Fast Imaging Techniques - Report Example

Fast Imaging Techniques (MRI) Insert (s) Fast Imaging Techniques (MRI Discuss the chain of consequences if you optimise the image by increasing the receiver bandwidth. When the image is optimised by increasing the receiver bandwidth, a number of sequences occur before the required field of view and matrix size of the T2 weighted image is achieved. Receiver bandwidth is generally used to fasten the digitalisation of the MR signals. In this regard, the receiver bandwidth 1 can determine the frequency ranges that will eventually be sampled using the frequency encoding gradient. During the optimization through an increase of receiver bandwidth, the amount of time at the flat top of the gradient is significantly reduced. Consequently, the shortened duration of flat top reduces both ESP and the geometric distortion of the image (Jezzard and Balaban, 1995, p.71). Another consequence of increasing the receiver bandwidth is faster imaging. Although increasing the receiver bandwidth allows faster imaging, it may also significantly reduce the SNR, and this often leads to more noise outside the spectrum (Parrish, 2000, p.927). For example, as the bandwidth range is gradually increased, the system may begin to sample more inherent noise together with the generated echo signal, thereby resulting in the fall of SNR. There are a number of ways that can generally be used to help recover the signals lost as a result of a wider bandwidth during the optimization of image. Some of the choices include acquisition of more signal averages and improving the receiver coil technology. The first option is, however, counter-productive because it may increase the amount of time needed to perform the overall scan while the second option if often preferred because it helps maintain the original objective of choosing EPI. Lastly, with regard to the required T2 weighted image, increasing the receiver bandwidth may reduce the effects of chemical shift artefacts on the image. According to Ra and Rim (1993, p.145), this is because higher receiver bandwidth results in a wide range of resonant frequencies on which the distortion is spread in order to cover a smaller pixel range and minimize the geometric distortion. 2. Discuss the advantages and disadvantages of using segmentation in EPI. Segmentation is a new concept that has significantly made it possible to use EPI on most of the conventional imaging systems where constraints related to signal to noise would have otherwise prevented EPI. Segmenting EPI is increasingly becoming more important to a number of its properties that ensure improved image quality as compared to the conventional single shot EPI. For example, one of the potential benefits of segmentation is that it allows EPI to be able to effectively run on the conventional systems where single short EPI can not be used. This is because segmentation ensures less stress is placed on the gradients as opposed to single short EPI and is therefore critically important in situations where by the available SNR and hardware makes it difficult to acquire all the necessary k-space data before the elimination of the MR signal by the traverse relaxation (McRobbie et al., 2003, p.75). Another important advantage of segmented EPI is that it helps reduce the magnetic susceptibility of various artefacts. This is because phase errors often have less time to build up when segmented EPI as compared to single shot EPI. The shortening of echo train length also allows segmented EPI to be less prone to the effects of artefact variations. Segmentation can also be used to help reduce imaging distortion and enable higher image resolution as compared to single shot EPI. The other key benefit of segmentation of EPI is the fact that it can be used to increase resolution. This is particularly attributed to the fact that segmented EPI have relatively short echo train length, thereby leading to increased spatial resolution. On the other hand, normal single shot EPI usually have lower spatial resolution, and this makes segmentation more preferable. The shortening of echo train length also allows segmented EPI to be less susceptible to a number of variations as well as allow for the introduction of T1 weighing. Consequently, segmentation has made it easier to use EPI on most imaging systems where constraints are related to signal to noise, which was not previously possible with the single shot EPI. Although segmented EPIs offer numerous benefits, using more segments, however, comes with a number of disadvantages that can potentially affect the image quality. Some of the limitations of segmentation include the fact that performing segmented EPI usually takes longer scanning time as compared to single shot EPI. Despite the fact that segmented EPI has no significant geometric distortion artefacts, it is often difficult to be used in clinical practices because of the long scanning time that it requires. However, there are currently a number of ways which can be used to address the problem of long time scans caused by diffusion directions or the acquisition of k-space limit. For example, multi band modification can be performed on the segmented EPI to help reduce the length of scanning time. It is also important to note that the robustness of segmented EPI against various motion artefacts is usually substantially reduced because different states of patient motion can easily occur for each of the segments acquired. As a result, segmented EPI is also considered to be significantly more prone to motion artefacts. This weakness of EPI segmentation is, however, normally corrected by applying navigator echo correcting schemes (Poser and Norris, 2009, p.1168). Increased signal fluctuations have also been known to occur in segmented EPI and, consequently, SNR may be significantly affected during the imaging process. Lastly, the complex coverage of k-space also makes segmented EPI to be comparatively more susceptible to specific artefacts and cases of ghosting. This, consequently, affects the quality of image and may sometimes significantly increase the length of time it takes to acquire a multi shot (segmented) EPI image. 3. What is the difference between SMASH and SENSE reconstruction in parallel imaging? Sensitivity encoding (SENSE) and simultaneous acquisition of spatial harmonics (SMASH) are some of the commonly used reconstruction techniques in parallel imaging. The two techniques not only help in the improvement of signal to noise ratio, but also in the acceleration of acquisition and scan time reduction. Although the two reconstruction imaging techniques employ the use of coil sensitivity as their encoding scheme, a number of differences exist with regard to the way they use the information encoded (McRobbie et al., 2003, p.346). As a parallel reconstruction technique, SENSE is based on the assumption that each pixel within a phased array is made up of several signals weighed by the spin density and the sensitivity of the coil profile (Prussman et al., 1999, p.954). Consequently, SENSE ascertains the sensitivity of each of the elements in the phase array through the use of reference scan. Although this technique does not have any restrictions on the arrangement of elements within the phased array, it often results in loss of a given amount of signal to noise. SMASH technique also uses the sensitivity of the coil to encode images but in a different way. For example, as opposed to SENSE method, SMASH relies on the sinusoids derived from the patterns of the coils’ sensitivity. One of the main differences between the two reconstruction imaging techniques is that in sensitivity encoding (SENSE), image processing is achieved using image domain data while SMASH generally uses raw data (k-space data) to perform image processing. Consequently the characteristics of the two techniques are slightly different. According to Weiger (2000, p.672), SENSE reconstruction imaging is considered to be more susceptible than SMASH because there are usually no restrictions regarding the coil arrangements during imaging. It is also important to note that SENSE reconstruction imaging has a shorter reconstruction time as compared to SMASH. This is because the spatial harmonic algorithms that are used in SMASH reconstruction imaging are not only complicated but are also time consuming. In terms of signal noise, images produced using SMASH techniques are generally less noisy although they are more likely to be corrupted by artefacts (Sodickson and Manning, 1997, p.599). On the other hand, SENSE usually takes a longer reconstruction time and can also be used to provide better image quality. This is particularly because SMASH utilises an approximation technique that significantly helps in the reduction of reconstruction time but this is often associated with the loss of SNR. The other significant difference between SENSE and SMASH is based on the construction methods that they use. For example, when using the SENSE technique, the unfolding of the pixels within a phased array is usually done after the Fourier transformation of k-space data (Bammer R. 2002, p.128). On the other hand, simultaneous acquisition of spatial harmonics (SMASH) performs reconstruction by fitting the various harmonic functions that encode k-space before the Fourier transformation. In this regard, SMASH can effectively be used as a solution to the problem of aliasing during the reconstruction of partially encoded images while SENSE is more of a pixel by a pixel reconstruction technique. References Bammer, R. 2002. Diffusion tensor imaging using single-shot SENSE-EPI. Magn Reson Med 48:pp.128-136. Jezzard, P., and Balaban, R.S. 1995. Correction for geometric distortion in echo planar images from B0 field variations. Magnetic Resonance in Medicine 34: 65-73. McRobbie, D.W., Moore, E.A., Graves, M.J., and Prince, R. 2003. From Picture to Proton. New York, NY: Cambridge University Press. Poser, B.A., and Norris, D.G. 2009. Investigating the benefits of multi-echo EPI for fMRI at 7T. Neu- roimage 45: 1162–1172.  Parrish, T.B. 2000. Impact of signal-to-noise on functional MRI. Magnetic Resonance in Medicine 44(2): pp.925–932. Prussman, K.P., Wieger, M., Scheidegeer, M.B. and Boesiger, P. 1999. SENSE: Sensitivity encoding for fast MRI. Magnetic Resonance in Medicine 42(5): pp. 952-962. Sodickson, D.K., and Manning, W.J. 1997. Simultaneous acquisition of spatial harmonics (SMASH): Fast imaging with radiofrequency coil arrays. Magnetic Resonance in Medicine38: pp. 591-603. Ra, J.B., and Rim, C.Y.1993. Fast imaging using subencoding data sets from multiple detectors. Magnetic Resonance in Medicine 30: 142–145. Weiger, M. 2000. Contrast-enhanced 3D MRA using SENSE. J Magn Reson Imaging. 12:pp. 671-677. Read More