Limitations of Parallel Imaging 177
O. Dietrich, PhD
Department of Clinical Radiology, University Hospitals – Grosshadern, Ludwig Maximilian University of Munich, Marchioninistr. 15, 81377 Munich, Germany
C O N T E N T S
17.1 Introduction 177
17.2 Technical Requirements 177
17.2.1 Multi-Channel Receiver Hardware 177 17.2.2 Multi-Element Coil Systems 177 17.2.3 Image Reconstruction System 178 17.3 Image Quality and Artefacts 178 17.3.1 Signal-to-Noise Ratio 178 17.3.2 Localized Image Artefacts 179 17.4 Conclusion 179
References 179
Limitations of Parallel Imaging 17
Olaf Dietrich
17.1
Introduction
Parallel imaging has been shown to be extremely valuable in a large number of MR applications and provides many substantial advantages summarized in the preceding chapter; however, there are also certain limitations associated with parallel-acquisi- tion techniques, e.g. with respect to technical pre- conditions as well as image quality. Knowledge of these limitations is essential for the application of parallel imaging in general and for the design and optimization of parallel-imaging protocols in par- ticular. Typical and important limitations associated with parallel-imaging techniques are discussed in the following sections.
17.2
Technical Requirements
Parallel imaging is based on the combination of data acquisition with multi-element coil systems, on the one hand, and sophisticated reconstruction algo- rithms for undersampled multi-channel data, on the other hand. Consequently, an MRI system must fulfi l certain specifi cations to be suited for parallel imag- ing.
17.2.1
Multi-Channel Receiver Hardware
The MRI system must allow for parallel data acquisi- tion through several independent RF receiver chan- nels. Although the minimum theoretical number of channels required for parallel imaging is two, generally at least 48 channels are recommended for parallel acquisition in clinical routine. For parallel imaging with more fl exible imaging geometries or for whole- body applications, even more receiver channels and coil connectors are required (cf. Chaps. 13 and 44);
thus, MRI systems for state-of-the-art parallel imaging should provide several (e.g. 832) RF receiver chan- nels, i.e. in particular a correspondingly large number of independent RF amplifi ers as well as extensive con- nective wiring, which considerably increase the com- plexity and costs of such MRI systems.
17.2.2
Multi-Element Coil Systems
In addition to the extended receiver capabilities of the MRI system, appropriate coil systems are needed for parallel MRI (cf. Chaps. 14 and 44). These coil sys- tems should provide a large number of independent elements optimally arranged for parallel acquisition techniques. If the coil elements are distributed along a
178 O. Dietrich
single direction (e.g. from left to right), parallel imag- ing is restricted to applications with phase encoding in this direction (e.g. to MRI in axial or coronal ori- entation with phase encoding in leftright direction).
As a rule of thumb, the highest possible acceleration factor, R, is given by the number of independent coil elements in phase-encoding direction.
To allow for a fl exible choice of image orientation, phase-encoding direction, and acceleration factor, multi-element coils are required with a large number of elements distributed uniformly around the patient.
With such coil systems, available, for example, for MRI of the head, high acceleration factors are feasible in all spatial directions. In body MRI, however, high acceleration factors are typical restricted to leftright and headfeet direction. In anteriorposterior direc- tion, parallel imaging often remains limited to maxi- mum acceleration factors of R=2 because of the typi- cal coil confi guration and the oblateoval shape of the human abdomen and thorax (cf. Chap. 21). In general, the choice of several protocol parameters, such as image orientation, phase-encoding direction, or fi eld of view, is more limited in parallel imaging than in conventional imaging and depends substan- tially on the coil systems used.
17.2.3
Image Reconstruction System
The separately acquired undersampled raw-data sets from all coil elements must be combined to a single resulting image data set without remaining aliasing artefacts. This is done with reconstruction algorithms that are generally much more complicated and com- putationally demanding than conventional image reconstruction, which is usually based on the (fast) Fourier transform of the acquired data. In particu- lar, raw-data sets acquired for parallel imaging are typically very large because they consist of data from multiple separate coil elements; thus, large amounts of memory as well as very fast reconstruction systems are required in order to reconstruct these data sets within acceptable times. Consequently, many state- of-the-art parallel-imaging protocols depend on the newest generation of image reconstruction systems and will be prohibitively slow when transferred to older systems.
Several different reconstruction algorithms are provided by the vendors of MRI systems (cf. Chap. 2) with certain advantages and disadvantages with respect to image quality and reconstruction time. The
optimization of parallel-imaging reconstruction is still a major subject of current research (cf. Chap. 46), and regular updates to the newest and most effi cient algorithms are recommendable to constantly provide the best possible image quality.
17.3
Image Quality and Artefacts
Apart from the technical limitations mentioned above, the obtained image quality is the most impor- tant factor to be considered when applying parallel- acquisition techniques. Image quality in the context of parallel imaging is characterized by two aspects:
the signal-to-noise ratio (SNR) and localized image artefacts.
17.3.1
Signal-to-Noise Ratio
The reduced SNR of parallel MRI is an intrinsic disadvantage common to all accelerated imaging techniques that acquire reduced data sets in order to shorten the scan time. As described in Chap. 1, the SNR is proportional to the square root of the total time spent for data acquisition (Edelstein et al. 1986; Haacke et al. 1999) and, thus, decreases with increasing acceleration. Consequently, MRI with a parallel-imaging acceleration factor of R=4 is asso- ciated with (at least) a 50% loss of SNR; therefore, parallel imaging is particularly suited for applica- tions with originally high SNR. Typical examples are applications that are restricted by acquisition time rather than SNR such as abdominal breath-hold MRI, contrast-enhanced fi rst-pass MR angiography, or time-resolved MRI. On the other hand, non-acceler- ated protocols with very low SNR and in particular MRI at low-fi eld systems with fi eld strengths, B0, of less than 1 T, will frequently not benefi t from parallel imaging. An exception to this general rule are certain low-SNR applications for that parallel imaging can be employed as a means to reduce motion sensi- tivity by averaging of multiply repeated accelerated acquisitions, i.e. without reduction of scan time (cf.
Chap. 5).
It is also noteworthy that signal-to-noise losses become even more signifi cant if parallel imaging is applied to increase the spatial resolution. A non-accel-
Limitations of Parallel Imaging 179
erated three-dimensional acquisition with isotropic spatial resolution of 1×1×1 mm³ may be converted to a protocol with acceleration factor R=4 and substantially improved isotropic resolution of 0.5×0.5×0.5 mm³ covering the same total volume of interest (i.e. the same three-dimensional fi eld of view). If the echo (or readout) duration is kept constant by increasing the receiver bandwidth, the total scan time of both pro- tocols will be identical, since the increased number of phase-encoding steps is compensated by the paral- lel-imaging acceleration; however, the voxel volume is reduced to an eighth of the original value and, thus, the SNR decreases as well by almost 90 %. For most protocols, this SNR loss will not be acceptable, which means that the theoretical potential of parallel imag- ing cannot always be completely exploited.
In addition to the SNR loss due to acceleration, image noise is also regionally amplifi ed. This effect is quantitatively described by the g-factor (cf. Chap. 3;
Pruessmann et al. 1999). Noise amplifi cation depends on several parameters such as the coil geometry, the image orientation, and the acceleration factor, R, and typically appears as band-like structures over central image parts (cf. Fig. 2 of Chap. 3). Obvious disadvan- tages of such varying noise levels are that the SNR may be subjectively overestimated (based on lower noise levels outside the noise bands) resulting in unaccept- ably low SNR is some parts of the image. Furthermore, the objective determination of SNR and CNR is made much more diffi cult in parallel imaging than in conven- tional MRI as discussed in Chap. 4. To avoid degrading noise amplifi cation, parallel-imaging acceleration, i.e.
the acceleration factor, R, as well as the acceleration (or phase-encoding) direction, must be chosen appropri- ate with respect to the used coil system.
17.3.2
Localized Image Artefacts
Since parallel imaging is based on undersampling of k-space data in phase-encoding direction, aliasing (fold-over or wrap-around) artefacts may appear due to imperfect parallel-imaging reconstruction. These localized aliasing artefacts are complementary to noise amplifi cation in parallel imaging; i.e., depending on the reconstruction algorithm, resulting images may contain either more stochastic noise and fewer remain- ing aliasing artefacts, or, vice versa, a lower noise level but more remaining aliasing. Further improvements of reconstruction techniques aim at optimally balancing both sources of artefacts (cf. Chap. 46).
A specifi c problem of parallel MRI with image-space- based reconstruction (e.g. with SENSE-related tech- niques) are residual aliasing artefacts in central parts of the fi eld of view that arise if the reconstructed full fi eld of view is smaller than the imaged object (Griswold et al. 2004; Goldfarb 2004); examples are shown in Fig. 7 of Chap. 1, and Fig. 1 of Chap. 21. The k-space-based reconstruction has been shown to be generally more robust for MRI with small fi elds of view.
17.4 Conclusion
There are two signifi cant limitations to the application of parallel imaging: these are, on the one hand, rela- tively demanding hardware requirements including multi-channel RF receivers as well as multi-element coil systems combined with appropriate reconstruc- tion systems and software. Most currently available new MRI systems fulfi l all these requirements for parallel imaging or can be upgraded relatively easily, but older existing installations will often be too lim- ited and not fl exible enough for parallel imaging. On the other hand, not all protocols are equally suited for parallel imaging, and certain restrictions with respect to SNR, image geometry, or maximum achiev- able acceleration factors must be kept in mind. Nev- ertheless, parallel imaging has turned out to be one of the most important recent developments in MR imaging, impacting examination protocols in virtu- ally all areas of research imaging and clinical MRI.
References
Edelstein WA, Glover GH, Hardy CJ, Redington RW (1986) The intrinsic signal-to-noise ratio in NMR imaging. Magn Reson Med 3:604–618
Griswold MA, Kannengiesser S, Heidemann RM, Wang J, Jakob PM (2004) Field-of-view limitations in parallel imaging.
Magn Reson Med 52:1118–1126
Goldfarb JW (2004) The SENSE ghost: fi eld-of-view restrictions for SENSE imaging. J Magn Reson Imaging 20:1046–1051 Haacke EM, Brown RW, Thompson MR, Venkatesan R (1999)
Magnetic resonance imaging: physical principles and sequence design. Wiley-Liss, New York
Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P (1999) SENSE: sensitivity encoding for fast MRI. Magn Reson Med 42:952–962
