Cardiovascular magnetic resonance artefacts
© Ferreira et al.; licensee BioMed Central Ltd. 2013
Received: 17 July 2012
Accepted: 17 April 2013
Published: 22 May 2013
The multitude of applications offered by CMR make it an increasing popular modality to study the heart and the surrounding vessels. Nevertheless the anatomical complexity of the chest, together with cardiac and respiratory motion, and the fast flowing blood, present many challenges which can possibly translate into imaging artefacts. The literature is wide in terms of papers describing specific MR artefacts in great technical detail. In this review we attempt to summarise, in a language accessible to a clinical readership, some of the most common artefacts found in CMR applications. It begins with an introduction of the most common pulse sequences, and imaging techniques, followed by a brief section on typical cardiovascular applications. This leads to the main section on common CMR artefacts with examples, a short description of the mechanisms behind them, and possible solutions.
There are unique motion and other issues involved in Cardiovascular Magnetic Resonance (CMR) that can lead to artefacts which can obscure or easily be misinterpreted as pathology. An artefact can be defined as something that is visible in an image but it is artificial, and is often detrimental to diagnosis. For this reason it is important to have an understanding of the physical principles behind the formation of such artefacts so that they can be identified and possibly avoided.
A large range of different sequences are used for the different applications in CMR and the majority of these are still being developed to improve their accuracy and reliability. It is therefore impossible to be completely comprehensive covering all artefacts for all sequences, thus the examples of artefact have been restricted to one or two of the most problematic or common. The artefacts are also specific to cardiovascular imaging, and more general artefacts related to hardware are omitted.
This article, that is designed for a clinical readership, follows previous publications on the subject [1–3]. There is initially a brief description of the most common sequences and preparation pulses used, along with imaging techniques and typical cardiovascular applications. The main section follows, with common examples of artefacts, accompanied with a small description of the mechanisms behind them and possible solutions and trade-offs. At this point it is quite possible that some readers will not require the introductory sections describing cardiovascular pulse sequences and applications and would happily move directly to the main sections describing artefacts. If this is the case then please jump to section Cardiovascular Magnetic Resonance Artefacts. Also, alternatives to these sections are available elsewhere such as the excellent physics articles from Ridgway and Biglands in JCMR 2010 and 2012 [4, 5].
Cardiovascular pulse sequences
Generally spin-echo sequences offer a greater flexibility in obtaining different contrasts (T1-weighted, T2-weighted, or proton-density weighted) depending on the choice of TE and TR (Time of Repetition). The main disadvantages of spin-echo sequences are their limited temporal-resolution and sensitivity to motion and flow.
In a bSSFP sequence the transverse magnetisation is not spoiled but refocused by gradients, contributing to the next echo. The word balanced in balanced-SSFP means that the net area in each gradient axis is null within a TR (Figure 3b). bSSFP sequences can use higher flip-angles and shorter TRs than GRE, increasing SNR and decreasing acquisition time but at a cost of an increase in sensitivity to field inhomogeneity and frequency-offsets.
Many different cardiovascular imaging sequences are combined with preparation pulses. These pre-pulses precede the host-sequence and can be used to suppress specific tissues such as blood or fat, enhance contrast weighting and add tags to the myocardium for example. Some of the most common preparation pulses are now described.
Similar to inversion pulses, saturation pulses can also be used to modify contrast in an image (Figure 5b). Instead of inverting the magnetisation, a saturation pulse rotates the magnetisation into the transverse x-y plane where it is spoiled by a gradient, resulting in zero net magnetisation.
Following both inversion and saturation pulses, the longitudinal magnetisation starts to recover towards equilibrium, and image acquisition with one of the host sequences occurs during this recovery. These techniques are therefore called inversion-recovery or saturation-recovery preparation pulses. Different tissues have different T1 values and therefore different available signal during recovery; these recovery techniques allow image contrast between different tissues to be manipulated. It should be noted however that the final contrast is not just dependent on the preparation pulses but also on the host sequence.
Optimal saturation recovery preparation is generally achieved by the use of special RF pulse designs (composite , B1 Independent Rotation (BIR) ). Contrast manipulation is somewhat more limited than with inversion recovery pulses, although there are shorter recovery times from saturation. A major advantage of saturation recovery is that it does not require near full longitudinal recovery before the next saturation is applied, unlike inversion recovery, because the magnetisation is always reset to zero by the saturation pulse; therefore offering insensitivity to arrhythmias. These pulses are commonly used in first-pass perfusion imaging to enhance the contrast agent signal.
Saturation pulses can be also used to suppress unwanted tissues. This suppression can be either spatially-selective or spectrally-selective or both, reducing the signal from defined spatial regions in the body, or from defined nuclei with specific chemical shifts respectively. Saturation bands can be used for example to suppress aliasing of tissue outside the field of view or signal ghosting from flowing blood, while spectrally-selective saturation pulses are commonly used to null the signal of fat, commonly known as fat-saturation pulses. These types of saturation pulses differ from a saturation recovery preparation in the sense that the main objective is to null signal instead of manipulating contrast with spin-relaxation; thus this type of preparation is commonly followed by a spoiler-gradient in order to destroy any transverse magnetisation, and followed immediately by the excitation pulse in the host sequence, with no recovery time.
Another form of preparation pulse used in CMR is the tagging pulse. This pulse introduces spatial tags, i.e. spatially periodic signal intensity modulation in the image and is commonly used to evaluate tissue deformation, such as myocardial strain throughout the cardiac cycle. Tagging pulses are commonly applied immediately after each R-wave followed by a segmented-image acquisition of multiple frames during the heart-cycle, to enable reconstruction of a cine. In a popular tagging preparation technique known as SPAMM , non-selective pulses are interleaved with a tagging gradient and followed by a spoiler gradient (Figure 5c). This preparation introduces a sinusoidal modulation in Mz along the tag gradient direction, represented by Gx in the Figure. This technique is usually applied separately in both in-plane spatial encoding directions and then combined in order to create a perpendicular grid. The contrast of the tag lines can be improved by summing two sets of images with complementary tagging pulses, in a technique called CSPAMM .
The data collected by the scanner needs to be converted to the final image. The acquired raw-data domain is commonly known as k-space and is mathematically related to the final image by a Fourier transformation. Thus each data value in k-space contains information about potentially any pixel in the final image, although a basic relationship can be considered between k-space and the image-space. The central region of k-space contains information about low spatial frequencies, i.e. mainly the contrast in the image, while the outer regions of k-space contain information about the high spatial frequencies, i.e. object-boundaries and edges . This relationship between k-space and image-space allows the manipulation of artefacts and image contrast by modifying the way k-space is sampled. Many different k-space sampling trajectories have been proposed and used for cardiac imaging. In this section a brief introduction is made to some of these techniques, while associated artefacts are presented later on. Most of these techniques are simply a method of sampling k-space and therefore can be used with different sequences and techniques.
Still in the realm of Cartesian trajectories we have EPI readouts, where more than one line is acquired in a gradient-echo train (Figure 6e). EPI uses bipolar readout gradients (Figure 4), which continuously produce echoes, making it a fast k-space sampling method. In its most common form EPI, although being Cartesian requires extra image processing steps due to half the echoes (odd echoes) being acquired in k-space with the opposite direction to even echoes. Although highly efficient, EPI is also very sensitive to many different artefacts, especially in its single-shot form and for this reason hybrid-epi is popular where shorter EPI trains are commonly acquired with only a few echoes or lines, instead of the whole of k-space.
Radial sampling was the first k-space sampling trajectory to be used in MRI with a backprojection image reconstruction , analogous to Computed Tomography. In a radial trajectory the k-space is sampled with radial spokes that pass through the centre of k-space (Figure 7b). Image reconstruction in radial sampling can either be with a back projection algorithm or, most commonly, gridded into a Cartesian matrix which is then reconstructed as Cartesian data. One potential advantage of a radial acquisition is the shorter minimum TE as there is no phase-encoding required. To satisfy the Nyquist sampling requirements, the number of acquired radial k-space lines must be greater than with Cartesian sampling by a factor of π/2; although occasionally mild undersampling may not compromise the diagnostic quality of the image, such as in contrast-enhanced vascular imaging. Variations of radial acquisition exist such as Linogram and PROPELLER. The explanation of these methods falls outside the scope of this article, but the interested reader is referred to the respective bibliographical references [12, 13].
Similar to Cartesian trajectories, non-Cartesian trajectories can also be modified in order to change image contrast by changing TE and for example T2* sensitivity. In both radial and spiral acquisitions, sampling can start either at the centre of k-space or at the edge, resulting in a short or longer TE respectively.
Non-Cartesian methods suffer a definite disadvantage in their sensitivity to even a few microseconds of synchronisation errors among the gradient waveform axes and also of these with data sampling. Cartesian scanning (except EPI) is much more tolerant of such errors.
Parallel imaging is another method of accelerating image acquisition without sacrificing spatial-resolution . In parallel imaging the spacing in k-space between acquired phase-encode lines is bigger than that required by the Nyquist sampling requirement for the phase-encoded FOV. This increase in line spacing is given by the acceleration factor R, for example an R=3 means that only one in every three lines is acquired. The result is a FOV reduced by a factor of 3, and aliasing or wrapping of the imaged object into the opposite edge of the image, if bigger than the reduced FOV. Parallel imaging requires phased-array coils, since it uses the coils’ individual spatial sensitivities (information about the spatial signal response profile of each coil) to either unwrap the object after image reconstruction or fill the missing k-space lines before the image reconstruction. Several parallel imaging methods are available with the most common being GRAPPA and SENSE [16, 17].
Either SENSE or GRAPPA can also be combined with another form of temporal undersampling (temporal filtering technique) known as UNFOLD , these are then usually known as TSENSE  and TGRAPPA  respectively. Combining UNFOLD with parallel imaging techniques improves coil sensitivity profile estimation.
In this section we describe the most common cardiovascular imaging applications to provide a context to the following section on artefacts.
For cardiovascular morphology, a double-inversion RF pulse preparation is commonly added to a turbo spin-echo sequence, removing the blood signal and providing a good contrast between the myocardium and blood, and is commonly referred as black or dark-blood preparation . Image acquisition can be achieved within a breath-hold, yielding a reasonably high spatial-resolution, or faster within a heart-cycle, with a reduced number of phase encoding steps and partial-Fourier, using a technique known as HASTE (Half-Fourier Acquisition Single-shot Turbo Spin-echo) .
The double inversion preparation can be modified to additionally suppress the signal of fat. This is accomplished by adding a second spatially selective inversion pulse closer to the host turbo spin-echo sequence (Figure 11b), known as triple-inversion recovery or short-tau inversion-recovery (STIR). This additional pulse is applied when the magnetisation of the flowing inverted blood is slightly positive, in this way the signal of the flowing blood and fat are close to their null point at the time of imaging. Because of the third inversion, myocardium is imaged while it is at negative magnetisation, but the magnitude image discards the polarity, resulting in a bright myocardial signal.
Good ECG gating or triggering is important to obtain good quality images, and different approaches exist. Cine acquisitions can be prospectively triggered or retrospectively-gated [29, 30]. For prospective triggering, each R-wave triggers the acquisition of a new k-space segment for each cardiac-phase. There are two forms of retrospectively-gated cine imaging. For the first a k-space segment is repeatedly acquired over a predefined time window (bigger than the maximum R-R interval), during the subsequent time window the next segment is acquired. The k-space segments acquired together are labelled with their time during the heart-cycle which is used during image reconstruction. This form of retrospective-gating takes longer to acquire than the second form where the QRS complex is detected and used to instantly advance to the next segment on-the-fly. These retrospective approaches can potentially be less susceptible to small heart-rate variations and they also allow the acquisition of cardiac-phases during late-diastole. Irrespective of the form of gating the temporal-resolution of cines is usually improved with view-sharing (Figure 10).
Cardiac function can also be complemented, to measure regional function, with a tagging sequence (see Section on Tagging Pulses, Figure 5c, and bottom of Figure 12). Tagging data is acquired in the same way, i.e. segmented cine, but with extra tagging pulses immediately after each R-wave trigger and before the cine sequence. The acquired tagging data can be analysed to compute several cardiac parameters including myocardial strain and torsion.
The phase differences can be well defined and velocity-encoded in any or all three perpendicular spatial directions, but are usually applied to just one axis at a time, giving an estimate of the blood flow velocity in each voxel through the chosen direction. It is common to measure the blood velocity in a cross section of a particular vessel. Data is usually acquired using a segmented approach, as described earlier, over a breath-hold. A cine of phase difference maps is reconstructed showing the temporal changes of the velocity throughout the cardiac cycle. Other sources of phase differences, due to field inhomogeneities for example, are the same on the two sets of phase images and these are removed when the images are phase subtracted.
First-pass myocardial perfusion
Perfusion images are commonly T1-weighted by a saturation-recovery preparation pulse that zeroes the entire longitudinal magnetisation a defined interval prior to the image acquisition. Image acquisition occurs during signal recovery from saturation, allowing a good visualisation of the Gd distribution due to its T1-shortening effect: myocardial regions with perfusion defects will have less Gd and are therefore darker than normal regions.
GRE and bSSFP sequences are commonly acquired with a sequential k-space phase-order, while h-EPI generally uses a perfusion-tailored centric interleaved phase-order described by Ding et al . This interleaved acquisition order minimises the TE in the central lines (effective TE) while providing a good T1-weighting for superior contrast enhancement, but it can lead to artefacts as described later.
Myocardial viability is commonly assessed with a technique known as Late Gadolinium Enhancement (LGE). A segmented GRE sequence with an inversion pulse preparation is normally used . The acquisition is ECG gated to diastole for every other heartbeat, as for best results at least a beat needs to be skipped in order to allow T1-recovery prior to the next inversion pulse. One image is typically acquired during each breath-hold, and 10 to 12 breath-holds are needed to cover the entire heart (stack of short-axis slices). The slices are sometimes repeated with swapped phase-encode direction, partly to guard against artefacts as described later, but often also for multiple studies during washout.
Contrast-enhanced GRE is common at 3T, taking advantage of the increased blood signal at higher field strengths . A T1-weighted (non-selective inversion recovery) GRE is used with a TI between 230 and 320 ms to suppress the myocardial signal during the slow infusion of contrast agent. Using a contrast agent increases the contrast between blood and the background signal, however the complexity and limitations of the study increase; contrast-agent usage is limited, and finding the optimum time between injection and imaging is a common difficulty.
Another imaging technique used for imaging the coronary vessel wall is a TSE dark-blood approach; in a similar way to morphology sequences, a dark blood double inversion pulse is used in combination with frequency selective fat suppression prior to image acquisition .
Cardiovascular magnetic resonance artefacts
Following the description of CMR techniques, this section introduces the main purpose of this manuscript, the description of the most common and problematic artefacts in CMR. The causes of these include motion (respiratory, cardiac, and blood flow); Gibbs ringing; aliasing; chemical-shift; and B0-inhomogeneities. In the following sections these different artefact sources will be discussed with particular regard to their physical basis and implications for the different sequences and applications.
The overall motion of the heart is a complex mixture of cardiac motion associated with its cyclic pumping and respiratory motion which results in an additional twisting and volumetric distortion. The respiratory motion is relatively unpredictable and can vary considerably from person to person and from time to time. Cardiac motion has been reasonably well controlled over the years by detecting the QRS complex of the ECG and triggering the acquisition at a certain delay following this. Obviously ECG triggering works best when there is low variation between beats; as discussed later, arrhythmias and ectopic hearts will cause artefacts.
The respiratory motion has in recent years been largely controlled by acquiring the data over the period of a breath-hold, although this can translate into a long acquisition window within the cardiac cycle, thus potentially including periods of more rapid cardiac motion. Restricting the acquisition to a period of mid diastole where the heart is reasonably still is sometimes not feasible during a breath-hold, especially for patients that have considerable problems in holding their breath longer than a few seconds. For patients with very rapid heart-rates it can also be difficult to find a “motion free” acquisition window. Respiratory gating is another technique that allows the removal of gross respiratory motion artefacts by restricting data acquisition to the expiratory pause, this enables longer scans with shorter acquisition windows within the cardiac cycle, which in turn reduces cardiac motion problems. Respiratory gating is most commonly used in 3D imaging, in particular in imaging of the coronary arteries due to the high spatial-resolution (larger data acquisition matrices) and coverage required. The imaging time makes breath-hold imaging impracticable.
A moving object will change both the phase and magnitude of its k-space components. Motion during image acquisition will therefore introduce artefacts, and these can be divided into two categories, motion during the acquisition of one phase-encode line intra-view, and motion between different phase-encode lines inter-view. For most sequences intra-view motion at typical myocardial and respiratory speeds can be ignored, although rapid blood flow in major vessels can be an issue. Inter-view motion artefacts can be caused by cardiac motion and or breathing motion and are very dependent on the nature of the motion in relation to the k-space coverage.
Artefacts can also be created by motion between different components of the sequence, for example between the timing of preparation pulses and image acquisition for a black-blood sequence. The next subsections describe the basics of motion artefacts introduced in cardiac studies by breathing motion, cardiac motion, and blood flow.
To avoid breathing motion artefact problems, the total imaging time is kept short, and suitable for a breath-hold. If the patient is unable to hold their breath, the total imaging time needs to be reduced. Possible solutions include the use of parallel imaging, although the reduction of SNR in some applications such as LGE imaging may prohibit this; or the reduction of overall k-space lines acquired, thus reducing phase-encode spatial-resolution. Another solution is to reduce the temporal-resolution, increasing the data lines per cardiac cycle and the imaging window of each cardiac-phase. This may have the cost of increasing cardiac motion problems, especially if imaging during rapid cardiac motion stages.
In general if imaging during a breath-hold, a saturation band can be applied positioned over the anterior chest wall, to suppress any motion-ghosting from this if the breath-hold is imperfect. This is a common technique in LGE scans.
Cardiac motion is another source of inter-view motion artefacts. Cardiac motion is mainly a problem in sequences where the data acquisition window includes periods of rapid cardiac motion. Blurring can be caused by motion during acquisition of a long segment as illustrated for coronary motion in Figure 18a.
Another good example is first-pass myocardial perfusion imaging, where several images are fully acquired during each heartbeat; therefore image acquisition windows are long and spread across the whole of the cardiac cycle, including rapid cardiac motion stages. The heart will go through contraction and expansion as different phase-encode lines are acquired; motion happens both in-plane and through-plane, resulting in artefacts. Acquisition windows for one perfusion image are approximately 100 ms for GRE and bSSFP sequences and 70 ms for h-EPI, with parallel imaging with an acceleration factor of 2.
In general, whatever the k-space acquisition scheme, in order to minimise cardiac motion artefacts it is important to keep the image acquisition time as short as possible in each heartbeat. Possible approaches, therefore, include using a fast EPI readout, and/or parallel imaging. Another solution is to aim imaging for timings of the heart-cycle where the heart is relatively still, although in some applications such as multi-slice myocardial perfusion imaging this is not possible for all slices, especially when patients are under stress with increased heart-rates. Also, for this specific application the slice-order could result in some slices being more motion affected than others. This slice-order, however, is not generally under the control of the scan operator.
Gibbs ringing, also known as a truncation artefact, is present in every unfiltered MRI image and results from the fact that there is only enough time to acquire a finite region of k-space for each image. When the sampled signal is truncated at the k-space edge and then this k-space is inverse Fourier transformed into the image, ringing will unavoidably be present at high-contrast sharp edges of structures on the image. The ringing is a known mathematical limitation of the Fourier transform.
One way of reducing Gibbs artefacts is by filtering the k-space data of the image, a process usually known as apodization. Hamming and Hann filters are commonly used in image and signal processing to reduce Gibbs ringing artefacts, although at the penalty of reducing spatial-resolution . Due to the image constraints of most cardiac imaging protocols, any further loss in spatial-resolution is unwanted, and therefore k-space filtering is seldom used due to the fear of reducing diagnostic confidence. It is therefore perhaps better for clinical diagnosis and image interpretation to be done by experts who understand the characteristics of these artefacts and can discriminate between them and true perfusion defects for example. The access to k-space filtering options in the scanner’s protocol may vary for different manufacturers.
Another way of reducing Gibbs ringing is by increasing the spatial-resolution. This will not reduce the ringing magnitude but it will make it less conspicuous due its property of scaling with pixel size. Unfortunately in many cases it is not possible to increase the resolution as this would require increased time, which might not be available. Additionally if it were possible, other sources of artefacts such as cardiac motion could be worsened. However as techniques such as parallel imaging and other image acceleration methods improve they can be used to increase spatial-resolution without increasing imaging time [63–65].
Even though this section focused on myocardial perfusion, Gibbs ringing is visible at any sharp edge, and therefore it could affect many other cardiac applications.
Aliasing or wraparound artefacts
Due to the need of large FOVs of image planes to cover the chest, aliasing is a common problem. If the region of interest is small, for example the heart only, then some wraparound can be acceptable as long as it does not superimpose on the heart. This keeps imaging time short without sacrificing diagnosis and experienced technologists commonly make careful use of this approach.
Another technique to avoid or attenuate this artefact is to use saturation bands (spatially selective saturation pulse as described earlier in the Saturation Pulse section under Cardiovascular Pulse Sequences) in the regions outside the FOV to suppress their signal. The saturation works well only if the signal used for the acquisition is excited only once and immediately after the saturation, such as in the 90° excitation of the TSE sequence.
Aliasing artefacts have been discussed in this section for Cartesian sampling only. Aliasing and undersampling artefacts are discussed further in the Artefacts Specific to Advanced Cardiac Imaging Methods section, particularly regarding non-cartesian trajectories and parallel imaging.
A fat and water separated imaging technique has been recently published as a method of detecting intramyocardial fat .
When imaging the coronaries, the signal cancellation artefacts can reduce the apparent diameter of the coronary arteries if fat signal is not properly suppressed.
The magnetic field is never completely homogeneous over the volume of the heart. It is possible to largely correct variations by obtaining 3D field plots and calculating the required shim currents, however, local field variations will remain because of the magnetic field susceptibility variations around the heart.
Most tissues are diamagnetic, i.e. create a magnetic field that slightly opposes the applied magnetic field. It is important to understand that this arises from their electronic (“Lenz”) diamagnetism, which is much larger than the nuclear magnetisation we employ for MRI. The differences in diamagnetism cause distortion of the main field at interfaces between tissues, and particularly those between tissue and air such as between the heart and lungs. These B0 field inhomogeneities cause resonance frequency offsets, where the local resonance frequency deviates from the scanner’s centre frequency, leading to off-resonance effects. Depending on the local geometry, and the sequence being used, this field distortion may sometimes be more intense causing artefacts such as signal loss or spatial distortion.
Localised field inhomogeneities due to susceptibility differences in the locality of the cardiac veins ; and at tissue-air interfaces such as the heart-lung interface , or adjacent to air pockets  (in the bowel, stomach, and colon for example), introduce banding type artefacts on bSSFP images that can confuse the image interpretation. These signal loss artefacts should not be confused with intravoxel dephasing which is caused very differently.
Field inhomogeneities are also an important source of artefacts for the less widely-used EPI sequences. Sequences with an EPI readout tend to be used in a hybrid approach (h-EPI), in order to keep the readout train reasonably short, thus minimising blurring, ghosting, image distortion, and chemical shift artefacts. h-EPI sequences are commonly used with an interleaved phase-order. Frequency offsets will introduce phase variations in a stepwise fashion, which can lead to artefacts such as blurring, and ghosting.
In general to minimise B0-inhomogeneities, careful shimming and especially localised scanner frequency adjustments are advised prior to imaging.
Blood flow measurement
More subtle effects can cause significant errors to flow measurements by introducing background phase shifts. Some distortion of the magnetic field gradients is unavoidable from fundamental electromagnetism, and this is known in MRI as Maxwell or concomitant gradients. This is one cause of the background phase shifts which become more significant when high-strength gradients are used and also when imaging at lower main field strengths. With the latest gradient systems Maxwell gradient effects are certainly a factor for phase contrast velocity mapping at 1.5T. The velocity maps can however be corrected analytically and automatically in software with no user intervention required.
A second common reason for background phase shifts is the presence of small uncorrected side-effects of the gradient pulses in the magnet, known as eddy currents. Software is sometimes provided which allows the user to place markers identifying stationary tissues so that the background phase error can be calculated and removed from the entire image. It has been shown previously that small background errors (smaller than 1% of the velocity sensitivity range (VENC)) can significantly affect measurements of shunt flow and cardiac output, and that these may occur easily on some systems .
Voxels containing a range of velocities in the direction encoded will suffer dephasing, resulting in a weak overall signal which can lead to unreliable phase measurements and therefore unreliable output from the phase subtraction for the velocity image. As the velocity encoded magnitude is often not reconstructed users should be aware of how unreliable the velocity data may be.
Late gadolinium enhancement
Artefacts specific to advanced cardiac imaging methods
Methods of more efficiently acquiring the MR data are of particular interest to CMR because of the compromises that have to be made to acquire image data in a short time, often restricted to a fraction of one cardiac cycle or fractions of multiple cardiac cycles within a breath-hold. Methods such as non-cartesian sampling, parallel imaging, and partial-Fourier have been introduced to accelerate the acquisition. Although each of these methods may work well a proportion of the time and in particular if extra care is taken to set up the scan, they all tend to reduce the imaging robustness and tend to produce artefacts on images and or produce artefactual measurements.
Parallel imaging artefacts
Parallel imaging accelerates image acquisition which has the potential to reduce some problems, for example, although parallel imaging introduces an SNR penalty, it also shortens the readout time which for a single shot EPI sequence for example reduces distortions caused by field inhomogeneities, reduces blurring due to T2* and or T2 decay and reduces sensitivity to motion.
Motion with radial and spiral k-space trajectories
Sequences with non-Cartesian forms of k-space coverage such as radial and spiral have also been used to image the heart [82–88], artefacts discussed earlier can have very different characteristics when compared to the more conventional Cartesian methods.
Radial sampled data can also be used to correct for motion in a self-navigating way. Different projection views (at different angles) can be analysed for consistency. If motion is present, consistency will fail and the data can be discarded and potentially resampled before reconstruction . This technique uses navigator data from the heart itself, and not from the diaphragm, eliminating any problems of translating diaphragmatic motion to cardiac motion. Similarly self-gating has been described using radial sampling with a 1DFT projection reconstruction to monitor the heart motion through the cardiac cycle and then to use this for cardiac gating . However, it has to be accepted that the performance of such methods depends on the contents of the slice being imaged and is potentially less reliable than the use of ECG synchronisation.
B0 inhomogeneity with Radial and Spiral k-space trajectories
Aliasing with radial and spiral k-space trajectories
Due to the 2D readout gradients in these trajectories, aliasing artefacts happen from all directions resulting in additional streaks and swirls, therefore the FOV has to be chosen with attention to aliasing in all directions. Because there is no wraparound along the phase-encode direction, mild undersampling artefacts are commonly considered as a good trade-off for reduced imaging time.
EPI and nyquist ghosting
1.5T vs 3T
Cardiac imaging at 3T is becoming increasingly popular due to the potentially higher SNR and CNR (Contrast to Noise Ratio). At higher fields, some of the above mentioned artefacts become even more problematic such as those caused by B0 and B1 field inhomogeneities or chemical shift. The potential increase in SNR, however, can be traded for example for higher parallel imaging accelerations resulting in quicker imaging acquisitions, which can potentially reduce motion artefacts; or enable higher spatial-resolutions which can for example make Gibbs artefacts less prominent.
Together with an increase of approximately twofold in SNR, there is also a quadruple increase in RF power absorption. Some sequences, such as bSSFP, may have to be used with a reduced flip-angle and higher TR than at 1.5T, which increases B0 inhomogeneity sensitivity and reduces contrast. An experienced operator with the ability to perform careful frequency adjustments is important when using bSSFP sequences at 3T. EPI geometric distortions and ghosting are also a bigger problem at a higher field. Spoiled GRE sequences are thus more common in many 3T imaging protocols, taking advantage of the spoiled sequence’s increased robustness to B0 inhomogeneities along with the increased SNR over 1.5T.
Although T2 relaxation times of tissues remain approximately unchanged from those at 1.5T, T1 relaxation times are noticeably longer at 3T . This requires many protocols to be adapted for use at 3T. For example the optimal inversion times for black blood imaging and late-Gd-enhancement may need to be increased. The same changes in relaxation time can also be used to reduce the dose of Gd contrast agent in first-pass perfusion and LGE studies decreasing possible susceptibility problems [98, 99].
Cardiac gating can also be more challenging at 3T. The higher field strength creates more magnetohydrodynamic distortion of the ECG signal, which can prevent the scanner from gating properly leading to additional artefacts.
Cardiovascular imaging is complicated primarily by the complex nature of the cardiac motion. Many of the cardiac imaging artefacts are directly related to motion or indirectly introduced by the requirement to shorten the acquisition time to remove motion. The complex cardiac structure with mixtures of fat and water based tissues containing complex and varying blood flows, and the large chest region with many organs and tissue-air interfaces also open the door to additional artefacts and measurement errors.
If we understand the physical principles behind the formation of artefacts, we should be in a position to identify and possibly avoid them, increasing image quality and interpretation.
The authors are grateful to Dr. Jennifer Keegan for her support with this manuscript. This work was supported by the NIHR Cardiovascular Biomedical Research Unit of Royal Brompton and Harefield NHS Foundation Trust and Imperial College London UK.
- Smith T, Nayak K: MRI artifacts and correction strategies. Imaging Med. 2010, 2 (4): 445-57. 10.2217/iim.10.33.View ArticleGoogle Scholar
- Saremi F, Grizzard JD, Kim RJ: Optimizing cardiac MR imaging: practical remedies for artifacts. Radiographics. 2008, 28 (4): 1161-87. 10.1148/rg.284065718.View ArticlePubMedGoogle Scholar
- McRobbie DW, Moore EA, Graves MJ, Prince MR: Chapter 6: Improving your image: how to avoid artefacts. MRI from Picture to Proton. 2006, Cambridge University Press, 79-107. 2View ArticleGoogle Scholar
- Ridgway JP: Cardiovascular magnetic resonance physics for clinicians: part I. J CardiovascMagn Reson. 2010, 12: 71-View ArticleGoogle Scholar
- Biglands JD, Radjenovic A, Ridgway JP: Cardiovascular magnetic resonance physics for clinicians: Part II. J Cardiovasc Magn Reson. 2012, 14: 66-10.1186/1532-429X-14-66.PubMed CentralView ArticlePubMedGoogle Scholar
- Zur Y, Wood ML, Neuringer LJ: Spoiling of transverse magnetization in steady-state sequences. Magn Reson Med. 1991, 21 (2): 251-63. 10.1002/mrm.1910210210.View ArticlePubMedGoogle Scholar
- Levitt MH: Composite pulses. Prog Nucl Magn Reson Spectrosc. 1986, 18: 61-122. 10.1016/0079-6565(86)80005-X.View ArticleGoogle Scholar
- Ugurbil K, Garwood MBM: Amplitude and frequency modulated pulses to achieve 90 plane rotations with inhomogeneous B1 fields. J Magn Reson. 1987, 72: 177-85.Google Scholar
- Axel L, Dougherty L: MR imaging of motion with spatial modulation of magnetization. Radiology. 1989, 171 (3): 841-5.View ArticlePubMedGoogle Scholar
- Fischer SE, McKinnon GC, Maier SE, Boesiger P: Improved myocardial tagging contrast. Magn Reson Med. 1993, 30 (2): 191-200. 10.1002/mrm.1910300207.View ArticlePubMedGoogle Scholar
- Lauterbur PC: Image formation by induced local interactions, examples employing nuclear magnetic resonance. Nature. 1973, 242: 190-1. 10.1038/242190a0.View ArticleGoogle Scholar
- Axel L, Herman GT, Roberts DA, Dougherty L: Linogram reconstruction for magnetic resonance imaging (MRI). IEEE Trans Med Imaging. 1990, 9 (4): 447-9. 10.1109/42.61760.View ArticlePubMedGoogle Scholar
- Pipe JG: Motion correction with propeller MRI: application to head motion and free-breathing cardiac imaging. Magn Reson Med. 1999, 42 (5): 963-9. 10.1002/(SICI)1522-2594(199911)42:5<963::AID-MRM17>3.0.CO;2-L.View ArticlePubMedGoogle Scholar
- Feinberg DA, Hale JD, Watts JC, Kaufman L, Mark A: Halving MR imaging time by conjugation: demonstration at 3.5 kg. Radiology. 1986, 161 (2): 527-31.View ArticlePubMedGoogle Scholar
- Larkman DJ, Nunes RG: Parallel magnetic resonance imaging. Phys Med Biol. 2007, 52 (7): R15-55. 10.1088/0031-9155/52/7/R01.View ArticlePubMedGoogle Scholar
- Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A: Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002, 47 (6): 1202-10. 10.1002/mrm.10171.View ArticlePubMedGoogle Scholar
- Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P: SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 1999, 42 (5): 952-62. 10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S.View ArticlePubMedGoogle Scholar
- Madore B, Glover GH, Pelc NJ: Unaliasing by fourier-encoding the overlaps using the temporal dimension (UNFOLD), applied to cardiac imaging and fMRI. Magn Reson Med. 1999, 42 (5): 813-28. 10.1002/(SICI)1522-2594(199911)42:5<813::AID-MRM1>3.0.CO;2-S.View ArticlePubMedGoogle Scholar
- Kellman P, Epstein FH, McVeigh ER: Adaptive sensitivity encoding incorporating temporal filtering (TSENSE). Magn Reson Med. 2001, 45 (5): 846-52. 10.1002/mrm.1113.View ArticlePubMedGoogle Scholar
- Breuer FA, Kellman P, Griswold MA, Jakob PM: Dynamic autocalibrated parallel imaging using temporal grappa (TGRAPPA). Magn Reson Med. 2005, 53 (4): 981-5. 10.1002/mrm.20430.View ArticlePubMedGoogle Scholar
- Foo TK, Bernstein MA, Aisen AM, Hernandez RJ, Collick BD, Bernstein T: Improved ejection fraction and flow velocity estimates with use of view sharing and uniform repetition time excitation with fast cardiac techniques. Radiology. 1995, 195 (2): 471-8.View ArticlePubMedGoogle Scholar
- Markl M, Hennig J: Phase contrast MRI with improved temporal resolution by view sharing: k-space related velocity mapping properties. Magn Reson Imaging. 2001, 19 (5): 669-76. 10.1016/S0730-725X(01)00386-1.View ArticlePubMedGoogle Scholar
- Simonetti OP, Finn JP, White RD, Laub G, Henry DA: "black blood" t2-weighted inversion-recovery MR imaging of the heart. Radiology. 1996, 199 (1): 49-57.View ArticlePubMedGoogle Scholar
- Kiefer B, Grassner J, Hausman R: Image acquisition in a second with half fourier acquisition single-shot turbo spin-echo. Proceedings of Society for Magnetic Resonance. 1994Google Scholar
- Sechtem U, Pflugfelder PW, Gould RG, Cassidy MM, Higgins CB: Measurement of right and left ventricular volumes in healthy individuals with cine MR imaging. Radiology. 1987, 163 (3): 697-702.View ArticlePubMedGoogle Scholar
- Plein S, Bloomer TN, Ridgway JP, Jones TR, Bainbridge GJ, Sivananthan MU: Steady-state free precession magnetic resonance imaging of the heart: comparison with segmented k-space gradient-echo imaging. J Magn Reson Imaging. 2001, 14 (3): 230-6. 10.1002/jmri.1178.View ArticlePubMedGoogle Scholar
- Barkhausen J, Ruehm SG, Goyen M, Buck T, Laub G, Debatin JF: MR evaluation of ventricular function: true fast imaging with steady-state precession versus fast low-angle shot cine MR imaging: feasibility study. Radiology. 2001, 219 (1): 264-9.View ArticlePubMedGoogle Scholar
- Thiele H, Nagel E, Paetsch I, Schnackenburg B, Bornstedt A, Kouwenhoven M, Wahl A, Schuler G, Fleck E: Functional cardiac MR imaging with steady-state free precession (SSFP) significantly improves endocardial border delineation without contrast agents. J Magn Reson Imaging. 2001, 14 (4): 362-7. 10.1002/jmri.1195.View ArticlePubMedGoogle Scholar
- Lanzer P, Barta C, Botvinick EH, Wiesendanger HU, Modin G, Higgins CB: ECG-synchronized cardiac MR imaging: method and evaluation. Radiology. 1985, 155 (3): 681-6.View ArticlePubMedGoogle Scholar
- Lenz GW, Haacke EM, White RD: Retrospective cardiac gating: a review of technical aspects and future directions. Magn Reson Imaging. 1989, 7 (5): 445-55. 10.1016/0730-725X(89)90399-8.View ArticlePubMedGoogle Scholar
- Bryant DJ, Payne JA, Firmin DN, Longmore DB: Measurement of flow with NMR imaging using a gradient pulse and phase difference technique. J Comput Assist Tomogr. 1984, 8 (4): 588-93. 10.1097/00004728-198408000-00002.View ArticlePubMedGoogle Scholar
- Nayler GL, Firmin DN, Longmore DB: Blood flow imaging by cine magnetic resonance. J Comput Assist Tomogr. 1986, 10 (5): 715-22. 10.1097/00004728-198609000-00001.View ArticlePubMedGoogle Scholar
- Moran PR: A flow velocity zeugmatographic interlace for NMR imaging in humans. Magn Reson Imaging. 1982, 1 (4): 197-203. 10.1016/0730-725X(82)90170-9.View ArticlePubMedGoogle Scholar
- VanDijk P: Direct cardiac NMR imaging of heart wall and blood flow velocity. J Comput Assist Tomogr. 1984, 8 (3): 429-36. 10.1097/00004728-198406000-00012.View ArticleGoogle Scholar
- Atkinson DJ, Burstein D, Edelman RR: First-pass cardiac perfusion: evaluation with ultrafast MR imaging. Radiology. 1990, 174 (3 Pt 1): 757-62.View ArticlePubMedGoogle Scholar
- Ding S, Wolff SD, Epstein FH: Improved coverage in dynamic contrast-enhanced cardiac MRI using interleaved gradient-echo EPI. Magn Reson Med. 1998, 39 (4): 514-9. 10.1002/mrm.1910390403.View ArticlePubMedGoogle Scholar
- Simonetti OP, Kim RJ, Fieno DS, Hillenbrand HB, Wu E, Bundy JM, Finn JP, Judd RM: An improved MR imaging technique for the visualization of myocardial infarction. Radiology. 2001, 218 (1): 215-23.View ArticlePubMedGoogle Scholar
- Kellman P, Arai AE, McVeigh ER, Aletras AH: Phase-sensitive inversion recovery for detecting myocardial infarction using gadolinium-delayed hyperenhancement. Magn Reson Med. 2002, 47 (2): 372-83. 10.1002/mrm.10051.PubMed CentralView ArticlePubMedGoogle Scholar
- Locca D, Bucciarelli-Ducci C, Lyne J, Chapparo M, Ferrante G, O’Hanlon R, Prasad S, Gatehouse P, Drivas P, Wage R, Firmin D, Pennell D: Rapid assessment of myocardial scar and viability in ischemic heart disease: a cardiovascular magnetic resonance study. Proceedings of Society for Cardiovascular Magnetic Resonance. 2009, 154-Google Scholar
- Stuber M, Botnar RM, Danias PG, Sodickson DK, Kissinger KV, Van Cauteren M, De Becker J, Manning WJ: Double-oblique free-breathing high resolution three-dimensional coronary magnetic resonance angiography. J Am CollCardiol. 1999, 34 (2): 524-31. 10.1016/S0735-1097(99)00223-5.View ArticleGoogle Scholar
- Regenfus M, Ropers D, Achenbach S, Schlundt C, Kessler W, Laub G, Moshage W, Daniel WG: Comparison of contrast-enhanced breath-hold and free-breathing respiratory-gated imaging in three-dimensional magnetic resonance coronary angiography. Am J Cardiol. 2002, 90 (7): 725-30. 10.1016/S0002-9149(02)02598-5.View ArticlePubMedGoogle Scholar
- Deshpande VS, Shea SM, Chung YC, McCarthy RM, Finn JP, Li D: Breath-hold three-dimensional true-FISP imaging of coronary arteries using asymmetric sampling. J Magn Reson Imaging. 2002, 15 (4): 473-8. 10.1002/jmri.10087.View ArticlePubMedGoogle Scholar
- Bi X, Li D: coronary arteries at 3.0 t: Contrast-enhanced magnetization-prepared three-dimensional breathhold MR angiography. J Magn Reson Imaging. 2005, 21 (2): 133-9. 10.1002/jmri.20250.View ArticlePubMedGoogle Scholar
- Stuber M, Botnar RM, Kissinger KV, Manning WJ: Free-breathing black-blood coronary MR angiography: initial results. Radiology. 2001, 219 (1): 278-83.View ArticlePubMedGoogle Scholar
- Al-Kwifi O, Stainsby J, Foltz WD, Sussman MS, Huang Y, Wright GA: Characterizing coronary motion and its effect on MR coronary angiography–initial experience. J Magn Reson Imaging. 2006, 24 (4): 842-50. 10.1002/jmri.20697.View ArticlePubMedGoogle Scholar
- Oshinski JN, Hofland L, Mukundan S, Dixon WT, Parks WJ, Pettigrew RI: Two-dimensional coronary MR angiography without breath holding. Radiology. 1996, 201 (3): 737-43.View ArticlePubMedGoogle Scholar
- Korin HW, Felmlee JP, Ehman RL, Riederer SJ: Adaptive technique for three-dimensional MR imaging of moving structures. Radiology. 1990, 177 (1): 217-21.View ArticlePubMedGoogle Scholar
- Taylor AM, Keegan J, Jhooti P, Firmin DN, Pennell DJ: Calculation of a subject-specific adaptive motion-correction factor for improved real-time navigator echo-gated magnetic resonance coronary angiography. J CardiovascMagn Reson. 1999, 1 (2): 131-8.View ArticleGoogle Scholar
- Keegan J, Gatehouse P, Yang G-Z, Firmin D: Coronary artery motion with the respiratory cycle during breath-holding and free-breathing: implications for slice-followed coronary artery imaging. Magn Reson Med. 2002, 47 (3): 476-81. 10.1002/mrm.10069.View ArticlePubMedGoogle Scholar
- Hofman MB, van Rossum AC, Sprenger M, Westerhof N: Assessment of flow in the right human coronary artery by magnetic resonance phase contrast velocity measurement: effects of cardiac and respiratory motion. Magn Reson Med. 1996, 35 (4): 521-31. 10.1002/mrm.1910350411.View ArticlePubMedGoogle Scholar
- Storey P, Chen Q, Li W, Edelman RR, Prasad PV: Band artifacts due to bulk motion. Magn Reson Med. 2002, 48 (6): 1028-36. 10.1002/mrm.10314.View ArticlePubMedGoogle Scholar
- Ferreira P, Gatehouse P, Kellman P, Firmin D: Realistic simulations on the dark rim artifact for myocardial perfusion protocols. Proceedings ISMRM. 2009Google Scholar
- Keegan J, Gatehouse PD, Prasad SK, Firmin DN: Improved turbo spin-echo imaging of the heart with motion-tracking. J Magn Reson Imaging. 2006, 24 (3): 563-70. 10.1002/jmri.20655.View ArticlePubMedGoogle Scholar
- Togawa T, Okai O, Oshima M: Observation of blood flow E.M.F. in externally applied strong magnetic field by surface electrodes. Med BiolEng. 1967, 5 (2): 169-70.Google Scholar
- Kellman P, Chefd’hotel C, Lorenz CH, Mancini C, Arai AE, McVeigh ER: High spatial and temporal resolution cardiac cine MRI from retrospective reconstruction of data acquired in real time using motion correction and resorting. Magn Reson Med. 2009, 62 (6): 1557-64. 10.1002/mrm.22153.PubMed CentralView ArticlePubMedGoogle Scholar
- Plein S, Smith WH, Ridgway JP, Kassner A, Beacock DJ, Bloomer TN, Sivananthan MU: Qualitative and quantitative analysis of regional left ventricular wall dynamics using real-time magnetic resonance imaging: comparison with conventional breath-hold gradient echo acquisition in volunteers and patients. J Magn Reson Imaging. 2001, 14 (1): 23-30. 10.1002/jmri.1146.View ArticlePubMedGoogle Scholar
- Setser RM, Fischer SE, Lorenz CH: Quantification of left ventricular function with magnetic resonance images acquired in real time. J Magn Reson Imaging. 2000, 12 (3): 430-8. 10.1002/1522-2586(200009)12:3<430::AID-JMRI8>3.0.CO;2-V.View ArticlePubMedGoogle Scholar
- Kaji S, Yang PC, Kerr AB, Tang WH, Meyer CH, Macovski A, Pauly JM, Nishimura DG, Hu BS: Rapid evaluation of left ventricular volume and mass without breath-holding using real-time interactive cardiac magnetic resonance imaging system. J Am CollCardiol. 2001, 38 (2): 527-33. 10.1016/S0735-1097(01)01399-7.View ArticleGoogle Scholar
- Hori Y, Yamada N, Higashi M, Hirai N, Nakatani S: Rapid evaluation of right and left ventricular function and mass using real-time true-FISP cine MR imaging without breath-hold: comparison with segmented true-FISP cine MR imaging with breath-hold. J CardiovascMagn Reson. 2003, 5 (3): 439-50.View ArticleGoogle Scholar
- Ferreira P, Gatehouse P, Kellman P, Bucciarelli-Ducci C, Firmin D: Variability of myocardial perfusion dark rim gibbsartifacts due to sub-pixel shifts. J Cardiovasc Magn Reson. 2009, 11: 17-10.1186/1532-429X-11-17.PubMed CentralView ArticlePubMedGoogle Scholar
- Di Bella EVR, Parker DL, Sinusas AJ: On the dark rim artifact in dynamic contrast-enhanced MRI myocardial perfusion studies. Magn Reson Med. 2005, 54 (5): 1295-9. 10.1002/mrm.20666.PubMed CentralView ArticlePubMedGoogle Scholar
- Frederick H: On the use of windows for harmonic analysis with the discrete fourier transform. Proc IEEE. 1978, 66 (51): 83-Google Scholar
- Otazo R, Kim D, Axel L, Sodickson DK: Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI. Magn Reson Med. 2010, 64 (3): 767-76. 10.1002/mrm.22463.PubMed CentralView ArticlePubMedGoogle Scholar
- Plein S, Ryf S, Schwitter J, Radjenovic A, Boesiger P, Kozerke S: Dynamic contrast-enhanced myocardial perfusion mri accelerated with k-t sense. Magn Reson Med. 2007, 58 (4): 777-85. 10.1002/mrm.21381.View ArticlePubMedGoogle Scholar
- Tsao J, Boesiger P, Pruessmann KP: k-t blast and k-t sense: dynamic MRI with high frame rate exploiting spatiotemporal correlations. Magn Reson Med. 2003, 50 (5): 1031-42. 10.1002/mrm.10611.View ArticlePubMedGoogle Scholar
- Kellman P, Hernando D, Arai AE: Myocardial fat imaging.CurrCardiovasc. Imaging Rep. 2010, 3 (2): 83-91.Google Scholar
- Scheffler K, Lehnhardt S: Principles and applications of balanced SSFP techniques. EurRadiol. 2003, 13 (11): 2409-18.Google Scholar
- Reeder SB, Faranesh AZ, Boxerman JL, McVeigh ER: In vivo measurement of t*2 and field inhomogeneity maps in the human heart at 1.5 t. Magn Reson Med. 1998, 39 (6): 988-98. 10.1002/mrm.1910390617.PubMed CentralView ArticlePubMedGoogle Scholar
- Atalay MK, Poncelet BP, Kantor HL, Brady TJ, Weisskoff RM: Cardiac susceptibility artifacts arising from the heart-lung interface. Magn Reson Med. 2001, 45 (2): 341-5. 10.1002/1522-2594(200102)45:2<341::AID-MRM1043>3.0.CO;2-Q.View ArticlePubMedGoogle Scholar
- Sorrell VL, Anderson JL, Gatehouse PD, Mohiaddin RH: Off-frequency tuning error artifact in steady-state free precession cine imaging due to adjacent air-filled bowel. J Cardiovasc Magn Reson. 2004, 6 (3): 709-16. 10.1081/JCMR-120038089.View ArticlePubMedGoogle Scholar
- Markl M, Alley MT, Elkins CJ, Pelc NJ: Flow effects in balanced steady state free precession imaging. Magn Reson Med. 2003, 50 (5): 892-903. 10.1002/mrm.10631.View ArticlePubMedGoogle Scholar
- Storey P, Li W, Chen Q, Edelman RR: Flow artifacts in steady-state free precession cine imaging. Magn Reson Med. 2004, 51 (1): 115-22. 10.1002/mrm.10665.View ArticlePubMedGoogle Scholar
- Markl M, Pelc NJ: On flow effects in balanced steady-state free precession imaging: pictorial description, parameter dependence, and clinical implications. J Magn Reson Imaging. 2004, 20 (4): 697-705. 10.1002/jmri.20163.View ArticlePubMedGoogle Scholar
- Nayak KS, Lee H-L, Hargreaves BA, Wideband BSH: SSFP: alternating repetition time balanced steady state free precession with increased band spacing. Magn Reson Med. 2007, 58 (5): 931-8. 10.1002/mrm.21296.View ArticlePubMedGoogle Scholar
- Ferreira P, Gatehouse P, Bucciarelli-Ducci C, Wage R, Firmin D: Measurement of myocardial frequency offsets during first pass of a gadolinium-based contrast agent in perfusion studies. Magn Reson Med. 2008, 60 (4): 860-70. 10.1002/mrm.21723.View ArticlePubMedGoogle Scholar
- Ferreira PF, Gatehouse PD, Firmin DN: Myocardial first-pass perfusion imaging with hybrid-EPI: frequency-offsets and potential artefacts. J CardiovascMagn Reson. 2012, 14: 44-View ArticleGoogle Scholar
- Bernstein MA, Zhou XJ, Polzin JA, King KF, Ganin A, Pelc NJ, Glover GH: Concomitant gradient terms in phase contrast MR: analysis and correction. Magn Reson Med. 1998, 39 (2): 300-8. 10.1002/mrm.1910390218.View ArticlePubMedGoogle Scholar
- Gatehouse PD, Rolf MP, Graves MJ, Hofman MB, Totman J, Werner B, Quest RA, Liu Y, von Spiczak J, Dieringer M, Firmin DN, van Rossum A, Lombardi M, Schwitter J, Schulz-Menger J, Kilner PJ: Flow measurement by cardiovascular magnetic resonance: a multi-centre multi-vendor study of background phase offset errors that can compromise the accuracy of derived regurgitant or shunt flow measurements. J Cardiovasc Magn Reson. 2010, 12: 5-10.1186/1532-429X-12-5.PubMed CentralView ArticlePubMedGoogle Scholar
- Gatehouse P, Al-Shalabi S, Firmin D: A study of possible inversion-recovery artefacts in late-Gd myocardial contrast enhancement imaging. Proceedings of Society for Cardiovascular Magnetic Resonance. 2006Google Scholar
- Griswold MA, Kannengiesser S, Heidemann RM, Wang J, Jakob PM: Field-of-view limitations in parallel imaging. Magn Reson Med. 2004, 52 (5): 1118-26. 10.1002/mrm.20249.View ArticlePubMedGoogle Scholar
- Ding Y, Chung Y-C, Jekic M, Simonetti OP: A new approach to autocalibrated dynamic parallel imaging based on the Karhunen-Loevetransform: KL-TSENSE and KL-TGRAPPA. Magn Reson Med. 2011, 65 (6): 1786-92. 10.1002/mrm.22766.PubMed CentralView ArticlePubMedGoogle Scholar
- Salerno M, Sica CT, Kramer CM, Meyer CH: Optimization of spiral-based pulse sequences for first-pass myocardial perfusion imaging. Magn Reson Med. 2011, 65 (6): 1602-10. 10.1002/mrm.22746.View ArticlePubMedGoogle Scholar
- Liao JR, Pauly JM, Brosnan TJ, Pelc NJ: Reduction of motion artifacts in cine MRI using variable-density spiral trajectories. Magn Reson Med. 1997, 37 (4): 569-75. 10.1002/mrm.1910370416.View ArticlePubMedGoogle Scholar
- Gatehouse PD, Firmin DN, Collins S, Longmore DB: Real time blood flow imaging by spiral scan phase velocity mapping. Magn Reson Med. 1994, 31 (5): 504-12. 10.1002/mrm.1910310506.View ArticlePubMedGoogle Scholar
- Meyer CH, Hu BS, Nishimura DG, Macovski A: Fast spiral coronary artery imaging. Magn Reson Med. 1992, 28 (2): 202-13. 10.1002/mrm.1910280204.View ArticlePubMedGoogle Scholar
- Rasche V, Holz D, Schepper W: Radial turbo spin echo imaging. Magn Reson Med. 1994, 32 (5): 629-38. 10.1002/mrm.1910320512.View ArticlePubMedGoogle Scholar
- Peters DC, Epstein FH, McVeigh ER: Myocardial wall tagging with undersampled projection reconstruction. Magn Reson Med. 2001, 45 (4): 562-7. 10.1002/mrm.1076.PubMed CentralView ArticlePubMedGoogle Scholar
- Larson AC, Simonetti OP: Real-time cardiac cine imaging with spider: steady-state projection imaging with dynamic echo-train readout. Magn Reson Med. 2001, 46 (6): 1059-66. 10.1002/mrm.1299.View ArticlePubMedGoogle Scholar
- Glover GH, Pauly JM: Projection reconstruction techniques for reduction of motion effects in MRI. Magn Reson Med. 1992, 28 (2): 275-89. 10.1002/mrm.1910280209.View ArticlePubMedGoogle Scholar
- Glover GH, Noll DC: Consistent projection reconstruction (CPR) techniques for MRI. Magn Reson Med. 1993, 29 (3): 345-51. 10.1002/mrm.1910290310.View ArticlePubMedGoogle Scholar
- Larson AC, White RD, Laub G, McVeigh ER, Li D, Simonetti OP: Self-gated cardiac cine MRI. Magn Reson Med. 2004, 51 (1): 93-102. 10.1002/mrm.10664.PubMed CentralView ArticlePubMedGoogle Scholar
- O’Donnell M, Edelstein WA: NMR imaging in the presence of magnetic field inhomogeneities and gradient field nonlinearities. Med Phys. 1985, 12 (1): 20-6. 10.1118/1.595732.View ArticlePubMedGoogle Scholar
- Bruder H, Fischer H, Reinfelder HE, Schmitt F: Image reconstruction for echo planar imaging with nonequidistant k-space sampling. Magn Reson Med. 1992, 23 (2): 311-23. 10.1002/mrm.1910230211.View ArticlePubMedGoogle Scholar
- Zhou XJ, Du YP, Bernstein MA, Reynolds HG, Maier JK, Polzin JA: Concomitant magnetic-field-induced artifacts in axial echo planar imaging. Magn Reson Med. 1998, 39 (4): 596-605. 10.1002/mrm.1910390413.View ArticlePubMedGoogle Scholar
- Delakis I, Petala K, De Wilde JP: MRI receiver frequency response as a contributor to Nyquist ghosting in echo planar imaging. J Magn Reson Imaging. 2005, 22 (2): 324-8. 10.1002/jmri.20365.View ArticlePubMedGoogle Scholar
- Reeder SB, Atalar E, Bolster BD, McVeigh ER: Quantification and reduction of ghosting artifacts in interleaved echo-planar imaging. Magn Reson Med. 1997, 38 (3): 429-39. 10.1002/mrm.1910380312.PubMed CentralView ArticlePubMedGoogle Scholar
- Stanisz GJ, Odrobina EE, Pun J, Escaravage M, Graham SJ, Bronskill MJ, Henkelman RM: T1, T2 relaxation and magnetization transfer in tissue at 3T. Magn Reson Med. 2005, 54 (3): 507-12. 10.1002/mrm.20605.View ArticlePubMedGoogle Scholar
- Araoz PA, Glockner JF, McGee KP, Potter DD, Valeti VU, Stanley DW, Christian TF: 3 tesla MR imaging provides improved contrast in first-pass myocardial perfusion imaging over a range of gadolinium doses. J Cardiovasc Magn Reson. 2005, 7 (3): 559-64. 10.1081/JCMR-200060622.View ArticlePubMedGoogle Scholar
- Klumpp B, Fenchel M, Hoevelborn T, Helber U, Scheule A, Claussen C, Miller S: Assessment of myocardial viability using delayed enhancement magnetic resonance imaging at 3.0 Tesla. Invest Radiol. 2006, 41 (9): 661-7. 10.1097/01.rli.0000233321.82194.09.View ArticlePubMedGoogle Scholar
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