voids, or signal pile-ups [3], thereby greatly affecting the diagnostic quality of the image. To address this issue, various approaches have been developed.
This review discusses the hazards and artifacts of implants and current approaches to reduce the latter. The goal is to provide the reader with an understanding of the topic that is sufficient for using and optimizing sequences for imaging implants.
Hazards
In general, MRI examinations are considered relatively safe for the patient and less harmful than, for example, X-rays. Hazards of routine MRI include heating, the attraction of loose ferromagnetic objects, peripheral nerve stimulation, and claustrophobia [4]. Special care has to be taken with respect to implants. Decisions as to whether or not a patient with an implant can undergo MRI have to be made on an individual basis. There are three classifications for implants with respect to MRI: MRI-safe, MRI-unsafe and MRI-conditional [5]. The information is usually provided in the implant user instructions (according to the international electrotechnical commission IEC 60 601–2-33 2010) or third-party services [6] [7].
MR-safe implants are not considered to pose a significant risk for patients undergoing MRI. Implants are categorized as MR-unsafe mostly because of the use of ferromagnetic materials. Patients with MR-unsafe implants cannot undergo MRI. MRI-conditional implants can be scanned under certain conditions (see instructions for use [8]). Still, specific handling is required, e. g. limits of the magnetic or radiofrequency field or a certain specific absorption rate must not be exceeded [5].
Hazards of implants with respect to MRI include malfunction (e. g., pacemakers) or harm by displacement, heating, or induced voltages. These effects are caused by the strong, static magnetic field B 0 ≈ 1 T, weaker but rapidly changing magnetic fields (gradients) B G ≈ 10–3 T at a frequency in the kHz range, and radiofrequency (RF) fields B 1 ≈ 10–6 T with a frequency in the 10–200 MHz range. In the following, we briefly describe the hazards caused by the different fields with a focus on implants.
Static magnetic field
Most modern MRI systems feature a magnetic field B 0 of 1.5 or 3 T. As per convention, we assume the main component of the static magnetic field to be in the z-direction along the bore (Equation 1).
The static magnetic field can attract loose ferromagnetic objects. Therefore, care has to be taken that no ferromagnetic material is brought near the MRI. In the past, fatal accidents have occurred when large metallic objects were attracted by the magnetic field and hit patients [4] [9]. This includes items of daily use in the hospital such as oxygen cylinders ([Fig. 1]), patient beds, scissors, and cleaning utensils. Accidents have also been caused on rare occasions, e. g., by respiratory equipment of firefighters.
In general, materials are divided into three different classes depending on the magnetic susceptibility (χ): diamagnetic (χ < 0), paramagnetic (χ > 0) and ferromagnetic (χ > > 1) materials. The magnetic susceptibility is a property that indicates how strongly a material will be magnetized by an external magnetic field [10]. Implants containing ferromagnetic material will exert a force, leading to displacement of the implant and thus malfunctioning or tissue injury.
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Gradient fields
When exposed to changing magnetic fields, a voltage is induced into a conductor. This voltage results in a current if the resistance is finite. For MRI, changing magnetic fluxes occur while approaching B 0 (the magnet) and by rapidly switching, spatially varying magnetic field B G (“gradients”). Gradients are applied in each Cartesian direction (Equation 2):
While entering the bore is relatively harmless, vertigo has been reported, especially at ultra-high fields of 7 T [11]. Gradients may induce electrical stimulation of nerves [12] or even heating of tissue [13].
In most cases, the unintentional nerve excitation is an uncomfortable but transient sensation for the patient (e. g., twitching or tingling). However, external devices, such as electrodes, may heat up significantly and cause fourth-degree burns [14]. To avoid burns, skin-skin contact (e. g., touching hands, thighs) or skin-metal contact has to be prevented [4]. For active implants, induced voltages could result in damaged circuits or malfunction like unwanted impulses (e. g., pacemaker) [15]. To account for the effects of switching gradients, some MR-conditional implants are specified to a maximal allowed slew rate. The slew rate of a gradient is a measure for how fast a gradient is turned on (in units of Tesla per meter per second (T/m/s)). It is calculated by the ratio of the maximum value of the gradient and the time necessary to reach this gradient amplitude.
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RF pulses
Radiofrequency (RF) pulses applied by every MRI are partially absorbed by the tissue and converted to heat. The rate, how much energy is absorbed, is given by the specific absorption rate (SAR) in units of W/kg and depends on the patient's size and body weight. To avoid heating, the allowed SAR must not be exceeded.
Conductive materials, like some implants, may reflect and absorb the RF pulses and thus increase heating [16]. Each implant is approved for a given magnetic field strength and SAR, e. g. 1.5 T and SAR < 2.0 W/kg for cardiovascular devices [17] or 1.5 T and SAR < 0.1 W/kg for deep brain stimulations [16]. However, it was realized that SAR is not the optimum measure to access implant safety. Instead, the root mean of the B 1 field (B 1+rms in units of mT) was suggested. B1+rms does not depend on the patient and is used for accessing implant safety today [18] [19].
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Imaging artifacts
Often, implants contain magnetic materials that distort the static magnetic field and shield RF pulses. This distortion is caused by the magnetic susceptibility (χ) that is much different compared to the surrounding tissue (see the previous section). This distortion results in an altered resonance frequency of the spins in the affected volume. These frequency changes may have several effects: a) the spins are not excited and/or detected, b) a fast T2* decay and c) errors in the spatial localization. To understand these effects, we need to consider the physical background of an MRI sequence.
Magnetization and resonance frequency
The nuclei (protons) of hydrogen atoms like in water (H2O) possess a nuclear spin, which gives rise to a magnetic moment. The spin is a quantum mechanical property, which we do not need to consider in much detail for the purposes of this paper. It is essential to consider, however, that the spins have two stationary states in a magnetic field, parallel (“up”) or antiparallel (“down”). One milligram of water, 1 mm3, contains approx. 1020 hydrogen atoms and thus spins and their magnetic moments.
However, most of these spins are MR-invisible and do not contribute to the MRI signal because they are almost equally in the up and down state and effectively cancel each other out (Boltzmann distribution of the Zeemann states). Only a small fraction of all spins, called polarization P, contributes to the magnetization and thus signal (Equation 3). The approximation only holds for room temperature
At room temperature, P and thus the magnitude of M increase approx. linearly with the strength of an outer magnetic field B0 . This is the reason why ever stronger magnets are being built.
Still, the polarization is very small – no more than about three parts per million (ppm) effectively contribute the signal at 1 T (or ≈ 10 ppm at 3 T). Thus, 99.999 percent of all spins are invisible at current magnetic fields. This implies that 100 000-fold enhancements are possible by increasing polarization – a fact that hyperpolarization techniques exploit [20]. Still, the small fraction of spins contributing to the signal is sufficient for MRI as we know it today.
Leaving the microscopic scale, let's consider that the spins, e. g., of 1 mm3 water, form a macroscopic magnetization vector M = [Mx My Mz]. Some aspects of this macroscopic magnetization may be compared to the needle of a hiking compass. One gram of water has a nuclear magnetization of 3.1 A/m in a magnetic field of 1 T. With B 0 = [0, 0, Bz], the magnetization becomes M = [0, 0, Mz].
When an oscillating magnetic field B 1 is applied at the right frequency ω L and perpendicular to B 0, magnetization M can be excited or flipped by an arbitrary degree α. The energy difference between the up- and downstate is dependent on the Larmor frequency ω L :
Where γ is the magnetogyric ratio, a constant of nature proportional to the magnetic moment of the element under consideration (γ(1H) = 42 MHz/T 2π), and t RF is the duration of the RF pulse. Note: ω L is directly proportional to B 0.
It is important to note that the excitation pulse has a finite bandwidth bw p – that is a frequency range, where the excitation pulse affects the magnetization. A higher bandwidth corresponds to a larger frequency range and therefore excites spins across a broader range of Larmor frequencies. The bandwidth depends on the duration and shape of the pulse.
After the excitation pulse, the magnetization vectors M precess about the z-axis. Any component of the magnetization vector in the xy-plane, [Mx My], induces an alternating magnetic flux and thus a current in a nearby conductor (e. g., a coil): this is the MR signal.
Similar to the excitation, the detection process has a bandwidth bw d, too, which depends on the rate of the discrete sampling of the continuous MR signal
where td is the dwell time and depicts the interval between two digitized samples. Shorter sampling intervals result in a higher bandwidth but reduce the signal-to-noise ratio (SNR) because less time was used to collect the signal. Different vendors indicate the bandwidth differently, either the total bandwidth in Hz or the bandwidth divided by the number of steps for the frequency encoding in bandwidth in Hz/Px.
After the excitation, the longitudinal or z-component of the magnetization Mz returns to its equilibrium value, M0, while Mxy decays to zero. Both effects can be described with exponential functions with the constant T1 for longitudinal and T2, T2* and T2i for transverse relaxation (Equation 7). Once Mxy is zero, no MR signal is recorded (while Mz may not yet be recovered). There are two fundamental effects contributing to the transverse relaxation: the effect of static B 0 inhomogeneities, described by an exponential decay with T2i, and other components, described by T2. While the T2 decay is irreversible, loss by T2i decay can be recovered by refocusing the magnetization in spin echoes.
Spin echoes are formed by flipping the transverse magnetization around × or y. This way, the effect of the inhomogeneities is reversed.
For spatial encoding, i. e., imaging, additional magnetic fields, B G, are applied whose strengths vary with the position in space:
Gx, Gy and Gz are the strength of the gradient fields in T/m and x, y and z are the spatial positions in m.
B G is applied at different points in time: during the pulse (“slice selection”), between excitation and detection (“phase encoding”), or during readout (“readout encoding”).
It is essential to realize that the magnetic field's linear variation (induced by B G) causes a spatial dependency of the Larmor frequency. As a result, the Larmor frequency becomes a function of the position, and this relation of spatial location and resonance frequency allows the reconstruction of images. Using this effect for imaging was awarded the Nobel Prize in 2003.
It should be noted that when we talk about the strength of an MRI device, we refer to the magnetic flux density, B, in T and not to the magnetic field strength, H, in A/m. The permeability, a proportionality factor, connects B and H.
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Impact of implants
As mentioned above, implants are either paramagnetic, diamagnetic, or ferromagnetic, a classification depending on their magnetic susceptibility χ. Like implant materials, each tissue in the body also has a different magnetic susceptibility ([Table 1]).
Material brought into a magnetic field may enhance, weaken, or not affect the magnetic field locally ([Fig. 2]).
Diamagnetic material, such as biological tissue and calcium, will weaken the magnetic field, while paramagnetic and ferromagnetic material, like gadolinium and iron, will enhance the magnetic field locally. The susceptibilities of different tissues are similar enough to have little impact on conventional MRI, although specialized sequences generate contrast based on different susceptibilities (susceptibility-weighted imaging, SWI) [21]. Problems occur in the presence of metal implants or at the interface between air and tissue (e. g., nasal cavities, intestines).
For implants, due to the different magnetic susceptibility compared to surrounding tissue, the magnetic field is distorted, causing changes in the Larmor frequency of nearby spins. This may have one or all of the following effects:
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Insufficient excitation because ω L is not within bw p
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Low signal detection because ω L is outside of bw d
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Low signal detection because the transverse magnetization decays very fast (large T2', dephasing)
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Misregistration of spins because ω L is different than expected ([Fig. 3]).
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Failure of frequency selective pulses.
All of this will lead to signal loss or signal pile-up and cause spatial distortions in the measured slice.
In addition to image distortion, failure of spectral fat suppression often occurs in tissue near metal implants for the same reason (distortions of the magnetic field and thus Larmor frequencies). Spectral fat suppression methods use the fact that the Larmor frequencies (chemical shift) of water and fat are different by approximately 3.5 ppm (e. g., 220 Hz for 1.5 T). A narrow (low bw p) pulse is applied at the frequency of fat to saturate its magnetization to suppress the fat signal. In the proximity of metal implants, the field and thus frequencies are distorted (e. g., by 30–80 Hz). As a result, fat is not excited by the narrow saturation pulses. Similar effects occur in other techniques, such as Dixon-type fat water imaging [22] ([Fig. 4]).
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Reduction of imaging artifacts
Several approaches were suggested to reduce implant-related artifacts. To some extent, standard sequences can be used with some parameter optimization. Additionally, special MRI sequences were developed for artifact reduction. In general, artifacts are dependent on the field strength of the MRI device, the used sequence, the chosen parameters, and the properties of the implant itself, such as orientation and type of material.
General considerations
Lower magnetic field strengths exhibit less metal-induced artifacts than higher field strengths. The field homogeneity (also without an implant) is higher in lower magnetic fields. Thus, lower field strengths were recommended for imaging implants [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34].
As expected, the material's susceptibility was found to affect the artifacts: larger susceptibility differences caused larger distortions.
The orientation of the implant with respect to B 0 may play a role, too [35]. It appears beneficial to position the long implant axis parallel to B 0, although it must not act as an antenna as heating may occur.
The phase encoding direction is less affected by metal artifacts. Thus, it may be advantageous to switch the phase and frequency encoding direction to improve the visibility of the nearby tissue. If phase oversampling is needed to avoid a folding artifact, the measurement time increases [22] [25].
Some sequence types are more robust with respect to distortions than others. Generally, spin echo (SE) sequences are benign because the echo can be acquired fully, even if T2* is short (compared to gradient echo sequences, where the signal may decay with T2* during spatial encoding before the acquisition is started). As a result, some of the inhomogeneities can be refocused with spin echo sequences. Although spin-echo-based sequences have benefits, some sequences like phase contrast imaging or fast imaging methods often use gradient echoes. Here, it is advantageous to reduce the time between excitation and image acquisition, TE [28] [29] [32] [36] [37]. In the extreme, ultra-short or zero-TE sequences can reduce artifacts and even image hard tissues [38] [39].
In the presence of field inhomogeneities, the spins precess with a frequency offset of Δf compared to the non-distorted case. The spatial distortion depends on the frequency offset and the slice thickness and negatively on the excitation bandwidth (bwp) [22]. Besides this, the spatial distortion also depends on the receiver bandwidth (bwd). A higher receiver bandwidth reduces the spatial distortion ([Fig. 5]) as well as an increasing slice selection gradient, which results in a decreased slice thickness. Additionally, increasing the matrix size or reducing the voxel size is helpful for reducing metal artifacts. However, a drawback of those reduction techniques is an increased scan time and reduced signal-to-noise ratio (SNR) [24] [25] [34] [36] [37] [40] [41]. A higher slice selection gradient ensures that each slice is encoded with a higher frequency range. As a result, spins with higher or lower Larmor frequencies (e. g., caused by field inhomogeneities) are still excited in the correct slice and contribute to the signal. This especially reduces signal loss. Again, higher bandwidth reduces SNR [23] [24] [25] [32] [36] [40] [41] [42] [43] [44]. For fat suppression near metal implants, spectral fat suppression sequences should be avoided. Instead, T1-based suppression techniques, such as short tau inversion recovery (STIR), are more robust. STIR exploits the fact that the T1-relaxation time of fat is shorter than that of tissue and can be nulled with an inversion pulse. STIR is beneficial compared to the spectral fat suppression near implants but results in a lower SNR. Additionally, a second RF pulse is necessary, which increases the specific SAR.
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Special sequences with high robustness against spatial distortions
One problem regarding imaging near metal implants is the failure of slice selection and readout encoding. For the acquisition of an MR image without slice selection and readout encoding, single point imaging (SPI) can be used. In SPI sequences, only phase encoding is applied, and only one point in k-space is acquired for each excitation. This method makes it possible to minimize the time between excitation and acquisition but leads to very long scan times of 40 minutes or longer which are rarely practical for in vivo use [45].
To reduce in-plane distortions, view-angle tilting (VAT) was suggested in conjunction with spin echo sequences. VAT exploits the fact that the distortion is dependent on the gradient strength of the slice selection gradient. To compensate the off-resonance effects of the slice selection gradient, an additional gradient is used during the readout, equivalent to the one used for slice selection. The additional gradient results in a tilting of the readout direction ([Fig. 6]). The readout direction’s tilt reduces the in-plane artifacts, but with a drawback of blurred edges [40] [42] [46] [47].
A specific optimization of parameters (high bandwidth, thin slices) was initially introduced by Olsen et al. as a metal artifact reduction sequence (MARS) [48]. More recently, modified spin echo sequences were combined with a view-angle tilting technique [49].
VAT is only able to reduce in-plane distortion. Slice Encoding for Metal Artifact Correction (SEMAC) was suggested to reduce through-plane distortions, which can be applied additionally to VAT. SEMAC is based on a conventional 2 D spin-echo sequence. It utilizes an additional phase-encoding step in the slice-selection direction, which reduces slice distortions. Knowledge of slice distortion can be used in the postprocessing step, where each slice is coded and reconstructed individually. The number of slice encoding steps is dependent on the extent of the geometric distortion. Like the other methods mentioned, this sequence's drawback is the increased scan time of around 10 minutes [37] [43] [50]. By optimizing for the particular implant, the scan time can be reduced to around 5 minutes [51].
Another sequence suggested for reducing through-plane distortions was Multi-Acquisition Variable Resonance Image Combination (MAVRIC), based on a 3D fast spin echo sequence. Here, multiple frequency-selective excitations are used instead of a single excitation pulse. All excited slabs are then analyzed in the postprocessing step to reduce artifacts. Like SEMAC, MAVRIC increases the scan time to around 20–25 min [22] [37] [52] [53].
A combination of SEMAC and MAVRIC was introduced by Koch et al. [53]. MAVRIC SL uses the selective excitation pulse like SEMAC, but the pulse profile is the same as for MAVRIC [24].
It is a common phenomenon that manufacturers give different names to relatively similar sequences. For example, optimized spin echo sequences with VAT are called O-MAR [54] (Philips) and WARP [55] (Siemens), or O-MAR XD [56] and Advanced WARP [57] with the addition of SEMAC. Readers are advised to consult available online databases to identify the appropriate sequence for their system.
It should not go unmentioned that attempts were recently made to reduce artifacts using artificial intelligence (AI) [58] [59].
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Summary
Besides the risk of injury, implants may severely influence MR image quality depending on the susceptibility of the implant. Careful selection of sequence parameters or the use of specialized solutions alleviates the issue.
If metal-induced artifacts occur, it may help to consider the following:
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Lower magnetic field strength
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Shorter TE
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Revert to spin echo sequences
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Thinner slices
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Smaller voxels
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Larger matrix size
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Higher excitation and detection bandwidth
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Switching of slice, phase, and readout direction
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Insufficient fat suppression: switch from spectral techniques to inversion techniques (e. g., STIR)
The following sequences or modules also offer some benefits:
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Single point imaging (SPI)
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UTE, ZTE
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Metal artifact reduction sequence (MARS)
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View angle tilting (VAT)
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Slice encoding for metal artifact correction (SEMAC)
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Multi-acquisition variable resonance image combination (MAVRIC)
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MAVRIC-SL
Overall, magnetic materials have always caused significant artifacts on MRI and continue doing so on modern machines. Various methods have been introduced to alleviate this issue but often come at the cost of prolonged scan times. Acceleration techniques may make these methods applicable for the clinical routine. Metal artifact reduction is an ongoing and highly relevant field of research. Undoubtedly, the future will bring more developments as more and more implants are being used, and it will become ever more important to diagnose the surrounding issue, e. g., for inflammation.
Funding
Deutsche Forschungsgemeinschaft (GRK 2154); European Regional Development Fund and the Zukunftsprogramm Wirtschaft of Schleswig-Holstein (122-09-053)
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Conflict of Interest
The authors declare that they have no conflict of interest.
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- 30 Thompson RM, Fowler E, Culo B. et al MRI safety and imaging artifacts evaluated for a cannulated screw used for guided growth surgery. Magnetic Resonance Imaging 2020; 66: 219-225 DOI: 10.1016/j.mri.2019.11.005.
- 31 Ganapathi M, Joseph G, Savage R. et al MRI Susceptibility Artefacts Related to Scaphoid Screws: the Effect of Screw Type, Screw Orientation and Imaging Parameters. Journal of Hand Surgery 2002; 27: 165-170 DOI: 10.1054/JHSB.2001.0717.
- 32 Lee MJ, Kim S, Lee SA. et al Overcoming Artifacts from Metallic Orthopedic Implants at High-Field-Strength MR Imaging and Multi-detector CT. RadioGraphics 2007; 27: 791-803 DOI: 10.1148/rg.273065087.
- 33 Chiba Y, Murakami H, Sasaki M. et al Quantification of metal‐induced susceptibility artifacts associated with ultrahigh‐field magnetic resonance imaging of spinal implants. JOR Spine 2019; 2 DOI: 10.1002/jsp2.1064.
- 34 Sutter R, Dietrich T. Reduktion von Metallartefakten in der muskuloskelettalen Bildgebung. Radiologie up2date 2016; 16: 127-144 DOI: 10.1055/s-0042-105421.
- 35 Ladd ME, Erhart P, Debatin JF. et al Biopsy needle susceptibility artifacts. Magnetic Resonance in Medicine 1996; 36: 646-651 DOI: 10.1002/mrm.1910360423.
- 36 Faulkner W. Managing Metallic Artifacts in MRI. Im Internet: http://www.medtronic.me/content/dam/medtronic-com/ca-en/hcp/documents/MRI/Managing%20Metallic%20Artifact%20White%20Paper%20201604693EC.pdf
- 37 Talbot BS, Weinberg EP. MR Imaging with Metal-suppression Sequences for Evaluation of Total Joint Arthroplasty. RadioGraphics 2016; 36: 209-225 DOI: 10.1148/rg.2016150075.
- 38 Stumpf K, van Gorp S, Strom A. et al Multi-sequence comparison of metal artifact reduction capabilities for dental materials. In: Proceedings of the Joint Annual Meeting of ISMRM and ESMRMB. Paris 2018
- 39 Hövener JB, Zwick S, Leupold J. et al Dental MRI: imaging of soft and solid components without ionizing radiation. J Magn Reson Imaging 2012; 36: 841-846 DOI: 10.1002/jmri.23712.
- 40 Koch KM, Hargreaves BA, Pauly KB. et al Magnetic resonance imaging near metal implants. J Magn Reson Imaging 2010; 32: 773-787 DOI: 10.1002/jmri.22313.
- 41 Jiang M, He C, Feng J. et al Magnetic resonance imaging parameter optimizations for diagnosis of periprosthetic infection and tumor recurrence in artificial joint replacement patients. Sci Rep 2016; 6: 36995 DOI: 10.1038/srep36995.
- 42 Viano AM, Gronemeyer SA, Haliloglu M. et al Improved MR imaging for patients with metallic implants. Magnetic Resonance Imaging 2000; 18: 287-295 DOI: 10.1016/S0730-725X(99)00135-6.
- 43 Kumar NM, de Cesar Netto C, Schon LC. et al Metal Artifact Reduction Magnetic Resonance Imaging Around Arthroplasty Implants: The Negative Effect of Long Echo Trains on the Implant-Related Artifact. Investigative Radiology 2017; 52: 310-316 DOI: 10.1097/RLI.0000000000000350.
- 44 de Cesar Netto C, Fonseca LF, Fritz B. et al Metal artifact reduction MRI of total ankle arthroplasty implants. Eur Radiol 2018; 28: 2216-2227 DOI: 10.1007/s00330-017-5153-9.
- 45 Ramos-Cabrer P, van Duynhoven JPM, Van der Toorn A. et al MRI of hip prostheses using single-point methods: In vitro studies towards the artifact-free imaging of individuals with metal implants. Magnetic Resonance Imaging 2004; 22: 1097-1103 DOI: 10.1016/j.mri.2004.01.061.
- 46 Cho ZH, Kim DJ, Kim YK. Total inhomogeneity correction including chemical shifts and susceptibility by view angle tilting: Total inhomogeneity correction including chemical shift. Med Phys 1988; 15: 7-11 DOI: 10.1118/1.596162.
- 47 Reichert M, Ai T, Morelli JN. et al Metal artefact reduction in MRI at both 1.5 and 3.0 T using slice encoding for metal artefact correction and view angle tilting. BJR 2015; 88: 20140601 DOI: 10.1259/bjr.20140601.
- 48 Olsen RV, Munk PL, Lee MJ. et al Metal Artifact Reduction Sequence: Early Clinical Applications. RadioGraphics 2000; 20: 699-712 DOI: 10.1148/radiographics.20.3.g00ma10699.
- 49 Toms AP, Smith-Bateman C, Malcolm PN. et al Optimization of metal artefact reduction (MAR) sequences for MRI of total hip prostheses. Clinical Radiology 2010; 65: 447-452 DOI: 10.1016/j.crad.2009.12.014.
- 50 Lu W, Pauly KB, Gold GE. et al SEMAC: Slice encoding for metal artifact correction in MRI. Magn Reson Med 2009; 62: 66-76 DOI: 10.1002/mrm.21967.
- 51 Deligianni X, Bieri O, Elke R. et al Optimization of Scan Time in MRI for Total Hip Prostheses: SEMAC Tailoring for Prosthetic Implants Containing Different Types of Metals. Rofo 2015; 187: 1116-1122 DOI: 10.1055/s-0041-104893.
- 52 Koch KM, Lorbiecki JE, Hinks RS. et al A multispectral three-dimensional acquisition technique for imaging near metal implants. Magn Reson Med 2009; 61: 381-390 DOI: 10.1002/mrm.21856.
- 53 Koch KM, Brau AC, Chen W. et al Imaging near metal with a MAVRIC-SEMAC hybrid. Magnetic Resonance in Medicine 2011; 65: 71-82 DOI: 10.1002/mrm.22523.
- 54 O-MAR | Klinische MR-Anwendung | Philips Healthcare. Philips. Im Internet (Stand: 22.07.2020): https://www.philips.de/healthcare/product/HCNMRB815/O-MAR-MR-Software
- 55 WARP. Im Internet (Stand: 22.07.2020): https://www.siemens-healthineers.com/de/medical-imaging/magnetic-resonance-imaging/options-and-upgrades/clinical-applications/syngo-warp/features
- 56 O-MAR XD | Klinische MR-Anwendung | Philips Healthcare. Philips. Im Internet (Stand: 22.07.2020): https://www.philips.de/healthcare/product/HCNMRB816A/O-MAR-XD-MR-Software
- 57 Advanced WARP. Im Internet (Stand: 22.07.2020): https://www.siemens-healthineers.com/de/medical-imaging/magnetic-resonance-imaging/options-and-upgrades/clinical-applications/advanced-warp/features
- 58 Duong STM, Phung SL, Bouzerdoum A. et al An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images. Magnetic Resonance Imaging 2020; 71: 1-10 DOI: 10.1016/j.mri.2020.04.004.
- 59 Kwon K, Kim D, Kim B. et al Unsupervised learning of a deep neural network for metal artifact correction using dual-polarity readout gradients. Magnetic Resonance in Medicine 2020; 83: 124-138 DOI: 10.1002/mrm.27917.
Publication History
Received: 01 September 2020
Accepted: 17 March 2021
Article published online:
12 May 2021
© 2021. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
-
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- 29 Tartaglino LM, Flanders AE, Vinitski S. et al Metallic artifacts on MR images of the postoperative spine: reduction with fast spin-echo techniques. Radiology 1994; 190: 565-569 DOI: 10.1148/radiology.190.2.8284417.
- 30 Thompson RM, Fowler E, Culo B. et al MRI safety and imaging artifacts evaluated for a cannulated screw used for guided growth surgery. Magnetic Resonance Imaging 2020; 66: 219-225 DOI: 10.1016/j.mri.2019.11.005.
- 31 Ganapathi M, Joseph G, Savage R. et al MRI Susceptibility Artefacts Related to Scaphoid Screws: the Effect of Screw Type, Screw Orientation and Imaging Parameters. Journal of Hand Surgery 2002; 27: 165-170 DOI: 10.1054/JHSB.2001.0717.
- 32 Lee MJ, Kim S, Lee SA. et al Overcoming Artifacts from Metallic Orthopedic Implants at High-Field-Strength MR Imaging and Multi-detector CT. RadioGraphics 2007; 27: 791-803 DOI: 10.1148/rg.273065087.
- 33 Chiba Y, Murakami H, Sasaki M. et al Quantification of metal‐induced susceptibility artifacts associated with ultrahigh‐field magnetic resonance imaging of spinal implants. JOR Spine 2019; 2 DOI: 10.1002/jsp2.1064.
- 34 Sutter R, Dietrich T. Reduktion von Metallartefakten in der muskuloskelettalen Bildgebung. Radiologie up2date 2016; 16: 127-144 DOI: 10.1055/s-0042-105421.
- 35 Ladd ME, Erhart P, Debatin JF. et al Biopsy needle susceptibility artifacts. Magnetic Resonance in Medicine 1996; 36: 646-651 DOI: 10.1002/mrm.1910360423.
- 36 Faulkner W. Managing Metallic Artifacts in MRI. Im Internet: http://www.medtronic.me/content/dam/medtronic-com/ca-en/hcp/documents/MRI/Managing%20Metallic%20Artifact%20White%20Paper%20201604693EC.pdf
- 37 Talbot BS, Weinberg EP. MR Imaging with Metal-suppression Sequences for Evaluation of Total Joint Arthroplasty. RadioGraphics 2016; 36: 209-225 DOI: 10.1148/rg.2016150075.
- 38 Stumpf K, van Gorp S, Strom A. et al Multi-sequence comparison of metal artifact reduction capabilities for dental materials. In: Proceedings of the Joint Annual Meeting of ISMRM and ESMRMB. Paris 2018
- 39 Hövener JB, Zwick S, Leupold J. et al Dental MRI: imaging of soft and solid components without ionizing radiation. J Magn Reson Imaging 2012; 36: 841-846 DOI: 10.1002/jmri.23712.
- 40 Koch KM, Hargreaves BA, Pauly KB. et al Magnetic resonance imaging near metal implants. J Magn Reson Imaging 2010; 32: 773-787 DOI: 10.1002/jmri.22313.
- 41 Jiang M, He C, Feng J. et al Magnetic resonance imaging parameter optimizations for diagnosis of periprosthetic infection and tumor recurrence in artificial joint replacement patients. Sci Rep 2016; 6: 36995 DOI: 10.1038/srep36995.
- 42 Viano AM, Gronemeyer SA, Haliloglu M. et al Improved MR imaging for patients with metallic implants. Magnetic Resonance Imaging 2000; 18: 287-295 DOI: 10.1016/S0730-725X(99)00135-6.
- 43 Kumar NM, de Cesar Netto C, Schon LC. et al Metal Artifact Reduction Magnetic Resonance Imaging Around Arthroplasty Implants: The Negative Effect of Long Echo Trains on the Implant-Related Artifact. Investigative Radiology 2017; 52: 310-316 DOI: 10.1097/RLI.0000000000000350.
- 44 de Cesar Netto C, Fonseca LF, Fritz B. et al Metal artifact reduction MRI of total ankle arthroplasty implants. Eur Radiol 2018; 28: 2216-2227 DOI: 10.1007/s00330-017-5153-9.
- 45 Ramos-Cabrer P, van Duynhoven JPM, Van der Toorn A. et al MRI of hip prostheses using single-point methods: In vitro studies towards the artifact-free imaging of individuals with metal implants. Magnetic Resonance Imaging 2004; 22: 1097-1103 DOI: 10.1016/j.mri.2004.01.061.
- 46 Cho ZH, Kim DJ, Kim YK. Total inhomogeneity correction including chemical shifts and susceptibility by view angle tilting: Total inhomogeneity correction including chemical shift. Med Phys 1988; 15: 7-11 DOI: 10.1118/1.596162.
- 47 Reichert M, Ai T, Morelli JN. et al Metal artefact reduction in MRI at both 1.5 and 3.0 T using slice encoding for metal artefact correction and view angle tilting. BJR 2015; 88: 20140601 DOI: 10.1259/bjr.20140601.
- 48 Olsen RV, Munk PL, Lee MJ. et al Metal Artifact Reduction Sequence: Early Clinical Applications. RadioGraphics 2000; 20: 699-712 DOI: 10.1148/radiographics.20.3.g00ma10699.
- 49 Toms AP, Smith-Bateman C, Malcolm PN. et al Optimization of metal artefact reduction (MAR) sequences for MRI of total hip prostheses. Clinical Radiology 2010; 65: 447-452 DOI: 10.1016/j.crad.2009.12.014.
- 50 Lu W, Pauly KB, Gold GE. et al SEMAC: Slice encoding for metal artifact correction in MRI. Magn Reson Med 2009; 62: 66-76 DOI: 10.1002/mrm.21967.
- 51 Deligianni X, Bieri O, Elke R. et al Optimization of Scan Time in MRI for Total Hip Prostheses: SEMAC Tailoring for Prosthetic Implants Containing Different Types of Metals. Rofo 2015; 187: 1116-1122 DOI: 10.1055/s-0041-104893.
- 52 Koch KM, Lorbiecki JE, Hinks RS. et al A multispectral three-dimensional acquisition technique for imaging near metal implants. Magn Reson Med 2009; 61: 381-390 DOI: 10.1002/mrm.21856.
- 53 Koch KM, Brau AC, Chen W. et al Imaging near metal with a MAVRIC-SEMAC hybrid. Magnetic Resonance in Medicine 2011; 65: 71-82 DOI: 10.1002/mrm.22523.
- 54 O-MAR | Klinische MR-Anwendung | Philips Healthcare. Philips. Im Internet (Stand: 22.07.2020): https://www.philips.de/healthcare/product/HCNMRB815/O-MAR-MR-Software
- 55 WARP. Im Internet (Stand: 22.07.2020): https://www.siemens-healthineers.com/de/medical-imaging/magnetic-resonance-imaging/options-and-upgrades/clinical-applications/syngo-warp/features
- 56 O-MAR XD | Klinische MR-Anwendung | Philips Healthcare. Philips. Im Internet (Stand: 22.07.2020): https://www.philips.de/healthcare/product/HCNMRB816A/O-MAR-XD-MR-Software
- 57 Advanced WARP. Im Internet (Stand: 22.07.2020): https://www.siemens-healthineers.com/de/medical-imaging/magnetic-resonance-imaging/options-and-upgrades/clinical-applications/advanced-warp/features
- 58 Duong STM, Phung SL, Bouzerdoum A. et al An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images. Magnetic Resonance Imaging 2020; 71: 1-10 DOI: 10.1016/j.mri.2020.04.004.
- 59 Kwon K, Kim D, Kim B. et al Unsupervised learning of a deep neural network for metal artifact correction using dual-polarity readout gradients. Magnetic Resonance in Medicine 2020; 83: 124-138 DOI: 10.1002/mrm.27917.