Pitfalls in Diagnostic Radiology || Magnetic Resonance Imaging

39W.C.G. Peh (ed.), Pitfalls in Diagnostic Radiology,DOI 10.1007/978-3-662-44169-5_3, © Springer-Verlag Berlin Heidelberg 2015

Abbreviations

2D Two-dimensional3D Three-dimensionalBLADE Proprietary name for periodically

rotated overlapping parallel lines with enhanced reconstruction or PROPELLER

CNR Contrast-to-noise ratioEPI Echo-planar imagingFLASH Fast low-angle shotFOV Field of viewGRAPPA Generalized autocalibrating par-

tially parallel acquisitionHASTE Half-Fourier acquisition single-shot

turbo spin echoMP-RAGE Magnetization-prepared rapid gra-

dient echoMRI Magnetic resonance imagingPACE Prospective acquisition correctionPD Proton densityRMC Retrospective motion correctionSE Spin echoSENSE Sensitivity encodingSNR Signal-to-noise ratioSSFP Steady-state free precessionTE Echo timeTR Repetition timeTrue FISP True fast imaging with steady-state

precessionTSE Turbo spin echoTWIST Time-resolved angiography with

stochastic trajectories

H. Rumpel, PhD (*) • L.L. Chan, MBBS, FRCRDepartment of Diagnostic Radiology, Singapore General Hospital, Outram Road, Singapore 169608, Republic of Singaporee-mail: [email protected]; [email protected]

3Magnetic Resonance Imaging

Helmut Rumpel and Ling Ling Chan

Contents

3.1 Introduction ................................................ 40

3.2 Pitfalls Inherent in Magnetic Resonance Imaging .................................... 41

3.2.1 Signal-to-Noise as a Source of Pitfalls ........ 413.2.2 Scan Time as a Source of Pitfalls ................ 41

3.3 Fast Imaging to Reduce Motion Artifacts ......................................... 42

3.3.1 Fast Imaging Using Different k-Space Trajectory Strategies ...................... 43

3.3.2 Fast Imaging Using TR Shortening ............. 523.3.3 View Sharing................................................ 543.3.4 Combining Fast Imaging with

Gating or Motion Correction ....................... 56

3.4 MRI at 3T .................................................... 573.4.1 High-Contrast Reading at 1.5T

Versus High-Resolution Reading at 3T ....... 573.4.2 Susceptibility Effects at 3T .......................... 593.4.3 Other Challenges at 3T ................................ 59

Conclusion .............................................................. 61

References ............................................................... 62

mailto:[email protected]

mailto:[email protected]

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3.1 Introduction

The Encyclopaedia Britannica gives one defi-nition of pitfall as “a pit flimsily covered or camouflaged and used to capture and hold ani-mals or men.” Does the magnetic resonance imaging (MRI) terrain lend itself to pitfalls? The answer is yes and no. With technological advancements in MRI, some pitfalls have become extinct, while others have emerged. As one browses through the literature, for exam-ple, the journal RadioGraphics between the year 1985 and the present (Pusey et al. 1986; Morelli et al. 2011), there is a noticeable change in the pattern of pitfalls.

A plethora of review articles on this subject can be found, and tutorials are offered in MRI conferences for the continuous training of radi-ologists and radiologic technicians to raise awareness about pitfalls and artifacts that can affect the diagnostic quality of images. The teaching points are that several thresholds in MRI must be met to reach a continuous state-of-the-art quality in the routine clinical setting. Notably, MRI sensitivity and vulnerability to motion- related image degradation are addressed. From the very beginning of MRI, all technical strate-gies have focused on getting the most signal and the least noise that cohere with the following two views: imaging of noisy structures and imaging of structured noise.

Before delving into pitfalls in MRI, it may be pertinent to remind ourselves of the funda-mental limitation of MRI which is the inherently low signal-to-noise ratio (SNR). This is because, unlike computed tomography or positron emis-sion tomography where every photon counts, only a small fraction of the entire spin population contributes to the signal intensity of MR images; the rest constitutes noise. Hence, MRI is best described as imaging of noisy structures (Fig. 3.1). Physiological motion is known to produce artifacts in MR imaging. An example would be periodic movements from blood vessel pulsation. In such situations, ghost images appear over the entire field of view (FOV), on top of the noise in the MR image. Therefore, MRI can also be described as imaging of structured noise (Fig. 3.2).

Pitfalls can be simply classified into those “within the operator’s control” and those “beyond the operator’s control.” On one hand, the inherent limitations in MRI with regard to SNR, contrast-to- noise ratio (CNR), imaging time, and their interdependencies create a vicious circle, which

Fig. 3.1 Imaging of noisy structures. High-resolution (in-plane, 0.25 mm; slice thickness, 0.5 mm) CISS MR image of the eighth nerve, afforded by the stark contrast between cerebrospinal fluid and non-fluid structures despite the low SNR

Fig. 3.2 MRI of structured noise. Physiological noise caused by vascular pulsation from the sigmoid sinus

H. Rumpel and L.L. Chan

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is the cause of numerous pitfalls. We often lead ourselves into these pitfalls by breaking through inherent limitations based on our wish-for-more. On the other hand, not all artifacts are within con-trol or even conspicuous and can even be mis-taken for underlying pathology, thereby raising the question: Is it an MRI pitfall or is it real? Another source of pitfalls is a result of the snow-balling advancements in MRI technology. For example, high-field MRI scanners combined with high-density array coils show more details – but many artifacts can also be exacerbated.

This chapter contains three sections. The first section aims to provide a concise overview of the basis of pitfalls inherent in MRI, namely, SNR, physiological motion, and their relationship. The second section focuses on fast imaging tech-niques that have been used to mitigate motion artifacts. The creation of “new artifacts” owing to the use of these techniques will be illustrated, along with suggestions to avoid pitfalls and resolve artifacts. Lastly, various challenges met in 3T MRI will be addressed.

3.2 Pitfalls Inherent in Magnetic Resonance Imaging

We summarize the inherent pitfalls in MRI, viz., SNR and motion, and how they are related to each other.

3.2.1 Signal-to-Noise as a Source of Pitfalls

We consider as a starting point the SNR from a particular voxel of the resulting image. In gen-eral, for a three-dimensional (3D) Fourier- imaging sequence, the voxel SNR can be expressed as the following proportionality (Callaghan and Eccles 1987; Macovski 1996):

SNR

BWacq∝

d d dx y z x y zN N N N

(3.1)

in which δx, δy and δz are the voxel dimensions, Nacq is the number of averages, Nx is the number

of times the signal is sampled in the frequency domain, Ny is the number of steps of the first phase-encoding gradient, Nz is the number of steps of the second phase-encoding gradient (in case of a two-dimensional [2D] Fourier-imaging sequence, Nz is 1), and BW is the receiver band-width, which defines the range of frequencies to be sampled. The constant of proportionality in this expression involves factors such as the spin density. The noise has its source from the patient’s body and the electronics and is referred to as Johnson-Nyquist noise (Redpath 1998). The SNR in (3.1) is the baseline value before it under-goes further manipulation, not only for T1/T2 weighting but for every other MR contrast. It serves as a guide to avoiding SNR pitfalls prior to modification of MR parameters.

3.2.2 Scan Time as a Source of Pitfalls

Data is sampled in MRI in a data matrix or k-space (Twieg 1983; Mezrich 1995). Every point therein contains part of the information for the complete image upon inverse Fourier trans-formation. Those in its center determine SNR and CNR, whereas data in the periphery sharpen the image. In a basic analogy, filling of k-space resembles how a rectangular function can be con-structed with a suitable set of waveforms with symmetrical harmonic components, namely, odd-integer harmonic frequencies. For illustra-tion, Fig. 3.3a shows a one-dimensional (1D) example of the contour of a rectangular function constructed with a set of low frequencies. By adding higher frequencies of odd harmonic wave-forms together, the shape becomes sharper (Fig. 3.3b). Translated into the concepts of MRI, the image becomes sharper as the number of phase-encoding steps Ny increases (Fig. 3.3c, d). Conventional imaging techniques take several minutes to produce images of sufficient resolu-tion and sharpness according to Eq. 3.2:

Acquisition time TRacq= × ×N Ny

(3.2)

in which TR is repetition time. By increasing Ny from 32 to 512, for example, it can be seen that

3 Magnetic Resonance Imaging

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>90 % of the acquisition time is expended just to get a sharper image. This is the reason why MRI is inherently time-consuming and only a small fraction of the k-space contributes to the signal of the image. These properties will become useful later on.

3.3 Fast Imaging to Reduce Motion Artifacts

The lengthy acquisition time of an MRI sequence causes its vulnerability to physiological motion, such as bulk movements, vascular and cerebro-spinal fluid pulsation, respiratory excursion, car-diac pulsation, and gastrointestinal peristalsis. Artifacts due to motion usually arise from long time segments within a pulse sequence, which are either in the form of tissue displacement dur-ing the TR or phase shifts during periods when

gradients are applied within the echo time (TE) (Pipe 1999). Signal averaging has been estab-lished as a technique not only for reducing noise but motion artifacts as well. However, we see from Eq. 3.2 that the use of this approach is unre-alistic for clinical practice as the acquisition time will be prolonged by a multiple. Furthermore, long scan times may result in patient discomfort. A better alternative will be to freeze the motion by using ultrafast imaging – in an idealistic nota-tion. In practice, an effective compromise between fast-imaging techniques and motion artifact reduction is required.

Chart 3.1 pulls together cornerstones of fast- imaging strategies in achieving time-efficient acquisitions, each with its associated pitfall, so as to overcome the supreme pitfall, i.e., physiologi-cal motion. Although there is no general solution to this, fast imaging can be achieved through various approaches, each well reputed in its own

a b

c d

Fig. 3.3 Concept of image sharpening: an analogy was made between the Fourier method of composing a peri-odic rectangular function in terms of a combination of trigonometric functions and MR images of four tubes. (a) Composition of the first three odd-integer harmonics sin(ωt) + 1/3 sin(3ωt) + 1/5 sin(5ωt) shows blurred edges. (b)

Composition of the first 49 odd-integer harmonics (sin(ωt) + 1/3 sin(3ωt) + 1/5 sin(5ωt) … + 1/47 sin(47ωt) + 1/49 sin(49ωt)) shows sharp edges. (c) Low-resolution MR image of 32 phase-encoding steps. (d) High-resolution MR image of 512 phase-encoding steps


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niche. We will illustrate in the text that follows (Sect. 3.3.1) on how these approaches relate to different k-space trajectories when zoning into central regions for encoding contrast information and peripheral regions for spatial resolution (Hennig 1999). From Eq. 3.2, it is also apparent that the image acquisition time can be shortened by reducing TR (Sect. 3.3.2).

3.3.1 Fast Imaging Using Different k-Space Trajectory Strategies

3.3.1.1 Parallel ImagingBefore embarking upon the different methods of “making MRI faster,” we need to understand the impact of parallel imaging (Pruessmann et al.

2001) and its relation to pitfalls. Parallel imaging became a standard in recent years, made possible by multiple receiver coils and image reconstruc-tion technology (Ohlinger and Sodickson 2006). It utilizes information from each element of a phased-array coil, which samples data in parallel, hence reducing acquisition time while maintain-ing spatial resolution. Parallel imaging can be readily combined with various fast-imaging methods and thus is ranked first in Chart 3.1.

The basic idea of parallel imaging is to use a FOV that is much smaller than the size of the object, so that a correspondingly smaller number of phase-encoding steps Ny is required to keep the image resolution constant, since

Resolution FOV= / Ny

(3.3)

T1/T2 weighted imaging

Long acquisition timeMotion artifacts

reduced SNR

T2 blurring ‘Poor’ contrast Complex contrast

Severe motionartefacts

Sub-optimal tissuedifferentiation

Misregistration

Breath hold Breath holdor

orFree breathing / PACE

Free breathing / PACE / RMC(in time-resolved scans)

BLADE

Arterial-venousoverlap

DistortionsMotion artifactsdue to temporalsharing of data

Pitfall:

Pitfall:

Various trajectories for sampling k-space

Sequence related pitfalls

Specific pitfalls

Approximate image acquisition time

Applications with gating or motion correction

TSE FLASH

Parallel imaging

SSFP

Structural MRI Cardiac MRIAbdomen MRI

Cardiac MRIAbdomen MRI

Functional MRIAbdomen MRI

Angiography

200 ms3 min 150 ms 100 ms NA

EPI View sharing

Chart 3.1 T1/T2 weighted imaging strategies in reducing motion artefacts


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This results in wraparound effects or aliasing artifacts, which then need to be eliminated by GRAPPA/SENSE reconstruction (Hoge and Brooks 2006). The price for faster imaging is lower SNR, as a consequence of reduced number of data samples Ny and the g-factor or noise amplification term (Larkman 2007) as shown in the following equation:

SNRSNR

parallell imaging = full k-space

g Ny

(3.4)

Is it possible to decrease the examination time without sacrificing the diagnostic accuracy? Figure 3.4 illustrates how the SNR decreases with higher parallel imaging factors according to (3.4). In practice, the cutoff value is usually at a parallel imaging factor of 2 or 3, but this decision is two-sided. The balance between distortions and SNR needs to be carefully weighed, and a different parallel imaging factor might be more suitable for a particular area of interest (Glockner et al. 2005). This is demonstrated for the brain

Fig. 3.4 Series of TSE MR images (TR/TE 4,000/94, FOV 256, matrix 384) with increasing parallel imaging factor. Limitations of parallel imaging include reduced SNR and reconstruction artifacts with higher parallel

imaging factors, albeit decreased geometric distortions. An artifact often associated with parallel imaging is caused by inaccurate coil sensitivity maps and produces a band of noise through the center of the image (arrow)


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stem using echo-planar imaging, which has been distorted by different magnetic susceptibilities from nearby tissue-air and tissue-bone interfaces as shown in Fig. 3.5 (refer to Sect. 3.3.1.4 for explanation). On the other hand, reconstruction artifacts also occur if SNR is below a threshold (Fig. 3.4) (Larkman 2007).

3.3.1.2 Multiple-Echo SequencesThe different k-space trajectories range from one echo per TR to multiple echoes per TR to an entire set of echoes per TR (Patel et al. 1997). The representative sequences are spin echo (SE), TSE, and HASTE.

One Echo per TR: The spin-echo sequence is the gold standard technique for T1 and T2 weighting:

SSE = ⋅[ ]⋅[ ]

r

r

T1weighting factor

T2 weighting factor

where is the pproton density

(3.5)

Here, the tissue has good contrast in a predictable manner. It exists as a general guide to how the tissue will appear on T1- or T2-weighted images (McRobbie et al. 2007). Clinical protocols may still vary within a certain range of TE or TR to allow the technologist to adjust the scan parameters according to the patient’s

Fig. 3.4 (continued)


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Fig. 3.5 Reduced distortion with higher parallel imaging factors. The geometric distortion significantly reduces with a higher parallel imaging factor. However, the balance between distortions and SNR needs to be carefully weighed


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needs while maintaining the contrast definition that the radiologist is comfortable with (Fig. 3.6).

Multiple Echoes per TR: The concept of turbo spin echo (TSE) was first described by Hennig et al. (1986). It uses echo trains in which each echo corresponds to a different phase-encoding view. The length of the echo train is equal to the lines in k-space sampled per excitation. Therefore, the acquisition time in (3.2) is shortened by the factor that is equal to the number of echoes in such an echo train or the TSE factor:

TSEacquisition time=

TR

TSE factoracqN Ny× ×

(3.6)

T2 weighting in TSE does not closely follow Eq. 3.5 but depends more on the manner of k-space sampling which is depicted in Fig. 3.7a.

As the echoes are received at multiples of the inter-echo time, T2 weighting correlates with the echo number which is allocated at the central part of the k-space. Reordering allocations of multiple echo signals in k-space allows a different effec-tive TE (TEeff) and thus a different T2 weighting. However, reordering strategies need to be fol-

lowed in avoiding ghosting artifacts due to k-space discontinuities (Carmichael et al. 2009). Hence, modifications in contrast must be taken into account in interpreting the images.

Using echo trains, it is also possible to keep the TE almost constant while increasing the TSE factor in a broad range. In both, the shorter and the longer echo train in Fig. 3.7a can be achieved by assigning the same TEeff to the center part of the k-space. Figure 3.7b shows a series of images with an effec-tive TE of 94 ms, while the TSE factor ranges from 12 to 128. Note how the SNR loss is accompanied by a deterioration of CNR and blurring effects. T2 decay during a long echo train can cause the image to appear blurred. Signals at the end of such a train may be low and contaminated by noise. If these low signals belong to data sampled at the periphery of the k-space, they may not contribute efficiently to the sharpness of the image (Larsen et al. 1996). For example, tissue with long T2 such as water is sharp, whereas tissue with short T2 such as bone marrow appears blurred (Fig. 3.8). This example serves the MRI user well to remember that image quality and gain in speed are in opposite directions and underpins the major pitfall in MRI.

TR 400 ms TR 700 ms

Fig. 3.6 Width of TR (400–700 ms) in clinical protocols. Sagittal SE T1-W MR images allow a parameter range of TR values that adheres to the contrast definition


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90 180 180

TE eff Centre of k-space Periphery of k-space

180 180 180 180

90 180 180 180 180 180 180 180 180 180 180 180 180

a

Fig. 3.7 TSE sequence. (a) Oversimplified scheme of two different echo train lengths but with same TEeff. (b) Series of TSE MR images (TR/TE 4,000/94, FOV 210, matrix 384) with an increasing TSE factor. The balance

between acquisition time and SNR (and subsequent loss in gray-white matter differentiation) needs to be carefully weighed

b


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a b

Fig. 3.8 Non fat-suppressed TSE MR image of the knee (TR/TE 3,600/48, FOV 140/140, matrix 314/448). (a) The intra-articular fluid (arrow) and bone marrow appear

sharp when using a turbo factor of 7, while (b) the edema stays sharp, whereas bone marrow and subcutaneous fat become blurred with a turbo factor of 39

bFig. 3.7 (continued)

Entire Echo Set per TR: At the other end of the TSE factor range is the single-shot approach HASTE (Patel et al. 1997). The TSE factor becomes almost Ny/2 in (3.6), which accelerates the image acquisition by the same factor. The course of dete-rioration in image quality in the series of Fig. 3.7b leads to the HASTE image, because the duration of the echo train exceeds the T2 relaxation of most brain tissues. The imaging time then matches that of a normal breath-hold time or shorter, and this

allows it to be used in a wide range of applications, including uncooperative patients, by effectively removing motion artifacts.

3.3.1.3 BLADE: Hybrid of TSE and Radial Acquisition

Radial Imaging: The detected time-domain signals can populate the k-space either in a Cartesian fashion or in a radial (non-Cartesian) fashion. In radial sequences, the k-space is sam-


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pled following radial straight lines, starting or crossing at the origin. Consequently, radial imag-ing is less sensitive to motion as the center of the k-space is oversampled, albeit with concurrent undersampling of the periphery of the k-space leading to streak artifacts (Block et al. 2007). This is demonstrated in Fig. 3.9.

BLADE: BLADE uses a TSE sequence of limited parallel (Cartesian) phase-encoding lines (Tamhane and Arfanakis 2009) (Fig. 3.10). Such rectilinear segments are acquired in a periodically rotating manner similar to radial imaging and has its atten-dant advantages and disadvantages. Since this tech-nique continuously acquires low-resolution images equal to the TSE factor, retrospective motion correc-tion (RMC) can be further applied to reduce in-plane motion artifacts (Fig. 3.11). This motion correction is achieved by iteratively searching for maximum cor-relation between each acquired BLADE. However, severe motion beyond correction thresholds results in rejection of data leading to undersampling and, thus, decreased SNR and streak artifacts (Arfanakis et al. 2005) (Fig. 3.12).

Centre of k-space

Fig. 3.10 Oversimplified BLADE acquisition scheme. The BLADE method is a variant of the radial scanning techniques. The center of k-space is sampled in every rec-tilinear segment

a b

Fig. 3.9 True FISP cardiac MR image with radial acqui-sition within a single breath-hold shows (a) thirty projec-tions with streak artifacts due to undersampling and

(b) improved image quality with 120 projections at the upper tolerance limit of breath-hold for certain patients


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3.3.1.4 Echo-Planar Imaging (EPI)Whenever speed is essential to freeze motion to a large extent, echo-planar imaging (EPI) is always an option (Mansfield 1984). This technique has been lauded as a major breakthrough in medical

diagnostics (press release: The 2003 Nobel Prize in Physiology or Medicine). In essence, the EPI sequence is continuous signal acquisition in the form of a gradient-echo train with several possi-ble trajectories of data sampling. This is where its unique speed is derived, since data is collected within a single T2* decay. The main limitation of EPI is the relatively low image resolution of matrices not exceeding 192 × 192. Nevertheless, this resolution is sufficient for physiological imaging such as in diffusion-weighted and diffusion- tensor imaging, perfusion imaging (arterial spin labeling and dynamic susceptibility contrast methods), and brain mapping (using blood oxygenation level dependent – BOLD – or other vascular-related techniques).

In addition, EPI is subjected to severe suscepti-bility artifacts. Any difference in susceptibility, as from tissue to bone, can lead to a local magnetic field gradient and a consequent shift of Larmor fre-quencies and will result in substantial image dis-tortions (Fig. 3.13). Inherent to the EPI acquisition scheme is an extremely low pixel bandwidth along the phase-encoding direction which is inversely related to the inter-echo time (about a millisecond

a b

Fig. 3.11 TSE T2-W MR image with BLADE acquisi-tion scheme of a restless patient; (a) without additional retrospective motion correction and (b) with additional retrospective motion correction. Note the improvement in

detail and contrast resolution between the gray and white matter margins due to sharpening of the gray-white inter-face following application of retrospective motion correction

Fig. 3.12 Knee image: fat-suppressed TSE (TR/TE 3,900/64) MR image with BLADE acquisition scheme. Note the streak artifact at the popliteal artery. Vascular pulsation caused severe local motion that was beyond the motion correction thresholds, leading to undersampling and local radial streaking


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or less) of the gradient-echo train. This is due to the fact that a decrease in the pixel bandwidth will result in greater image distortions. Tsao (2010) provides a complete description of EPI. Therefore, it is logical that increasing the pixel bandwidth (in the phase direction) will reduce these unwanted distortions in EPI. This can be achieved either by shortening the gradient-echo train length, using an higher parallel imaging factor, or shortening the inter-echo time with readout segmentation (Porter and Heidemann 2009) (Fig. 3.14), or a combina-tion of both. Figures 3.5 and 3.15 illustrate repre-sentative cases.

3.3.2 Fast Imaging Using TR Shortening

Representative sequence families of this cat-egory include spoiled gradient-echo sequences (FLASH) (Haase et al. 1986) and rewound gradient- echo sequences (steady-state sequences) (Chavhan et al. 2008). What they have in common

is an inter-echo time of the same order of magni-tude as the TR. Otherwise, they are based on dif-ferent MRI principles, namely, using longitudinal versus transverse magnetization (Fig. 3.16). By shortening TE and TR periods to a minimum, phase shifts during periods within TE and/or tis-sue displacement during TR are scaled down to an insignificant level, allowing these sequences to be used for breath-hold scans and dynamic contrast examinations. The drawback is that the image contrast reveals a more complicated weighting, and thus leading to pitfalls.

The FLASH sequence can produce PD-/T1-/T2*-weighted tissue contrast, depending on the acquisition parameters. However, it is notewor-thy to mention the difficulty in achieving good T2* contrast. Under the specific condition of TR being less than T2*, a remnant of transverse mag-netization will remain as the sequence is repeated for the next phase-encoding step. This transverse magnetization is eliminated in routine protocols either by radio-frequency (RF) spoiling or gradient spoiling or by both. As such, this tech-nique lends itself to reduced T2* weighting. Furthermore, since a long TE aggravates motion artifacts, it is tacitly kept as short as possible. The signal intensity in FLASH is far more complex than for SE. It is beyond the scope of this chapter to state explicably the solution to the FLASH sig-nal (McRobbie et al. 2007), but the chief arbitrator lies in the Ernst angle (which is determined by the repetition time and the T1 of the tissue in question) for FLASH. The choice of flip angle is important for achieving T1 weighting, and thus an inappropriate angle may conceal the true or optimal tissue differentiation.

In SSFP sequences, the reverse is performed with regard to transverse magnetization. Balanced gradients maintain the transverse magnetization so that both T1 and T2 contrasts are represented in the image (Chavhan et al. 2008). True FISP requires a high performance in field homogeneity. If this is not achieved, the images become degraded by banding artifacts which have spacing inversely proportional to off-center frequencies due to field inhomogeneities (Li et al. 2004) (Fig. 3.17).

Fig. 3.13 Spatial distortion in dynamic perfusion map based on EPI. The distortion and posterolateral displace-ment of a high CBV area (white arrow), is clearly visible at tissue-bone interfaces related to a focal-enhancing lesion medial to left optic canal (yellow arrow) when over-laid on MP-RAGE or contrast-enhanced T1-W images


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Pha

se

Read - out

a b c

Fig. 3.14 Oversimplified k-space schemes for EPI (Tsao 2010). (a) Fully encoded sampling scheme, (b) undersam-pled by a factor of 2, resulting in a shorter echo-train length,

and (c) readout segmentation by a factor of 4, giving rise to a higher switching frequency for the oscillating readout gradient waveform, resulting in a shorter echo spacing

a b

Fig. 3.15 Diffusion-weighted EPI of the cervical spinal cord. (a) Single-shot EPI with echo spacing of 0.94 ms and (b) readout segmented EPI with echo spacing of 0.38 ms. Note the improvement in distortion at the vertebral- CSF interface following readout segmentation


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3.3.3 View Sharing

The purpose of “view sharing” is for the use of time-resolved acquisitions in contrast-enhanced MR angiography or in dynamic contrast- enhanced

MRI (Song et al. 2009; Tsao and Kozerke 2012). As implied by the subtitle, the design of this k-space trajectory reduces the amount of acquired data based on the fact that much of the MRI data is redundant. In this setting, only the centrally located region of k-space which provides infor-mation regarding image contrast is sampled dynamically during the passage of the contrast agent bolus through the covered 3D volume. Contrariwise, the periphery of k-space is heavily undersampled to achieve imaging in the shortest possible intervals. If the pure keyhole method is used, the full k-space is acquired once at the beginning of a specific case, whereas other spa-tiotemporal techniques such as TWIST also sam-ple higher spatial frequencies during the dynamic part of the scan. For the latter, the periphery k-space is reconstructed from the undersampled subsets after the dynamic scan.

Which artifacts are inherent in this concept? First of all, keyhole imaging is particularly sensi-tive to motion, since data acquired at different time points during the dynamic scan are com-bined in k-space. Moreover, artifacts can arise from poor temporal resolution, such as arteriove-nous overlap (Fig. 3.18). The larger the number

Fig. 3.17 True FISP cardiac cine MR image extracted from a time series. Banding artifacts or moiré patterns are apparent, caused by field heterogeneity (arrows)

a b

Fig. 3.16 Comparison of image contrast in (a) spoiled gradient-echo FLASH and (b) rewound gradient-echo true FISP MR images, using the same TR/TE 8.0/3.2. Note the stark difference in tissue contrast despite using

identical TR/TE parameters. There is heavier T1 weight-ing in FLASH from elimination of the transverse magne-tization versus heavier T2 weighting in FISP from preservation of the transverse magnetization


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a

c

b

Fig. 3.18 Dynamic gradient-echo acquisition based on k-space sharing (TWIST). The ratio of central k-space to outer k-space sampling determines the temporal resolu-tion, which is 2.7 s compared to 7.5 s for sampling the

whole matrix. Series of contrast-enhanced MR angiogra-phy images of the carotids from (a) the arterial phase to (b) the arteriovenous overlap and to (c) the venous phase within one breath-hold


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of sampling points in the central region of k-space, the better the contrast image, albeit at the cost of reduced temporal resolution. On top of that, artifacts may also occur, depending on the various ways to realize k-space sampling as dis-cussed above, such as T2 blurring and ghosting for TSE and streak artifact for radial acquisition.

3.3.4 Combining Fast Imaging with Gating or Motion Correction

Physiological motion such as respiratory motion, cardiovascular pulsation, bowel movement, and physical movement of subjects may be rhythmic or random and even vary from patient to patient or within the same patient. As a rule of thumb, the respiratory time scale is in seconds, whereas the movement of the myocardium is in tens of milli-seconds. Arteries and cerebrospinal fluid pulse with the same beat of the heart, while bowel and physical movements are random, and especially so in the ill and restless patient for the latter. Fast imaging can be combined with various methods to correct physiological motion.

Nevertheless, fast imaging has its shortcom-ings – rather than pitfalls – as these techniques are not fast enough to freeze motion and hence unable to completely eliminate motion arti-facts. To overcome these problems, fast imag-ing can be combined with methods of motion correction that can be classified into three cat-egories: before (e.g., using prospective acquisi-tion correction, PACE (Thesen et al. 2000)), during (e.g., real- time correction using ECG and respiratory gating), and after recording the data (e.g., using retrospective motion correc-tion, RMC). Methods of the first two categories allow data acquisition only if the patient’s posi-tion falls within an acceptance window, i.e., the operator decides on the range of diaphragm positions or the stage of the cardiac cycle allowed in this window (Fig. 3.19). A small acceptance window will lead to reduced acqui-sition efficiency and prolonged scan time, which predominate in cases of erratic or irregu-lar breathings and arrhythmias. Figure 3.20

shows the deterioration in image quality for a different range of acceptance windows.

RMC methods are known to be effective for correcting inter-scan motion if the movement is within a few degrees of rotation or millimeters in the 2D axial plane, provided that previously acquired images are available. These may be applied to images that originate from either com-plete images of a time-resolved sequence or from sub-images such as a low-resolution image of a single BLADE. For fast imaging of about 30 s or faster, the image acquisition can be performed within a single breath-hold window or in multiple breath-hold windows if patients experience diffi-culties in maintaining even a short breath-hold. Figure 3.21 is a pictorial of four different

a

b

Fig. 3.19 Concept of PACE illustrated on a free- breathing image averaging by a factor of 2 with an inter- scan interim time. Single-shot HASTE can freeze diaphragm motion for liver images. (a) Non-respiratory gating shows superposition of two sharp images with dif-ferent diaphragm positions. (b) PACE navigator detects image at the same diaphragm position


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breath- hold scans each with a specific pitfall as tabulated in Chart 3.1. On the other hand, incom-plete breath-holding leads to a variable degree of image degradation. In this case, the free- breathing acquisitions are considered as the more practical approach. Going into detail for each of these approaches is beyond the scope of this chapter. In making generalizations, they can be freely com-bined with the fast-imaging techniques, as out-lined in Chart 3.1.

3.4 MRI at 3T

3.4.1 High-Contrast Reading at 1.5T Versus High-Resolution Reading at 3T

Rapid molecular tumbling motion is the source of T1 relaxation, which is more effective at 64 MHz (1.5T) than at 128 MHz (3T). As a con-sequence, T1 times of gray and white matter lengthen and converge at higher fields. Lowering the two flip angles of a spin-echo sequence

(Schmitz et al. 2005a, b) mildly improves the gray-white matter contrast, but it remains a pitfall in T1-weighted neuroimaging at 3T (Fig. 3.22). As an alternative, inversion-based sequences are playing a more prominent role in T1-weighted imaging on 3T. This is basically the 3D MP-RAGE sequence, which increases the gray- white matter contrast-to-noise ratios.

When we follow the 1.5T versus 3T literature, a shift from contrast-weighted 2D imaging to iso-tropic 3D high-resolution imaging is noticeable in musculoskeletal imaging. The rationale behind this transition of protocols is twofold, based on SNR and relaxation time considerations. Firstly, T1 is prolonged for cartilage, muscle, synovial fluids, and bone lipids (Gold et al. 2004), although to a lesser extent than brain parenchyma, making 2D MRI too long, if collected in multiple ori-entations with the appropriate TR. A relatively straightforward solution is isotropic 3D imaging which allows for the multiplanar reformatting of the images. Small delicate or oblique structures of the musculoskeletal anatomy are then identified based on high-resolution anatomy rather than on

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Fig. 3.20 Coronary artery imaging. Navigator PACE and ECG gating were used. (a) Rhythmic breathing: data acquisition (black cycles) at the same diaphragm position within the PACE allowance window. (b) Irregular breath-ing (in a different patient): data acquisition at different

diaphragm positions within the PACE allowance window. Blurring artifacts of the coronary artery lumen are noted as the allowed window of chest wall movement was larger than the diameter of the coronary artery


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Fig. 3.21 Breath-hold liver imaging. Comparison of image contrast in (a) FLASH, (b) true FISP, (c) TSE T2 (multiple breath-holds), and (d) inversion-recovery HASTE of a tiny hepatic lesion in segment 7 compatible with a hemangioma (arrow). Note the suboptimal

predominantly T1-W contrast of lesion in FLASH, improved T2-W contrast on true FISP, longest acquisition time for TSE with improvement in lesion conspicuity, and best lesional-liver contrast in HASTE but concomitant T2 blurring overestimating the lesion size

a b

Fig. 3.22 T1-W MR imaging at 3T. (a) Axial SE T1-W MR image (TR/TE 500/8.4, 70 150 pulses). Since T1 times of gray and white matter lengthen and converge at higher fields, gray-white matter differentiation is difficult.

(b) 3D MP-RAGE (TR/TE/TI 1,900/2.5/900) MR image serves as a pictorial alternative with a significantly improved gray-white matter contrast differentiation


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MR contrast (Shapiro et al. 2010). Eliminating partial volume averaging for cartilage and liga-ments is certainly an advantage on 3T.

In terms of SNR and spatial resolution in gen-eral, we see more details on 3T than we could see before (Wong et al. 2009). Is this a potential pit-fall? Accurate image interpretation requires knowledge of specific structures and their diverse anatomic variants. These are challenges, espe-cially for the trainee or junior radiologist. This could be made even more challenging in the sce-nario of switching back and forth between image characteristics of 1.5T versus 3T in institutions running both scanner types in clinical routines. This additional variability might lead to a false interpretation for the untrained eye.

3.4.2 Susceptibility Effects at 3T

Magnetic susceptibility is the ability of a material or tissue to be magnetized when placed in a mag-netic field. It is more prominent at 3T compared to 1.5T. Increased variation in magnetic suscepti-bility at 3T may range from being beneficial to minor adverse effects to causing significant image degradation (Schenck 1996). On a micro-scopic level, susceptibility effects produce signal

losses in gradient-echo images. Deoxyhemoglobin alters the susceptibility of blood in a way that increases the sensitivity of fMRI, whereas hemo-siderin in higher concentrations, e.g., in caverno-mas, may create blooming artifacts (Fig. 3.23). Image degradation due to position errors as a result of higher susceptibility differences at tissue- bone-air interfaces (Fig. 3.13) is distinc-tive when EPI is used at 3T. The high-bandwidth approach helps in reducing susceptibility and chemical shift effects; nevertheless at the expense of part of the gain in SNR, we had wanted to achieve at 3T. An example of reduction of a metallic artifact from optimized high-bandwidth protocols is shown in Fig. 3.24. Another approach for metal implant artifact reduction is the use of “view-angle tilting” (Olsen et al. 2000; Sutter et al. 2012) (Fig. 3.25).

3.4.3 Other Challenges at 3T

High-field MRI scanners equipped with high- density phased-array coils show more details in high spatial resolution, but any artifacts are also exacerbated. A well-known pitfall in high-field scans is the occurrence of regional signal varia-tions across the FOV caused by inhomogeneity

a b

Fig. 3.23 (a) Susceptibility-weighted MR image at 3T shows a large blooming artifact at the right motor strip on SWI secondary to a small hemorrhagic scar depicted on the (b) T2-W MR image


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of the static (B0) and radio-frequency (B1) mag-netic field. These problems have now largely been overcome, or solutions have been offered (Tanenbaum 2006). Another component that can influence the regional sensitivity of an image is the receiver coil. Phased-array coils are a

state-of- the-art development, generally com-posed of a number of mutually decoupled surface coils. The individual signals from these coil ele-ments are combined in post-processing. Homogeneity of the receiver coil is subject to the characteristics of the coil elements and how the

a b

Fig. 3.24 Proton density images of a magnetic object (surgical nail) placed in a water bath in a plane perpen-dicular to its axis. (a) Standard bandwidth of 200 Hz/pixel

and (b) increased bandwidth of 445 Hz/pixel. Note the significant decrease in distortion, but at the cost of a loss in SNR by a factor of two

a b

Fig. 3.25 Knee MR image with a metallic ACL recon-struction screw. (a) Image obtained with standard TSE PD (TR/TE 3,000/33) and (b) with additional “view-angle

tilting.” Note the reduction of the metal artifact and improvement in image quality


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coil elements are arranged in the housing. For a head coil, the image signal is higher in the periph-ery than in the center, as demonstrated in Fig. 3.26 (Mekle et al. 2008). It shows unfiltered high- and low-signal regions with regard to the coil ele-ments. Although filters for equalizing signal intensities are used (Vemuri et al. 2005), it is not intuitive which effects (B0-, B1-, or receive coil heterogeneity) are dominant. This can be prob-lematic in the evaluation for hippocampal epi-lepsy, since asymmetry in the hippocampal signal could be attributed to early pathological sclerosis versus artifactual inhomogeneity.

Conclusion

With this brief discussion on pitfalls in MRI, we will now focus on future prospects: noise as an unwanted disturbance – an avoidable pit-fall. Supply induces demand. In the initial stages of the use of MRI, protocols comprised PD-/T1-/T2-weighted imaging in different planes only. With advances in MRI, there is now an extensive number of protocols. For example, a neuro- protocol for tumor imaging may read T1-/T2-weighted imaging, suscepti-bility- or diffusion- weighted imaging, perfu-sion imaging, spectroscopic imaging, and

contrast-enhanced T1-weighted imaging. Within the almost same time period of a slot, a tremendous increase in information about the pathological tissue is now available. However, is there a need for this overwhelming amount of data? The answer depends on the clinical indications and working hypotheses.

In the clinical setting, thorough and careful input from the physician goes a long way in tailoring the necessary sequences for the MRI study and optimal resolution for the region of interest to be studied in a particular patient, be it for screening, diagnosis, staging, presur-gical planning, or the evaluation of response to treatment. This also needs to be weighed against patient’s condition and comfort and sometimes conflicting demands to optimize patient throughputs and scanner econom-ics. In this scenario, our wish-for- more may compromise some of the protocols. This may result in pitfalls or shortcomings in MRI, as per what we have described in the preceding paragraphs. The gathering of redundant and insufficient data is an unwelcome distraction during reporting. The overall view becomes noisy again, and this itself is also a major pit-fall in MRI.

a b

Fig. 3.26 Phased-array coil. (a) CT image of a 12- channel head coil shows the positions of the coil ele-ments in relation to MR image signal variations of an oil phantom of 30 cm in diameter (CT and MR images are

superimposed). Higher sensitivities near the coil element are observed. (b) Subject’s head needs to be in the epicen-ter for accurate left-to-right signal intensity comparisons


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Acknowledgment A big thank you to Ms. N. Kaarmann (Siemens AG Healthcare Sector, Erlangen, Germany) for aiding us in “producing and avoiding artifacts” in this work.

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