Cardiovascular magnetic resonance physics for clinicians: part II
© Biglands et al.; licensee BioMed Central Ltd. 2012
Received: 12 March 2012
Accepted: 13 September 2012
Published: 20 September 2012
This is the second of two reviews that is intended to cover the essential aspects of cardiovascular magnetic resonance (CMR) physics in a way that is understandable and relevant to clinicians using CMR in their daily practice. Starting with the basic pulse sequences and contrast mechanisms described in part I, it briefly discusses further approaches to accelerate image acquisition. It then continues by showing in detail how the contrast behaviour of black blood fast spin echo and bright blood cine gradient echo techniques can be modified by adding rf preparation pulses to derive a number of more specialised pulse sequences. The simplest examples described include T2-weighted oedema imaging, fat suppression and myocardial tagging cine pulse sequences. Two further important derivatives of the gradient echo pulse sequence, obtained by adding preparation pulses, are used in combination with the administration of a gadolinium-based contrast agent for myocardial perfusion imaging and the assessment of myocardial tissue viability using a late gadolinium enhancement (LGE) technique. These two imaging techniques are discussed in more detail, outlining the basic principles of each pulse sequence, the practical steps required to achieve the best results in a clinical setting and, in the case of perfusion, explaining some of the factors that influence current approaches to perfusion image analysis. The key principles of contrast-enhanced magnetic resonance angiography (CE-MRA) are also explained in detail, especially focusing on timing of the acquisition following contrast agent bolus administration, and current approaches to achieving time resolved MRA. Alternative MRA techniques that do not require the use of an endogenous contrast agent are summarised, and the specialised pulse sequence used to image the coronary arteries, using respiratory navigator gating, is described in detail. The article concludes by explaining the principle behind phase contrast imaging techniques which create images that represent the phase of the MR signal rather than the magnitude. It is shown how this principle can be used to generate velocity maps by designing gradient waveforms that give rise to a relative phase change that is proportional to velocity. Choice of velocity encoding range and key pitfalls in the use of this technique are discussed.
KeywordsCardiovascular magnetic resonance MR physics MR contrast agents Fat suppression Tagging Myocardial perfusion imaging Late gadolinium enhancement MR angiography Velocity mapping Myocardial edema Myocardial ischemia Coronary heart disease Myocardial infarction
This review is the second part of two that aim to cover the basic physical principles underlying the most commonly used cardiovascular magnetic resonance CMR) techniques. In part I, the basic principles of MR signal generation and image formation were reviewed, together with the principles of cardiac synchronisation and fast (or turbo) imaging pulse sequences and how these can be combined to achieve imaging of the heart within a single patient breath-hold. Part I is concluded by describing the two most commonly used cardiac MR imaging techniques; anatomical imaging using a double inversion, black-blood spin echo pulse sequence and bright blood functional cine imaging using either spoiled gradient echo or balanced steady state free precession (bSSFP) imaging pulse sequences.
Part II of this review aims to cover the remaining imaging techniques that are commonly used in cardiac MR imaging. There are many excellent texts that provide further in-depth coverage of the techniques discussed here[2–9]. Each technique can be considered as being based upon either the spin echo or gradient echo pulse sequences already described in part I, but with certain modifications applied to their contrast behaviour or mode of acquisition. Three main approaches to the modification of contrast behaviour are discussed. Firstly, it is shown how radiofrequency (rf) preparation pulses can be added to existing pulse sequences to alter their contrast behaviour: An inversion pulse added to a black-blood FSE/TSE pulse sequence enhances T1 and T2 weighted contrast for imaging of myocardial oedema. A fat suppression pulse added to an existing pulse sequence selectively suppresses the MR signal contribution from lipid based tissues, thus improving the delineation of non-lipid based structures. More complex preparation pulses may also be added to the cine gradient echo pulse sequence to apply a line or grid pattern to achieve myocardial tissue tagging that allows visualisation of intra-myocardial motion[12, 13].
The second method of modifying the MR contrast behaviour is through the intravenous administration of an endogenous contrast agent, based on the paramagnetic Gadolinium (Gd) ion. This contrast agent is used in two of the key CMR applications for the imaging of ischaemic heart disease; myocardial perfusion imaging[15, 16] and late gadolinium enhancement (LGE) imaging[17, 18]. Both of these techniques combine the use of preparation pulses and the administration of a Gd-based contrast agent to achieve T1 contrast weighting. The use of contrast agent also provides the basis of contrast enhanced MR angiography (CE-MRA) which is now in widespread use to image most major vessels outside the heart. Magnetic resonance angiography techniques that do not make use of Gd-based contrast agent are also summarised. Imaging of the coronary arteries is most commonly performed without the use of contrast agent. The most common approach, performed with the patient free-breathing and using navigator echoes for gating of the respiratory cycle[20, 21], is described in detail.
The third contrast mechanism that is discussed in this review differs somewhat from the first two. Whereas for all of the techniques discussed so far, the MR image pixel intensity depends on the magnitude of the MR signal intensity, for phase contrast techniques the image pixel intensity is related to the phase of the MR signal. In this section it will be shown how the imaging gradients can be used to encode the velocity of blood flowing along a particular gradient direction to generate a relative phase change that is proportional to velocity[22–24]. This provides a quantitative measure of blood velocity and blood flow and has particular application in valvular and congenital heart disease.
All of the above techniques make use of the segmented k-space fast imaging techniques (either turbo/fast spin echo or turbo/fast gradient echo) described in part I to ensure that image acquisition can be performed within an acceptable breath-hold period, or in the case of perfusion imaging, within a single heart beat. A number of other acceleration techniques are used to further reduce acquisition times to provide shorter breath-hold periods or to improve temporal and spatial resolution. Although a detailed description of these techniques is beyond the scope of this review, they are briefly summarised in the following section.
More acceleration techniques
Reduced matrix in the phase encoding direction
Reduced field of view in the phase encoding direction
Half -Fourier acquisition
Rectangular FOV (RFOV)
Parallel imaging techniques are mainly used to reduce imaging time, especially to shorten breath-hold periods, but may also be used to improve either temporal or spatial resolution for the same imaging time. There are however drawbacks of parallel imaging: The image signal-to-noise ratio is reduced according to the square root of the reduction factor. For a reduction factor of 2, this results in a reduction of the signal-to-noise ratio by approximately 30 %, and so parallel imaging should only be applied when the image signal-to-noise ratio is sufficient to accommodate such a reduction. Furthermore, if the field of view in the phase encoding direction is set too small, residual aliasing or foldover artefacts will appear at the centre of the image which cannot be removed by the parallel imaging reconstruction, so careful selection of the field of view and image orientation is needed. The phase encoding direction in which the parallel imaging reduction factor is applied must also always be chosen along a direction where there is a favourable distribution of array coil elements. Otherwise the reconstruction will fail leading to high noise levels at the centre of the image.
More recently k-space under-sampling techniques that make use of information that is repeated over time have been developed for cine and dynamic imaging[31, 32] and are being translated into products.
Adding preparation pulses to modify contrast
Preparation pulses – general principles
STIR, Triple IR and oedema imaging
Frequency selective fat suppression
Cine myocardial tagging with spatial modulation of magnetisation (SPAMM)
On the first image of the cine series (immediately after the tagging pulse), the magnetisation pattern appears as a series of low-signal-intensity parallel lines across the image where the magnetisation has been saturated. As the heart contracts through systole the magnetisation pattern deforms as it follows the contraction of the myocardial muscle (Figure6b). As the pattern is generated through saturation of the tissue magnetisation, T1-relaxation causes the magnetisation to return towards its equilibrium value. At the same time the tissue magnetisation at equilibrium becomes partially saturated by the rf pulses applied as part of the cine imaging sequence. These two effects cause the magnetisation of the tagged and untagged tissue to converge, resulting in a rapid loss of contrast for the tagged lines and fading of the tagging pattern during the cardiac cycle. The rate at which contrast is lost can be reduced by ensuring a low flip angle is used for the cine gradient echo pulse sequence, and by limiting the number of cine frames. Typically two line patterns are generated at right angles to form a grid pattern. This can be done by using two tagging preparation pulses within the same acquisition (known as grid tagging), or by performing two separate acquisitions with line tagging at right angles, and subsequently combining the two data sets as a post-processing step.
SPAMM is the most well established of the methods used to perform CMR tagging and it is derivatives of this basic method that are implemented by the MR vendors for use in routine clinical practice, with visual assessment being the main method of analysis. There have been many further developments of CMR tagging techniques in the research domain, together with methods used to analyse the tagged images, and many of these are described in the recent review.
Using exogenous contrast agents to modify contrast
MR Contrast Agents
Extra-vascular, extra-cellular contrast agents are most commonly used in clinical practice. These agents are small enough to leak through the capillaries from the vascular space into the extra-vascular, extra-cellular space but not through cell membranes. It is this property of the contrast agent that enables late gadolinium enhancement of myocardial infarcts where the extravascular, extracellular space is enlarged (see later). Intravascular contrast agents, which stay within the vascular space, are less commonly used but may be preferable for quantitative perfusion imaging as they allow simpler mathematical models to be used for flow quantification as no account needs to be taken of leakage from the vascular space.
Myocardial perfusion imaging
Myocardial perfusion imaging assesses the blood supply to the myocardium and plays an increasing role in the diagnosis of ischemic heart disease. In this section dynamic contrast enhanced MRI (DCE-MRI) is introduced and the challenging requirements for performing it in the heart are described with reference to pulse sequences described in previous sections. A discussion of the necessary trade-offs that should be considered when designing a perfusion imaging protocol is given. Finally quantification of myocardial blood flow (MBF) from perfusion DCE-MRI datasets is discussed considering the further imaging constraints required for this purpose.
Dynamic Contrast Enhanced MRI (DCE-MRI)
The essential requirements of a DCE-MRI cardiac perfusion imaging sequence can therefore be summarised as follows: All data for multiple images must be acquired within a single heart beat and the effects of cardiac and respiratory motion must be minimised. In addition the image contrast must be T1-weighted to maximise the effect of the contrast agent on image signal intensity. In order to fulfil these requirements, the choice of pulse sequence, method of contrast generation and approaches to minimise motion effects must be carefully considered.
Choice of acquisition pulse sequence
Comparison of the properties of the pulse sequences most commonly applied to cardiac perfusion DCE-MRI
hybrid EPI + FGE
Use of preparation pulses for T1-weighting
DCE-MR images should be T1-weighted in order to maximise the effect of the contrast agent on signal intensity. To reduce acquisition time the FGE and segmented EPI sequences described above employ small flip angles and very short TRs resulting in poor T1-contrast, while the bSSFP sequence using a higher flip angle is weighted by the ratio of T2/T1. For this reason a preparation pulse is applied prior to the read-out pulse sequence with a sufficiently long preparation pulse delay to establish a high T1-contrast before the read-out sequence is employed. Currently perfusion imaging is usually carried out using a saturation recovery preparation pulse as inversion recovery increases the total scan time, and is more vulnerable to R-R variation.
Reduction of cardiac and respiratory motion effects
In perfusion imaging each single-shot image acquisition is acquired quickly enough to avoid the detrimental effect of cardiac motion on each individual image. However, respiratory motion still causes mis-registration between adjacent temporal frames. It is typically dealt with by patient breath-holding as the requirement to acquire a dynamic series of images in contiguous heart beats rules out other methods such as respiratory gating. ECG-triggering is also still required to ensure that data acquisition for each image slice is performed at the same point in the cardiac cycle in successive heart beats so that cardiac motion appears frozen when the images are viewed as a dynamic movie.
For visual analysis of perfusion defects the T1 weighting can be optimised to maximise T1 contrast during the passage of contrast agent through the myocardium. However, if the same image data is to be used for quantitative assessment of myocardial blood flow (MBF), the T1-weighted contrast that is ideal for visual analysis introduces non-linearity in the relationship between the signal intensity and the higher concentrations of the Gd contrast agent found in the blood pool, leading to errors in the quantitation of MBF. For the detection of sub-endocardial perfusion defects there is a requirement to maximise spatial resolution but this increases the acquisition time for each slice which renders the acquisition more prone to cardiac motion and limits the number of slices that can be acquired within a heartbeat, thus limiting coverage of the left ventricle. As the acquisition of sufficient slices to cover the whole heart is desirable, this could be achieved by acquiring an increased number of slices over more than one heart beat, but this increases the time between acquisition of successive images in the dynamic series. For quantitative imaging in particular, it is important to achieve a temporal resolution equal to the acquisition of an image every heart beat. Consideration also needs to be given to the time point in the cardiac cycle that the image data for each is acquired.
These competing factors must be balanced in order to create the ideal pulse sequence for the specific purposes of the study they are being acquired for.
T1-weighting and TS
T1 weighting is controlled by careful selection of the saturation time (TS). Typically each imaging slice is preceded by a preparation pulse so that there are as many preparation pulses as there are slices in a given RR-interval. To maximise T1-contrast for visualisation of perfusion defects within myocardium longer saturation times should be used. However unnecessarily long TS values take up too much of the RR-interval and limit coverage (by restricting the number of slices that may be acquired) and/or spatial resolution (by limiting the length of the data acquisition per slice). Furthermore if the images are to be used for quantitative imaging shorter TS values are preferable to minimise the non-linearity in the relationship between CA concentration and signal intensity (See later). A typical TS for cardiac perfusion imaging is around 100 ms, but a wide range of values have been used for the reasons described above.
Factors affecting trigger delay (TD)
Coverage and resolution
Myocardial perfusion image analysis
Factors relevant to quantitation of myocardial blood flow
Semi-quantitative analysis uses a specific property of the time-intensity curve, such as peak height or maximum upslope, as an index of MBF and has been shown to be diagnostically effective[54, 55]. Quantitative methods aim to derive an absolute MBF value in ml/min/g by fitting the curves to a mathematical model describing the flow of contrast agent through the myocardium[51, 56].
Non-Linearity effects at high Gd concentrations
Nonlinearity depends on the dose and injection rate of the administered contrast agent, the type of MR pulse (EPI, FFE, SSFP) and the saturation time (TS).
Acquisition protocols for quantitative perfusion imaging attempt to optimise these factors to ameliorate the effect of this non-linearity on the MBF estimate. The simplest method is to simply administer a low dose of contrast agent so that the relationship between MR signal intensity and Gd concentration is in the approximately linear region (Figure16). Contrast agent doses need to be around 0.01 mmol/kg to ensure linearity in the blood pool. These low doses reduce the CNR and SNR of the images rendering visual analysis (still the main-stay of clinical reporting) difficult. The myocardial curve enhances less dramatically than the AIF due to the lower concentration within the myocardium and such low administered doses can reduce the change in signal in the myocardium to such an extent that MBF estimates become significantly affected by image noise, compromising the precision of the MBF estimate. Approaches that try to overcome these issues include mathematical conversion of SI to CA concentration[59, 60], dual bolus strategies that repeat the experiment using low contrast and high contrast doses[61, 62], and dual sequence strategies that repeat the experiment using two pulse sequences optimised for the blood-pool and myocardial curves.
The dark rim artifact (DRA)
Causes and solutions of DRA
Under-sampling of high frequency data causes signal oscillations at high contrast boundaries
Increase image resolution:
a) Increase number of phase encoding lines with increased image time.
b) Use parallel imaging, with decreased SNR
Increased magnetic field distortions at boundaries and due to arrival of CA cause signal loss and voxel mismapping
a) Avoid bSSFP
b) Decrease CA concentration
Discontinuities in k-space due to motion translate to banding at boundaries in the image.
a) Use sequential k-space ordering.
b) Use parallel imaging
Delayed imaging after contrast administration
Delayed Gadolinium Enhancement (DGE) imaging is one of the principal CMR techniques. It has been extensively validated, both in animal models and in clinical studies[68–70]. The technique itself is remarkably simple and robust: it involves intravenous administration of gadolinium-based contrast agent followed by the acquisition of T1 weighted images of the myocardium using an inversion recovery technique. DGE imaging is a powerful tool for the assessment of a wide and still expanding range of cardiac pathologies, from acute and chronic myocardial infarction, through inflammatory or infectious myocardial diseases, to cardiac neoplasms[71, 72].
Depending on the timing of the acquisition relative to contrast administration, there are two distinct subtypes of the DGE imaging: Early Gadolinium Enhancement (EGE) and Late Gadolinium Enhancement (LGE). These two sub-types of DGE are essentially the same, but the timing of the acquisition (ta) following intravenous administration of the contrast agent (0.1 to 0.2 mmol/kg of an extravascular gadolinium chelate) is a distinguishing factor that influences image contrast and provides insights into different aspects of myocardial pathology. Whilst typically ta ~ 5 min post injection is used for EGE, ta > 10 min is used for LGE.
Before describing the nature of temporal changes in longitudinal relaxation time T1 within LV blood and normal and pathological myocardial tissue following intravenous contrast administration, a brief outline of the use of the DGE technique in its primary setting (characterization of myocardial scarring after myocardial infarction) is presented. Temporal changes in T1 and associated changes in signal intensity in inversion recovery T1-weighted images acquired at different times post- injection will then be illustrated using a generalised model of different tissue compartments in DGE studies.
The identification of scarred myocardial tissue in patients with acute or chronic myocardial infarction is one of the most important clinical applications of CMR. This method is referred to as “viability imaging” as the absence of scar indicates that the myocardium is viable, i.e. that it retains a capacity to recover contractile function following revascularisation. The information on the location and the extent of myocardial scaring is therefore important for planning coronary artery revascularisation. As the size of scarred myocardium and its location relative to the endocardial border are important predictors of the potential for functional recovery, CMR assessment of myocardial viability by DGE has an inherent advantage over other imaging methods (such as PET, SPECT and echocardiography) due to its superior spatial resolution.
In addition to the identification of the location and the extent of scarred tissue by LGE, EGE provides important diagnostic information about the presence and the extent of microvascular obstruction (MVO). MVO is also known as the no-reflow phenomenon and its presence serves as a significant negative predictor of functional recovery post percutaneous coronary intervention (PCI).
Areas supplied by patent coronary vessels and occupied by a dense capillary network will exhibit strong enhancement of the MR signal during first pass of the contrast agent, as the local concentration of contrast agent carried by blood will cause strong acceleration of longitudinal relaxation (T1 decrease), and consequent pixel intensity increase on T1-weighted images (Figure8).
Another important process takes place at the same time: extravasation of the contrast agent and its accumulation within the extravascular extracellular (interstitial) fluid. Areas with an increased volume of interstitial space will present a larger distribution volume for the incoming contrast agent, but importantly pathological tissues such as myocardial scar, may also display slower extravasation rates as well as delayed re-absorption (wash out) of contrast agent into the vascular space (Figure17).
This is why scarred tissue contains high concentrations of contrast agent compared to normal (viable) myocardium several minutes after bolus administration. It is this difference in delayed local tissue concentration within the interstitial fluid that gives rise to image contrast on what is generally referred to as delayed gadolinium enhancement CMR: scarred myocardium appears relatively hyperintense compared to surrounding viable myocardium on T1-weighted images. This same principle applies to acute infarction and fibrosis as well as chronic scar with each appearing bright on LGE images.
To maximise the effect of these differences in contrast agent concentration, the image readout needs to be timed to coincide with the point at which the difference between viable and scarred tissue concentration is most pronounced and optimal T1-weighting needs to be achieved to translate these concentration differences into strong image contrast.
The following sections describe how the changes in contrast agent concentration affect T1 values of LV blood, normal myocardium, scar and MVO, and how T1 values change over time. They will also describe the effect those changes have on MR signal intensity, and how to achieve image contrast suitable for the delineation of scar and MVO.
Time-related changes in T1
Although differences in native T1 values between normal myocardium and regions affected by different pathological processes exist in the pre-contrast state, they tend to be subtle and difficult to measure using currently available techniques. Following the administration of an intravenous contrast agent various tissues experience different degrees of T1 shortening, and the assessment of these changes in native tissue T1 enables us to distinguish between normal myocardium and various pathologies.
The differences in the temporal pattern of the return to the pre-contrast state, and the extent of the SI changes, give a very powerful (if indirect) measure of the local tissue haemodynamics and water content. Of course, systemic factors could potentially obscure this process of differentiation and must therefore be taken into account.
Although the exact mechanisms behind the complex contrast patterns that characterise EGE and LGE in particular are still not fully understood, it is helpful to try to explain them in the context of two distinct phases of extracellular contrast agent pharmacokinetics, namely early access phase (EGE) and late distribution phase (LGE). To illustrate the principal contrast-inducing process (contrast agent induced temporal T1 changes), a set of measurements adopted from a study by Klein et al. will be used.
Following bolus injection of T1-shortening contrast agent, a transient sharp increase in the blood signal (arterial input function peak) is followed by several oscillations (recirculation peaks) after which a gradual approach to equilibrium occurs. In the equilibrium the concentration of contrast agent in the circulating blood is in balance with the concentration in the interstitial compartment (Figure17).
In areas occupied by MVO, a very modest amount of contrast agent is present at 5 min post-injection, and the T1 value within the MVO is high compared to the other three compartments at this time point.
The rate of recovery towards the baseline (pre-contrast) T1 value reflects the washout of contrast from individual compartments. Whilst normal myocardium and LV blood T1 values continue to rise between 5-15 min post-injection, scar tissue still maintains low T1 values, due to delayed extravasation and accumulation of contrast agent within an enlarged interstitial water compartment (Figure18). The low values of T1 may further be maintained by the slow washout kinetics.
In MVO, T1 values may continue to decrease, as the areas occupied by MVO may receive contrast agent via passive diffusion from the neighbouring scar.
Pulse sequences for EGE and LGE
In CMR perfusion imaging signal acquisition needs to be performed during the first pass of the contrast agent through the myocardial capillary bed. The contrast agent concentration changes very rapidly during this time, thus requiring a dynamic imaging technique using an ultra-fast single shot acquisition pulse sequence (see previous section on perfusion imaging). In DGE the signal collection is performed during the equilibrium phase of contrast agent kinetics when the concentration of contrast agent changes relatively slowly and image data acquisition over several heart beats using a cardiac-triggered, multi-shot imaging pulse sequence is therefore possible. This means that high spatial resolution DGE images can be acquired, a factor that is important for accurate delineation of scar size and especially its transmural extent.
With the readout timing limitation (150 to 200 ms) and a typical TR of 5-10 ms, 15 to 40 lines of k-space can be acquired within a single data acquisition window. A typical acquisition matrix is 240 x 240, which yields DGE images with a voxel size of 1.75 mm, for a FOV of 420 mm.
Each image data acquisition is preceded by a non-slice-selective inversion recovery preparation pulse to provide T1-weighting. As well as producing strong T1 contrast, the inversion recovery (IR) technique has the additional benefit that is it is possible to suppress the signal from tissue of a particular T1. Careful choice of the time delay after inversion, TI, allows the optimisation of contrast between tissues with different contrast agent concentrations including selective suppression of one of these tissues. The TI value is either fixed (~440 ms, as in EGE) or determined empirically for LGE applications (see next section).
With this choice of timing for the inversion pulse (Figure19), the z-magnetisation for the tissue with longer T1 (red line) will be close to zero at the time of the readout. The voxels occupied by tissues with this T1 value will therefore have very low SI on MR images (i.e. this T1 value will be “suppressed” or “nulled”).
In a typical LGE exam, 10–12 breath hold slices are acquired in short axis orientation, followed by long axis and 4-chamber views where clinically indicated. The choice of TI needs to be periodically updated if the examination is prolonged to ensure optimal nulling of the normal myocardial tissue, as the T1 of the normal myocardium will continue to increase gradually during this time.
Optimising T1 contrast in EGE an LGE
The image contrast between different tissue compartments is controlled by choosing an appropriate inversion time, TI to highlight the differences in their T1 values. This implicitly highlights the differences between time-variant concentrations of Gd-DTPA in individual tissue compartments, as described in the earlier section. As LV blood pool and scar have very similar T1 values between 5–15 minutes post contrast, their recovery curves closely follow each other. Separation of scar and blood pool signal is therefore difficult to achieve. However, an appropriate choice of TI will highlight the differences between MVO and normal myocardium in EGE. In LGE, the TI can be fine-tuned to emphasize the differences in T1 of normal myocardium and scar.
In EGE, the difference between T1 in the MVO compartment and surrounding scar and normal myocardium is emphasized by using a long TI which minimises the signal from the MVO. In the example presented in Figure18, a TI of 440 ms will null the signal from MVO (T1 = 640 ms at 5 minutes post-injection). With this choice of TI, surrounding scar and normal myocardium appear bright, thus enabling identification of MVO (Figure20, left panel).
At 10 and 15 minutes post-injection, the differences in T1 between normal myocardium and scar begin to emerge due to delayed accumulation of contrast in the enlarged interstitial space of the scar. To maximise contrast between scar and normal myocardium, a TI of 300 ms is chosen to null the signal from normal myocardium at 10 min LGE images (Figure20, middle panel). As T1 values continue to change between 10 and 15 minutes post injection, the optimal nulling time rises to 320 ms in at 15 minutes post-injection for the example presented above (Figure20, right panel).
Overall signal levels continue to decrease during the late enhancement phase as LV and normal myocardium continue their return to their pre-contrast (long) T1 values.
Selection of TI for optimal LGE imaging – the ‘TI scout’
The main practical difference in the acquisition of EGE and LGE is that LGE is preceded by a TI-sweep Look Locker module, designed to find the optimal inversion time TI to null the signal from the normal myocardium and maximize the contrast between normal myocardium and scar tissue.
The exact value of this parameter will depend on the individual haemodynamics and systemic water compartmentalisation that will define global contrast agent kinetics in individual patients. The optimal TI will also change over time, as T1 values in all four compartments continue to change. Whilst LV blood and normal myocardium T1 values continue their recovery towards their baseline (pre-contrast values) during this late enhancement phase, T1 values in scar tissue and MVO follow a different pharmacokinetic path determined by the volume of the interstitial space, wash-in and wash-out rates and, in the case of MVO, passive diffusion of contrast from the surrounding scar tissue.
For example, the optimal TI that will suppress the signal from normal myocardium will be 300 ms at 10 minutes post-injection in the example presented in Figure18, but at 15 minutes post-injection, the optimal TI will be 320 ms (Figure20).
As exact values of T1 in individual tissue compartments are not known ahead of IR-GRE acquisition, optimal values of TI need to be determined empirically. In the T1-sweep Look Locker module, TI values are changed incrementally before each image readout. The resulting images display different contrast between the four compartments, and allow the operator to identify the TI which best minimises the signal from normal myocardium.
Alternative DGE pulse sequences
Although the standard IR-FGE sequence combined with a modulus image reconstruction is still the most widely used in clinical practice, there are other approaches that aim to address different shortcomings of this standard approach.
As the polarity of the signal is restored, relative signal levels between normal myocardium and scar can be captured over a wide range of inversion times, and precise estimation of TI via a TI Scout module is no longer necessary.
By collecting the IR prepared signal in a 3D mode, significant savings in imaging time can be achieved[80, 81] However, the required readout window is longer compared to 2D and the spatial resolution is significantly reduced too. To offset these drawbacks, navigated free-breathing approaches have been proposed[82, 83].
In addition to these efforts directed at collecting DGE images in a more time-efficient manner, there is an ongoing research into alternative signal preparation schemes that would improve the contrast between scarred and normal myocardium, as well as scar and blood[84, 85]. With a wider use of parallel imaging, further refinements in both DGE preparation and readout are likely to emerge in the coming years.
Magnetic Resonance Angiography (MRA)
In this section, three different approaches to performing MR angiography will be described. First, the most common approach, known as contrast enhanced MR angiography (CE-MRA) involves the use of a Gadolinium-based contrast agent to delineate the vessel lumen and is an extremely fast and reliable method for imaging the vasculature outside the heart. Due to concerns relating to the use of contrast agents in patients with poor renal function, there has been a resurgence of non-contrast MRA techniques to image vasculature outside the heart. The exact approach is dependent upon the vessel to be imaged, but this section provides a brief overview of the currently available methods. For all of the above MRA methods, image degradation caused by respiratory motion within the thorax and abdominal regions is eliminated by performing the acquisition during patient breath-holding. However this limits the acquisition time and hence the spatial resolution of the method. For imaging of the coronary arteries, their relatively small diameter, together with significant motion during the cardiac cycle, make the standard MRA techniques ineffective. The final part of this section describes the most common approach to coronary MRA, respiratory navigator-gated 3D coronary angiography. This is performed without the use of contrast agent over several minutes to achieve higher spatial resolution. Respiratory motion is compensated for by accurately gating the acquisition with respect to the respiratory cycle by using special navigator rf pulses to accurately track diaphragm position, while the influence of cardiac motion is removed by using ECG triggering to synchronise the data acquisition to mid-diastole.
Contrast-enhanced MRA (CE-MRA): the basic principles
In order to perform CE-MRA successfully it is important to understand the practical implications of the above requirements. The following sections will explain the basis of choosing the volume and duration of the bolus injection, timing the image acquisition to coincide with the first pass phase of the contrast medium and selecting a suitable pulse sequence and its parameters to provide a sufficiently rapid data acquisition whilst maintaining good contrast, 3D coverage and spatial resolution.
The basis of image contrast in contrast-enhanced MRA (CE-MRA)
Conventional T1-weighted anatomical imaging using spin echo or spoiled gradient echo pulse sequences is achieved using a short TR and a short TE. For both these techniques, the TR is chosen so that there is good contrast between most of the tissues, and most of the tissues (apart from fluid) will contribute a reasonable signal. For CE-MRA, much shorter TR values are used. In this case, the signal from all of the tissues, including fat, is significantly reduced. High signal intensities only exist where the contrast medium is present at sufficiently high concentrations.
The concentration of contrast agent during first pass, cfirst pass required to reduce the T1 of blood to around 50 ms can be calculated using the relationship described in the early section on contrast agents, which relates T1 relaxation rate to the concentration of contrast agent of a given relaxivity, r1. For most currently available gadolinium-based contrast media, the T1 relaxivity is approximately 0.004 ms-1 mM-1 for field strengths of 1.5 T. Estimating the T1 of blood without contrast agent as 1200 ms, the required concentration can be estimated to be around 5 milliMolar (mM).
The original concentration of the contrast medium (from the bottle) depends on the particular contrast agent used, but a typical value might be 0.5 mmol/ml. (=0.5 mol/l = 0.5 Molar concentration), which is about 100 times too high. Once injected, however, the initially high concentration of contrast medium within the bolus becomes diluted as it travels from the injection site by gradual mixing with the blood pool as it travel first though the right side of the heart, the pulmonary circulation and then the left side of the heart.
where Cbottle is the original concentration of the contrast medium (from the bottle). For a typical person the cardiac output is around 6 litres/minute, which is equal to 100 ml/s. Using the above relationship to achieve the desired dilution of Cfirst pass / Cbottle = 1/100, the required injection rate must be around 1 ml/s. In clinical practice, injection rates of between 1–5 ml/s are in use. An increase in injection rate results in a higher concentration of contrast agent during the first pass, further reducing the T1 of blood and increasing the signal intensity within the vessels. The duration of injection will determine the duration of the contrast bolus. Ideally, this should match the acquisition time of the MR pulse sequence. The injection rate and the duration of injection together determine the volume of contrast agent delivered and therefore the dose. Each of these parameters needs to be carefully balanced to avoid giving the patient unnecessarily large doses of contrast agent, while maximising signal intensity. There is clearly an advantage in choosing acquisition techniques that can achieve shorter acquisition times, leading to a shorter duration of injection and lower contrast dose without compromising the injection rate.
There is also an effect of the contrast medium upon the T2 relaxation time, which is determined by the T2 relaxivity, r2. For field strengths from 0.5 to 1.5 Tesla, r2 is approximately 0.006 ms-1 mM-1. If it is assumed that the T2 of blood without the contrast medium is approximately 200 ms, then by a similar calculation, the observed T2 of the arterial blood during first pass is approximately 28 ms. The T2 of the blood is therefore also considerably shortened, but not by the same proportion as the T1. To minimise any signal loss caused by the reduction of the T2 value of the blood, the echo time of the pulse sequence must be kept as short as possible. As a rule of thumb, provided that the T2 is greater than two times the TE, signal loss due to T2 effects will not be significant, except in regions where the concentration is closer to the original concentration within the injected vein. This is often seen as signal drop-out within the vein close to the site of injection.
The CE-MRA pulse sequence
Key pulse sequence parameters for CE-MRA
Influence of geometry parameters for CE-MRA acquisitions
How is it chosen?
What is the limitation/ disadvantage?
Acquisition Matrix, NR, in the readout direction (Base Resolution)
256 Minimum Increase to 512 preferred
To get best resolution in readout direction
512 matrix increases TE and therefore TR. (increases scan time)
Acquisition Matrix, NP, in the phase encoding direction
To get best resolution in phase encoding direction
Increases Scan time (directly proportional)
(depends on breath-hold period)
SNR decreases as square root of increase
No of slices, NS
Increases coverage of volume thickness
Scan time (increases proportionally)
(depends on breath-hold period, slice thickness and FOVS
Increases SNR as square root
(fixed slice thickness)
Slice thickness, THK
Minimise for best resolution in the slice direction
Increases through-plane resolution
FOVS = THKxNS
Decreases SNR (directly proportional)
Field of View (FOVR)
Optimise for desired in-plane coverage
Aim to get best in-plane resolution without getting too much foldover
If too small, foldover becomes a problem.
SNR decreases with FOVR (proportional to square).
Rectangular Field of View factor (RFOV)
Minimise for desired coverage in phase encoding direction
Reduces scan time
Foldover is increased
FOVP = RFOVxFOVR
(NP reduces in same proportion as RFOV)
SNR is decreased
(Proportional to square root)
Zero filling/ interpolation
Apply in the slice direction
Doubles the number of reconstructed slices (but doesn’t improve resolution)
In general SNR is proportional to the voxel volume and the square root of the number of phase encoding steps, while the spatial resolution is directly related to the voxel dimensions. For a 3D acquisition, the voxel dimension in the phase encoding direction is equal to the field of view in that direction divided by the number of pixels NP in that direction, while the voxel dimension in the slice encoding dimension (the slice thickness) is equal to the field of view in that direction divided by the number of pixels (or slices) in that direction, NS.
For a given field of view, increasing NP and NS gives a proportionate improvement in spatial resolution in each direction, but also increases the scan time in proportion to the product of the two. In each case the SNR is also decreased (proportional to the square root of NP and NS). This is because the increase in SNR caused by the increased signal sampling (proportional to the square root of the product of NP and NS) is more than offset by the decrease in SNR caused by the reduction in voxel volume (directly proportional to the product of NP and NS).
Given the above constraints the best way to minimise the acquisition time whilst achieving high spatial resolution is to make the TR, and consequently the TE, as short as the MR system hardware and software will allow. The use of low flip angles, described in Part I, together with the reduction of T1 relaxation times by the use of contrast agent makes extremely short TR values of less than 5 ms possible.
The flip angle is chosen to maximise the signal for a particular TR and T1 value (known as the Ernst angle). In practice flip angle values in the range 30°-40° which are slightly higher than the Ernst angle are used to improve the saturation of the background tissues and hence maximise the contrast between them and the vessels.
Timing of the start of acquisition after contrast injection
The MR fluoroscopy technique may use either a manual or automated trigger to start the CE-MRA acquisition. The manual trigger method is based upon visual bolus detection. In this case, a single thick slice is positioned to include the vessels of interest and images are acquired and updated continually with a one second temporal resolution. There are a number of potential advantages of this approach. First, the operator watches for the arrival of the contrast agent and triggers the 3D CE-MRA acquisition manually at the appropriate time. The operator therefore gains an impression of how fast the circulation is. This is useful in patients with extremely slow flow (typically patients with abdominal aortic aneurysms) in whom triggering of the 3D acquisition as soon as contrast arrives within the upper abdominal aorta would result in artefacts due to delayed filling of the iliac arteries. As a single thick slice is used for bolus detection, the slice encompasses a large amount of the anatomy. Therefore, sequential enhancement of the right side of the heart, pulmonary circulation, left heart chambers and aorta is easily visualized. This sequential enhancement is useful as the operator has more warning to co-ordinate the breathing instructions accordingly. The scanner briefly falls silent after aborting the 2D fluoroscopic scan. Communication with the patient for the instruction to breath-hold is therefore unhindered. Real-time subtraction of the 2D fluoroscopic images eliminates the background tissue signal and improves visualization of contrast arrival.
For the automated triggering approach the MR system continuously monitors the signal intensity within a single large voxel placed over an artery (e.g. upper abdominal aorta) within the region-of-interest (ROI). The scan is triggered when the signal intensity rises above a predetermined threshold value, indicating the arrival of contrast medium in the selected artery. This approach removes user dependence from the process but there is no possibility for the operator to interactively select a slightly longer scan delay time, for example in a patient with extremely slow flow in whom there may be a prolonged delay between arrival of contrast within the upper abdominal aorta and the iliac arteries.
Time-resolved contrast-enhanced MRA techniques
Non-Contrast Enhanced MRA techniques
Non-contrast-enhanced MRA (NCE-MRA) techniques rely on changes in the MR signal that are caused by the motion of blood through or within the image plane. There are three principal flow effects that can occur, depending on the pulse sequence that is being used: The spin washout effect described in Part 1 of this review gives a ‘dark’ or ‘black’ blood appearance and is characteristic of spin echo pulse sequences. This effect has sometimes been used as the basis for ‘black blood‘ angiography. The second effect, flow-related enhancement, gives rise to the bright blood contrast observed with spoiled gradient echo pulse sequences and is also described in Part 1. This is the principal effect that is used as the basis for time-of-flight (TOF) MRA which for body applications has been largely replaced by CE-MRA, but still has some application in the head for imaging of the circle of Willis and the sagittal sinus[97, 98].
The third effect, phase-related signal loss gives rise to the appearance of signal voids in cine gradient echo pulse sequences in the presence of flow jets and turbulence. This is due to the intrinsic flow sensitivity of pulse sequences and is described in more detail in the flow velocity mapping section (see later). The same principle that causes this signal loss is used as the basis for phase contrast angiography or PCA[99, 100]. In this case, the gradient pulses are designed to produce phase changes which are typically less than 180° for a given velocity range. In this way, the signal is not completely de-phased, and the phase information is preserved during the image reconstruction. Since the phase of the signal can depend on many factors, it is necessary to perform at least two acquisitions so that the phase changes due to the other factors can be removed by subtracting one image acquisition from the other. In practice, an image data set is first acquired using a pulse sequence that is relatively insensitive to flow (or flow compensated), followed by one that is sensitive to flow over a particular range of velocities in one chosen direction. To image blood flow in all three directions the flow sensitive acquisition is repeated in each of the other two directions. The signal data from the flow compensated acquisition is then subtracted from each of the flow sensitive acquisitions, giving a phase contrast image for each flow direction. Since the phase is unchanged for static protons, the subtraction completely suppresses the signal from the background tissue. The final step in the image reconstruction is to combine the phase contrast data sets for each direction to calculate a ‘speed’ image. The signal intensity on PCA images is related to velocity. The operator prior to the scan sets the flow sensitivity of the pulse sequence by defining the maximum velocity range (VENC; +/− max velocity).
More recently, the same principle used for PCA has been modified to provide a NCE-MRA technique to image the peripheral arteries, exploiting the difference in flow velocities between systole and diastole. Whereas PC-MRA is normally used in combination with a 2D or 3D gradient echo pulse sequence, this method uses two 3D fast (or turbo) spin echo acquisitions, synchronised first to systole and then diastole[98, 99, 101]. Phase-related signal loss relating to higher velocities in systole is not present in diastole and the difference in signal is used to generate an arteriogram by subtraction of the two data sets. Techniques that apply this principle are now available commercially, implemented as Flow-Spoiled Fresh Blood Imaging (FBI) by Toshiba, Native SPACE MRA by Siemens, TRANCE by Philips and InHance 2D Inflow by GE.
A further recent development is the use of both 2D and 3D bSSFP pulse sequences to perform NCE-MRA[19, 99]. The combination of their intrinsically high signal from blood and the use of fat suppression techniques provides a simple, flow-independent method of imaging vessels. Vendor implementations of this approach include FIESTA with Fat Sat, Balanced FFE with SPIR, True FISP with Fat Sat. The main disadvantage of this approach is that both the arterial and venous system is imaged, as well as other fluid-filled ducts, although the venous suppression techniques used in TOF-MRA can also be applied here to remove unwanted venous signal. Balanced SSFP techniques have also been combined with a technique known as arterial spin labelling (ASL) to provide high quality arteriograms of both the renal and carotid arteries[19, 98, 99]. Vendor implementations of this technique include time-SLIP by Toshiba, Native TrueFISP by Siemens, b-TRANCE by Philips and InHance Inflow IR by GE.
Coronary MRA with respiratory gating using navigator echoes
Flow velocity mapping
Intrinsic flow sensitivity of pulse sequences
Appearance of flow voids
Flow velocity encoding and velocity mapping
This inherent flow sensitivity is exploited to enable the quantification of blood flow velocity by generating images, known as phase maps, in which pixel intensity depends upon the phase of the transverse magnetisation, rather than its magnitude[23, 24]. There are however a number of potential causes of relative change in phase of the transverse magnetisation. These include phase changes due to motion along more than one gradient direction (arising from velocity components in these other directions) and phase changes due to magnetic field inhomogeneities.
The phase changes due to the above causes must be accounted for in order to isolate the change that is due to motion along the desired gradient direction. This is achieved by performing two consecutive acquisitions for each phase encoding step. The two acquisitions are identical other than that they have different flow sensitivities in the chosen direction of flow measurement, known as the velocity encoding direction. The flow sensitivity is determined by the amplitude, duration and time separation of the bipolar flow-encoding gradients in that direction. Once the image data acquisition is complete, phase maps from the two acquisitions are calculated and subtracted to produce a velocity map. The subtracted velocity map contains only phase shifts that are related to velocity components in the flow-encoding direction. Phase changes due to other causes, including velocity components in other directions and magnetic field inhomogeneities are removed by the subtraction.
This review has outlined the key physical principles that underlie the more advanced cardiac MR imaging techniques most commonly used in clinical practice. The basic principles of oedema imaging, myocardial cine tagging, myocardial perfusion, late enhancement imaging, magnetic resonance angiography and velocity mapping have been explained. Key imaging parameters have been defined, explaining their influence on image contrast, resolution and acquisition time. Where appropriate, common pitfalls have been discussed and the causes and remedies of common image artefacts have been explained. Further detailed reading is provided through the provision of key references. This review should be a useful resource from clinicians who wish to gain a greater understanding of the underlying physics of CMR.
The authors wish to thank Dave Higgins of Philips Healthcare for helpful discussions, Darach O h-Ici and Daniel Messroghli for providing the Oedema image example and John Greenwood (Multidisciplinary Cardiovascular Research Centre (MCRC) & Leeds Institute of Genetics, Health and Therapeutics) for providing the EGE and ischemic perfusion defect examples. Aleksandra Radjenovic is funded through WELMEC, a Centre of Excellence in Medical Engineering funded by the Wellcome Trust and EPSRC, under grant number WT 088908/Z/ 09/Z and is additionally supported by the NIHR (National Institute for Health Research) as part of a collaboration with the LMBRU (Leeds Musculoskeletal Biomedical Research Unit). John Biglands is funded by a National Institute for Health Research (NIHR) Research Training Fellowship (NIHR/RTF/01/08/014). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
- Ridgway JP: Cardiac magnetic resonance physics for clinicians: part I. J Card Magn Reson. 2010, 12 (1): 71-10.1186/1532-429X-12-71.Google Scholar
- Bogaert J, Dymarkowski S, Taylor A: Clinical Cardiac MR. 2005, London: SpringerGoogle Scholar
- Lee VS: Cardiovascular MR: Physical principles to practical protocols. 2005, Philadelphia: Lippincott Williams and WilkinsGoogle Scholar
- McGee K, Williamson E, Julsrud P: Mayo Clinic Guide to Cardiac Magnetic Resonance Imaging. 2008, Rochester: Mayo Clinic Scientific PressGoogle Scholar
- Biederman RWW, Doyle M, Yamrozik J: Cardiovascular MR Tutorial: Lectures and Learning. 2008, Philadelphia: Lippincott Williams and WilkinsGoogle Scholar
- Grizzard JD, Judd RM, Kim RJ: Cardiovascular MR in Practice: A teaching file approach. 2008, London: SpringerGoogle Scholar
- Manning WJ, Pennell DJ: Cardiovascular Magnetic Resonance. 2010, Philadelphia: Saunders, 2Google Scholar
- Myerson SG, Francis JM, Neubauer S: Clinical Cardiac MR. 2010, Oxford: Oxford University PressGoogle Scholar
- Plein S, Greenwood JP, Ridgway JP: Cardiovascular MR Manual. 2011, London: SpringerGoogle 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.PubMedGoogle Scholar
- Abbara S, Migrino RQ, Sosnovik DE, Leichter JA, Brady TJ, Holmvang G: Value of fat suppression in the MRI evaluation of suspected arrhythmogenic right ventricular dysplasia. AJR Am J Roentgenol. 2004, 182 (3): 587-91.PubMedGoogle Scholar
- Shehata ML, Cheng S, Osman NF, Bluemke DA, Lima JAC: Myocardial tissue tagging with cardiovascular magnetic resonance. J Card Magn Reson. 2009, 11: 55-10.1186/1532-429X-11-55.Google Scholar
- Ibrahim E-SH: Myocardial tagging by Cardiovascular Magnetic Resonance: evolution of techniques–pulse sequences, analysis algorithms, and applications. J Card Magn Reson. 2011, 13 (1): 36-10.1186/1532-429X-13-36.Google Scholar
- Caravan P: Cardiovascular magnetic resonance contrast agents. Cardiovascular Magnetic Resonance. Edited by: Manning WJ, Pennell DJ. 2010, Philadelphia: Saunders, 76-90.Google Scholar
- Kellman P, Arai AE: Imaging sequences for first pass perfusion –a review. J Card Magn Reson. 2007, 9 (3): 525-37. 10.1080/10976640601187604.Google Scholar
- Gerber BL, Raman SV, Nayak K, Epstein FH, Ferreira P, Axel L, Kraitchman DL: Myocardial first-pass perfusion cardiovascular magnetic resonance: history, theory, and current state of the art. J Card Magn Reson. 2008, 18 (10): 1-18.Google Scholar
- Simonetti OP, Kim RJ, Fieno DS, Hillenbrand HB, Wu E, Bundy JMM, Finn JP, Judd RM: An Improved MR Imaging Technique for the Visualization of Myocardial Infarction. Radiology. 2001, 218 (1): 215-23.PubMedGoogle Scholar
- Kim R, Fieno D, Parrish T, Harris K, Chen E: Relationship of MRI delayed contrast enhancement to irreversible injury, infarct age, and contractile function. Circulation. 1999, 100: 1992-2002. 10.1161/01.CIR.100.19.1992.PubMedGoogle Scholar
- Hartung MP, Grist TM, François CJ: Magnetic resonance angiography: current status and future directions. J Card Magn Reson. 2011, 13 (1): 19-10.1186/1532-429X-13-19.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 Coll Cardiol. 1999, 34 (2): 524-31. 10.1016/S0735-1097(99)00223-5.PubMedGoogle Scholar
- Nezefat R, Botnar RM, Kissinger KV, Hu F, Manning WJ: Coronary artery imaging methods. Cardiovascular Magnetic Resonance. Edited by: Manning WJ, Pennell DJ. 2010, Philadelphia: Saunders, 284-99.Google Scholar
- Van Dijk 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.PubMedGoogle Scholar
- Lotz J, Meier C, Leppert A, Galanski M: Cardiovascular Flow Measurement with Phase-Contrast MR Imaging: Basic Facts and Implementation. Radiographics. 2002, 22 (3): 651-PubMedGoogle Scholar
- Gatehouse PD, Keegan J, Crowe LA, Masood S, Mohiaddin RH, Kreitner K-F, Firmin DN: Applications of phase-contrast flow and velocity imaging in cardiovascular MRI. Eur Radiol. 2005, 15 (10): 2172-84. 10.1007/s00330-005-2829-3.PubMedGoogle Scholar
- Paschal CB, Morris HD: K-space in the clinic. J Magn Reson Imaging. 2004, 19 (2): 145-59. 10.1002/jmri.10451.PubMedGoogle Scholar
- Bradley WG, Tsuruda JS: MR Sequence Parameter Optimization: An Algorithmic Approach. AJR Am J Roentgenol. 1987, 149 (4): 815-23.PubMedGoogle Scholar
- Mezrich R: A perspective on k-space. Radiology. 1995, 195: 297-315.PubMedGoogle Scholar
- Glockner JF, Hu HH, Stanley DW, Angelos L, King K: Parallel MR Imaging: A User ’ s Guide. Radiographics. 2005, 25: 1279-97. 10.1148/rg.255045202.PubMedGoogle Scholar
- van den Brink JS, Watanabe Y, Kuhl CK, Chung T, Muthupillai R, Van Cauteren M, Yamada K, Dymarkowski S, Bogaert J, Maki JH, Matos C, Casselman JW, Hoogeveen RM: Implications of SENSE MR in routine clinical practice. Eur J Radiol. 2003, 46 (1): 3-27. 10.1016/S0720-048X(02)00333-9.PubMedGoogle Scholar
- Dietrich O, Nikolaou K, Wintersperger B, Flatz W, Nittka M, Petsch R, Kiefer B, Schoenberg S: iPAT: applications for fast and cardiovascular MR imaging. Electromedica. 2002, 70 (2): 133-46.Google Scholar
- Jahnke C, Nagel E, Gebker R, Bornstedt A, Schnackenburg B, Kozerke S, Fleck E, Paetsch I: Four-dimensional single breathhold magnetic resonance imaging using kt-BLAST enables reliable assessment of left- and right-ventricular volumes and mass. J Magn Reson Imaging. 2007, 25 (4): 737-42. 10.1002/jmri.20877.PubMedGoogle Scholar
- Guttman MA, Kellman P, Dick AJ, Lederman RJ, McVeigh ER: Real-time accelerated interactive MRI with adaptive TSENSE and UNFOLD. Magn Reson Med. 2003, 50 (2): 315-21. 10.1002/mrm.10504.PubMed CentralPubMedGoogle Scholar
- Delfaut EM, Beltran J, Johnson G, Rousseau J, Marchandise X, Cotten A: Fat suppression in MR imaging: techniques and pitfalls. Radiographics. 1999, 19 (2): 373-82.PubMedGoogle Scholar
- Bydder GM, Young IR: MR imaging: clinical use of the inversion recovery sequence. J Comput Assist Tomogr. 1985, 9 (4): 659-75. 10.1097/00004728-198507010-00002.PubMedGoogle Scholar
- Hashemi RH, Bradley WG, Chen DY, Jordan JE, Queralt JA, Cheng AE, Henrie JN: Suspected multiple sclerosis: MR imaging with a thin-section fast FLAIR pulse sequence. Radiology. 1995, 196 (2): 505-10.PubMedGoogle Scholar
- Haase A, Frahm J, Hänicke W, Matthaei D: 1 H NMR chemical shift selective (CHESS) imaging. Phys Med Biol. 1985, 30 (4): 341-4. 10.1088/0031-9155/30/4/008.PubMedGoogle Scholar
- Axel L, Dougherty L: MR imaging of motion with spatial modulation of magnetization. Radiology. 1989, 171 (3): 841-5.PubMedGoogle Scholar
- Axel L, Dougherty L: Heart wall motion: improved method of spatial modulation of magnetization for MR imaging. Radiology. 1989, 172 (2): 349-50.PubMedGoogle Scholar
- Grobner T: Gadolinium–a specific trigger for the development of nephrogenic fibrosing dermopathy and nephrogenic systemic fibrosis?. Nephrol Dial Transplant. 2006, 21 (4): 1104-8.PubMedGoogle Scholar
- Marckmann P, Skov L, Rossen K, Dupont A, Damholt MB, Heaf JG, Thomsen HS: Nephrogenic systemic fibrosis: suspected causative role of gadodiamide used for contrast-enhanced magnetic resonance imaging. J Am Soc Nephrol. 2006, 17 (9): 2359-62. 10.1681/ASN.2006060601.PubMedGoogle Scholar
- Kanal E, Barkovich AJ, Bell C, Borgstede JP, Bradley WG, Froelich JW, Gilk T, Gimbel JR, Gosbee J, Kuhni-Kaminski E, Lester JW, Nyenhuis J, Parag Y, Schaefer DJ, Sebek-Scoumis EA, Weinreb J, Zaremba LA, Wilcox P, Lucey L, Sass N: ACR guidance document for safe MR practices: 2007. AJR Am J Roentgenol. 2007, 188 (6): 1447-74. 10.2214/AJR.06.1616.PubMedGoogle Scholar
- Jerosch-herold M, Wilke N, Wang Y, Gong G, Mansoor AM, Huang H, Gurchumelidze S, Stillman AE: Direct comparison of an intravascular and an extracellular contrast agent for quantifcation of myocardial perfusion. Int J Card Imaging. 1999, 15: 453-64. 10.1023/A:1006368619112.PubMedGoogle Scholar
- Greenwood JP, Maredia N, Younger JF, Brown JM, Nixon J, Everett CC, Bijsterveld P, Ridgway JP, Radjenovic A, Dickinson CJ, Ball SG, Plein S: Cardiovascular magnetic resonance and single-photon emission computed tomography for diagnosis of coronary heart disease (CE-MARC): a prospective trial. Lancet. 2012, 379 (9814): 453-60. 10.1016/S0140-6736(11)61335-4.PubMed CentralPubMedGoogle Scholar
- Sourbron SP, Buckley DL: Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability. Phys Med Biol. 2011, 57 (2): R1-R33.PubMedGoogle Scholar
- Lyne JC, Gatehouse PD, Assomull RG, Smith GC, Kellman P, Firmin DN, Pennell DJ: Direct comparison of myocardial perfusion cardiovascular magnetic resonance sequences with parallel acquisition. J Magn Reson Imaging. 2007, 26 (6): 1444-51. 10.1002/jmri.21167.PubMedGoogle Scholar
- Wang Y, Moin K, Akinboboye O, Reichek N: Myocardial first pass perfusion: steady-state free precession versus spoiled gradient echo and segmented echo planar imaging. Magn Reson Med. 2005, 54 (5): 1123-9. 10.1002/mrm.20700.PubMedGoogle Scholar
- Fenchel M, Helber U, Simonetti OP, Stauder NI, Kramer U, Nguyen C-N, Finn JP, Claussen CD, Miller S: Multislice first-pass myocardial perfusion imaging: Comparison of saturation recovery (SR)-TrueFISP-two-dimensional (2D) and SR-TurboFLASH-2D pulse sequences. J Magn Reson Imaging. 2004, 19 (5): 555-63. 10.1002/jmri.20050.PubMedGoogle Scholar
- Bellon EM, Haacke EM, Coleman PE, Sacco DC, Steiger DA, Gangarosa RE: MR artifacts: a review. AJR Am J roentgenol. 1986, 147 (6): 1271-81.PubMedGoogle Scholar
- Morelli J, Runge V, Fei A, Attenberger U, Vu L, Scmeets S, Nitz W, Kirsch J: An Image-based Approach to Understanding the Physics of MR Artifacts. Radiographics. 2011, 31 (6): 849-67.PubMedGoogle Scholar
- Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Sanjiv K, Laskey WK, Pennell DJ, Rumberger JA, Ryan T, Verani MS: Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart: A Statement for Healthcare Professionals From the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation. 2002, 105 (4): 539-42. 10.1161/hc0402.102975.PubMedGoogle Scholar
- Jerosch-Herold M: Quantification of myocardial perfusion by cardiovascular magnetic resonance. J Card Magn Reson. 2010, 12 (1): 57-10.1186/1532-429X-12-57.Google 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 CentralPubMedGoogle Scholar
- Greenwood JP, Maredia N, Radjenovic A, Brown JM, Nixon J, Farrin AJ, Dickinson C, Younger JF, Ridgway JP, Sculpher M, Ball SG, Plein S: Clinical evaluation of magnetic resonance imaging in coronary heart disease: the CE-MARC study. Trials. 2009, 10: 62-10.1186/1745-6215-10-62.PubMed CentralPubMedGoogle Scholar
- Nagel E, Klein C, Paetsch I, Hettwer S, Schnackenburg B, Wegscheider K, Fleck E: Magnetic resonance perfusion measurements for the noninvasive detection of coronary artery disease. Circulation. 2003, 108 (4): 432-7. 10.1161/01.CIR.0000080915.35024.A9.PubMedGoogle Scholar
- Schwitter J, Nanz D, Kneifel S, Bertschinger K, Büchi M, Knüsel PR, Marincek B, Lüscher TF, von Schulthess GK: Assessment of myocardial perfusion in coronary artery disease by magnetic resonance: a comparison with positron emission tomography and coronary angiography. Circulation. 2001, 103 (18): 2230-5. 10.1161/01.CIR.103.18.2230.PubMedGoogle Scholar
- Costa MA, Shoemaker S, Futamatsu H, Klassen C, Anglolillo DJ, Nguyen M, Siuciak A, Gilmore P, Zenni MM, Guzman L, Bass TA, Wilke N: Quantitative magnetic resonance perfusion imaging detects anatomic and physiologic coronary artery disease as measured by coronary angiography and fractional flow reserve. J Am Coll Cardiol. 2007, 50 (6): 514-22. 10.1016/j.jacc.2007.04.053.PubMedGoogle Scholar
- Jerosch-Herold M, Seethamraju RT, Swingen CM, Wilke NM, Stillman AE: Analysis of myocardial perfusion MRI. J Magn Reson Imaging. 2004, 19 (6): 758-70. 10.1002/jmri.20065.PubMedGoogle Scholar
- Utz W, Niendorf T, Wassmuth R, Messroghli D, Dietz R, Schulz-Menger J: Contrast-dose relation in first-pass myocardial MR perfusion imaging. J Magn Reson Imaging. 2007, 25 (6): 1131-5. 10.1002/jmri.20910.PubMedGoogle Scholar
- Larsson HBW, FritzHansen T, Rostrup E, Sondergaard L, Ring P, Henriksen O: Myocardial perfusion modeling using MRI. Magn Reson Med. 1996, 35 (5): 716-26. 10.1002/mrm.1910350513.PubMedGoogle Scholar
- Fritz-Hansen T, Rostrup E, Larsson HB, Søndergaard L, Ring P, Henriksen O: Measurement of the arterial concentration of Gd-DTPA using MRI: a step toward quantitative perfusion imaging. Magn Reson Med. 1996, 36 (2): 225-31. 10.1002/mrm.1910360209.PubMedGoogle Scholar
- Köstler H, Ritter C, Lipp M, Beer M, Hahn D, Sandstede J: Prebolus quantitative MR heart perfusion imaging. Magn Reson Med. 2004, 52 (2): 296-9. 10.1002/mrm.20160.PubMedGoogle Scholar
- Ritter C, Brackertz A, Sandstede J, Beer M, Hahn D, Kostler H: Absolute quantification of myocardial perfusion under adenosine stress. Magn Reson Med. 2006, 56 (4): 844-9. 10.1002/mrm.21020.PubMedGoogle Scholar
- Gatehouse PD, Elkington AG, Ablitt N, Yang G-Z, Pennell DJ, Firmin DN: Accurate assessment of the arterial input function during high-dose myocardial perfusion cardiovascular magnetic resonance. J Magn Reson Imaging. 2004, 20 (1): 39-45. 10.1002/jmri.20054.PubMedGoogle Scholar
- Arai AE: Magnetic resonance first-pass myocardial perfusion imaging. Topics Magn Reson Imaging. 2000, 11 (6): 383-98. 10.1097/00002142-200012000-00007.Google Scholar
- Schreiber WG, Schmitt M, Kalden P, Mohrs OK, Kreitner K-F, Thelen M: Dynamic contrast-enhanced myocardial perfusion imaging using saturation-prepared TrueFISP. J Magn Reson Imaging. 2002, 16 (6): 641-52. 10.1002/jmri.10209.PubMedGoogle Scholar
- Elkington AG, Gatehouse PD, Cannell TM, Moon JC, Prasad SK, Firmin DN, Pennell DJ: Comparison of hybrid echo-planar imaging and FLASH myocardial perfusion cardiovascular MR imaging. Radiology. 2005, 235 (1): 237-43. 10.1148/radiol.2351040360.PubMedGoogle 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.PubMedGoogle Scholar
- Kim RJ, Fieno DS, Parrish TB, Harris K, Chen E, Simonetti O, Bundy J, Finn JP, Klocke FJ, Judd RM: Relationship of MRI Delayed Enhancement to Irreversible Injury, Infarct Age, and Contractile Function. Circulation. 1999, 100 (1992): 2002-Google Scholar
- Choi KM, Kim RJ, Gubernikoff G, Vargas JD, Parker M, Judd RM: Transmural Extent of Acute Myocardial Infarction Predicts Long-Term Improvement in Contractile Function. Circulation. 2001, 104 (10): 1101-7. 10.1161/hc3501.096798.PubMedGoogle Scholar
- Kim R, Edwin W, Allen R, Enn_ling C, Parker M, Simonetti O, Klocke F, Bonow R, Judd R: The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med. 2000, 343 (20): 1445-53. 10.1056/NEJM200011163432003.PubMedGoogle Scholar
- Mahrholdt H, Wagner A, Judd RM, Sechtem U, Kim RJ: Delayed enhancement cardiovascular magnetic resonance assessment of non-ischaemic cardiomyopathies. Eur Heart J. 2005, 26 (15): 1461-74. 10.1093/eurheartj/ehi258.PubMedGoogle Scholar
- Kim HW, Farzaneh-Far A, Kim RJ: Cardiovascular magnetic resonance in patients with myocardial infarction. J Am Col Card. 2009, 55 (1): 1-16. 10.1016/j.jacc.2009.06.059.Google Scholar
- Kim R, Wu E, Rafael A, Chen EL, Parker MA, Simonetti O, Klocke FJ, Bonow RO, Judd RM: The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med. 2000, 343 (20): 1445-53. 10.1056/NEJM200011163432003.PubMedGoogle Scholar
- Kloner RA, Ganote CE, Jennings RB: The “ No-Reflow ” Phenomenon after Temporary Coronary Occlusion in the Dog. J Clin Invest. 1974, 54: 1496-508. 10.1172/JCI107898.PubMed CentralPubMedGoogle Scholar
- Klein C, Schmal TR, Nekolla SG, Schnackenburg B, Fleck E, Nagel E: Mechanism of late gadolinium enhancement in patients with acute myocardial infarction. J Card Magn Reson. 2007, 9 (4): 653-8. 10.1080/10976640601105614.Google Scholar
- Kim RJ, Chen EL, Lima JA, Judd RM: Myocardial Gd-DTPA kinetics determine MRI contrast enhancement and reflect the extent and severity of myocardial injury after acute reperfused infarction. Circulation. 1996, 94 (12): 3318-26. 10.1161/01.CIR.94.12.3318.PubMedGoogle Scholar
- Mather AN, Lockie T, Nagel E, Marber M, Perera D, Redwood S, Radjenovic A, Saha A, Greenwood JP, Plein S: Appearance of microvascular obstruction on high resolution first-pass perfusion, early and late gadolinium enhancement CMR in patients with acute myocardial infarction. J Card Magn Reson. 2009, 11: 33-10.1186/1532-429X-11-33.Google Scholar
- Look DC: Time Saving in Measurement of NMR and EPR Relaxation Times. Rev Sci Instrum. 1970, 41 (2): 250-10.1063/1.1684482.Google Scholar
- Kellman P, Arai AE, Mcveigh ER, Aletras AH: Phase-Sensitive Inversion Phase-Sensitive Inversion Recovery for Detecting Myocardial Infarction Using Gadolinium-Delayed Hyperenhancement. Magn Reson Med. 2002, 383: 372-83.Google Scholar
- Dewey M, Laule M, Taupitz M, Kaufels N: Myocardial Viability: Assessment with Three-dimensional MR Imaging in Pigs and Patients. Radiology. 2006, 239 (3): 703-9. 10.1148/radiol.2393050586.PubMedGoogle Scholar
- Foo TKF, Stanley DW, Castillo E, Rochitte CE, Wang Y, Bluemke DA, Wu KC: Myocardial Viability: Breath-hold 3D MR Imaging of Delayed Hyperenhancement in Time. Radiology. 2004, 230: 845-51. 10.1148/radiol.2303021411.PubMedGoogle Scholar
- Saranathan M, Rochitte CE, Foo TKF: Fast, three-dimensional free-breathing MR imaging of myocardial infarction: a feasibility study. Magn Reson Med. 2004, 51 (5): 1055-60. 10.1002/mrm.20061.PubMedGoogle Scholar
- Nguyen TD, Spincemaille P, Weinsaft JW, Ho BY, Cham MD, Prince MR, Wang Y: A fast navigator-gated 3D sequence for delayed enhancement MRI of the myocardium: comparison with breathhold 2D imaging. J Magn Reson Imaging. 2008, 27 (4): 802-8. 10.1002/jmri.21296.PubMedGoogle Scholar
- Kellman P, Chung Y-C, Simonetti OP, McVeigh ER, Arai AE: Multi-contrast delayed enhancement provides improved contrast between myocardial infarction and blood pool. J Magn Reson Imaging. 2005, 22 (5): 605-13. 10.1002/jmri.20426.PubMed CentralPubMedGoogle Scholar
- Foo TKF, Wolff SD, Gupta SN, Kraitchman DL: Enhanced viability imaging: improved contrast in myocardial delayed enhancement using dual inversion time subtraction. Magn Reson Med. 2005, 53 (6): 1484-9. 10.1002/mrm.20515.PubMedGoogle Scholar
- Prince MR, Yucel EK, Kaufman JA, Harrison DC, Geller SC: Dynamic gadolinium-enhanced three-dimensional abdominal MR arteriography. J Magn Reson Imaging. 1993, 3 (6): 877-81. 10.1002/jmri.1880030614.PubMedGoogle Scholar
- Sivananthan UM, Ridgway JP, Bann K, Verma SP, Cullingworth J, Ward J, Rees MR: Fast magnetic resonance angiography using turbo-FLASH sequences in advanced aortoiliac disease. Br J Radiol. 1993, 66 (792): 1103-10. 10.1259/0007-1285-66-792-1103.PubMedGoogle Scholar
- Davis CP, Hany TF, Wildermuth S, Schmidt M, Debatin JF: Postprocesing techniques for gadolinium enhanced three-dimensional MR angiography. RadioGraphics. 1997, 17: 1061-77.PubMedGoogle Scholar
- Prince M: Gadolinium enhanced MR aortography. Radiology. 1994, 191: 155-64.PubMedGoogle Scholar
- Shetty AN, Bis KG, Vrachliotis TG, Kirsch M, Shirkhoda A, Ellwood R: Contrast-Enhanced 3D MRA With Centric Ordering in k Space: A Preliminary Clinical Experience in Imaging the Abdominal Aorta and Renal and Peripheral Arterial Vasculature. J Magn Reson Imaging. 1998, 8: 603-15. 10.1002/jmri.1880080314.PubMedGoogle Scholar
- Wilman AH, Riederer SJ: Performance of an elliptical centric view order for signal enhancement and motion artifact suppression in breath-hold three-dimensional gradient echo imaging. Magn Reson Med. 1997, 38 (5): 793-802. 10.1002/mrm.1910380516.PubMedGoogle Scholar
- Earls JP, Rofsky NM, DeCorato DR, Krinsky GA, Weinreb JC: Hepatic arterial-phase dynamic gadolinium-enhanced MR imaging: optimization with a test examination and a power injector. Radiology. 1997, 202 (1): 268-73.PubMedGoogle Scholar
- Riederer SJ, Tasciyan T, Farzaneh F, Lee JN, Wright RC, Herfkens RJ: MR fluoroscopy: technical feasibility. Magn Reson Med. 1988, 8 (1): 1-15. 10.1002/mrm.1910080102.PubMedGoogle Scholar
- Wilman AH, Riederer SJ, King BF, Debbins JP, Rossman PJ, Ehman RL: Fluoroscopically triggered contrast-enhanced three-dimensional MR angiography with elliptical centric view order: application to the renal arteries. Radiology. 1997, 205 (1): 137-46.PubMedGoogle Scholar
- Foo TK, Saranathan M, Prince MR, Chenevert TL: Automated detection of bolus arrival and initiation of data acquisition in fast, three-dimensional, gadolinium-enhanced MR angiography. Radiology. 1997, 203 (1): 275-80.PubMedGoogle Scholar
- Korosec FR, Frayne R, Grist TM, Mistretta CA: Time-resolved contrast-enhanced 3D MR angiography. Magn Reson Med. 1996, 36 (3): 345-51. 10.1002/mrm.1910360304.PubMedGoogle Scholar
- Laub GA: Time-of-flight method of MR angiography. Magn Reson Imaging Clin N Am. 1995, 3 (3): 391-8.PubMedGoogle Scholar
- Miyazaki M, Akahane M: Non-contrast enhanced MR angiography: Established techniques. J Magn Reson Imaging. 2012, 35 (1): 1-19. 10.1002/jmri.22789.PubMedGoogle Scholar
- Miyazaki M, Lee VS: Nonenhanced MR angiography. Radiology. 2008, 248 (1): 20-43. 10.1148/radiol.2481071497.PubMedGoogle Scholar
- Dumoulin CL: Phase contrast MR angiography techniques. Magn Reson Imaging Clin N Am. 1995, 3 (3): 399-411.PubMedGoogle Scholar
- Miyazaki M, Takai H, Sugiura S, Wada H, Kuwahara R, Urata J: Peripheral MR angiography: separation of arteries from veins with flow-spoiled gradient pulses in electrocardiography-triggered three-dimensional half-Fourier fast spin-echo imaging. Radiology. 2003, 227 (3): 890-6. 10.1148/radiol.2273020227.PubMedGoogle Scholar
- Botnar RM, Stuber M, Danias PGP, Kissinger KV, Manning WJ: Improved coronary artery definition with T2-weighted, free-breathing, three-dimensional coronary MRA. Circulation. 1999, 99 (24): 3139-48. 10.1161/01.CIR.99.24.3139.PubMedGoogle Scholar
- Sakuma H, Ichikawa Y, Suzawa N, Hirano T, Makino K, Koyama N, Van Cauteren M, Takeda K: Assessment of coronary arteries with total study time of less than 30 minutes by using whole-heart coronary MR angiography. Radiology. 2005, 237 (1): 316-21. 10.1148/radiol.2371040830.PubMedGoogle Scholar
- Evans AJ, Blinder RA, Herfkens RJ, Spritzer CE, Kuethte DO, Fram EK, Hedlund LW, Kuethe DO: Effects of turbulence on signal intensity in gradient echo images. Invest Radiol. 1988, 23 (7): 512-8. 10.1097/00004424-198807000-00006.PubMedGoogle Scholar
- Kilner P, Mohiaddin R: Valvular heart disease. Cardiovascular Magnetic Resonance. Edited by: Manning WJ, Pennell DJ. 2010, Philadelphia: Saunders, 510-4.Google Scholar
- Firmin D: Blood flow velocity assessment. Cardiovascular Magnetic Resonance. Edited by: Manning WJ, Pennell D. 2010, Philadelphia: Saunders, 91-9.Google Scholar
- Wagner S, Auffermann W, Buser P, Lim T, Kircher B, Plugfelder P, Higgins C: Diagnostic accuracy and estimation of the severity of valvular regurgitation from the signal void on cine magnetic resonance images. Am Heart J. 1989, 118: 760-7. 10.1016/0002-8703(89)90590-5.PubMedGoogle Scholar
- Suzuki J, Caputo GR, Kondo C, Higgins CB: Cine MR imaging of valvular heart disease: display and imaging parameters affect the size of the signal void caused by valvular regurgitation. AJR Am J Roentgenol. 1990, 155 (4): 723-7.PubMedGoogle Scholar
- Kilner PJ, Firmin DN, Rees RS, Martinez J, Pennell DJ, Mohiaddin RH, Underwood SR, Longmore DB: Valve and great vessel stenosis: assessment with MR jet velocity mapping. Radiology. 1991, 178 (1): 229-35.PubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.