Technical noteOn the effects of gating in diffusion imaging of the brain using single shot EPI
Introduction
Diffusion tensor imaging (DTI) requires high SNR DTI data for the estimation of all elements of the diffusion tensor. To obtain optimal SNR in the DTI data several issues have been investigated in the literature. These include e.g. optimal diffusion gradient schemes [1], [2]. In any diffusion experiment, minimizing artifacts due to different types of macroscopic motion is of critical importance. For non-single shot EPI sequences, navigator echoes are frequently used to remove e.g. patient head motion. It has been shown that for various multi shot sequences in the brain, cardiac gating is also of great importance [3], [4], [5], [6], [7], [8]. For single shot EPI, patient motion can generally be neglected during the acquisition window, which implies that navigator correction is usually unnecessary. However, it may still be of importance to perform gating even though single shot techniques are used, because even in this time frame brain motion [9], [10] of some parts of the brain is large compared to molecular Brownian motion leading to signal voids in the diffusion weighted image. This leads to artifactually high estimates of the apparent diffusion coefficient (ADC). A similar tissue motion effect has been shown in detail in for the abdomen [11]. For the brain Brockstedt et al. [12] have shown that cardiac gating is beneficial, but no thorough analysis has yet been performed. In this work we have investigated the need for gating the diffusion weighted single shot EPI sequence for brain studies. We have also examined where in the brain gating is most critical and which optimal trigger delay after the pulse wave that minimizes the variance in the DWI data.
Section snippets
Materials and methods
The experiments were performed on a 1.5T GE Signa Echospeed (GE Medical Systems, Milwaukee, WI, USA). Four healthy volunteers were scanned using a diffusion weighted single shot spin echo EPI sequence. In order to get a reasonable total experiment time, the diffusion weighted (DW) gradients were applied in one direction only, the z or through slice direction. Hence, our data set does not allow for estimation of the DT parameters but rather demonstrates the test-retest reliability of a single
Results
In Fig. 1 one slice from one volunteer is shown from two different experiments; ungated (a) and gated with a TD of 500 ms (b). In Fig. 1a the effect of the heartbeats is evident. About 20% of the images are affected by severe brain motion artifacts. This was consistent across all volunteers in this region of the brain. Closer inspection reveals an even higher fraction of the images with minor degradation. This reflects the “probability” to get severe signal dropout for one single slice when
Discussion
Minimizing the variance and artifacts in DW data as well as minimizing the experiment time is desirable. One rationale for not performing gating in a diffusion imaging experiment is the shorter experiment time. For e.g. a DTI study with 28 slices and only 6 diffusion encoding directions (plus one b = 0 s/mm2) the minimum TR is about 7 seconds on our MR scanner, because gradient heating limitations does not allow more than about 4 slices per second. The experiment time in this example is 7 × 7 =
Conclusion
In conclusion, these results suggest that DTI experiments in the brain should be gated, unless only the part of the brain above corpus callosum is of interest. By not performing gating severe signal dropouts will occur at and below that level. Even though ungated DTI experiments yields shorter imaging times, gating will result in more accurate data for any given scan time due to its comparatively low variance. A trigger delay of 500 ms relative to the peripheral pulse wave was found to be
References (15)
- et al.
Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI
J Magn Reson
(2000) - et al.
High-resolution diffusion imaging using phase-corrected segmented echo-planar imaging
Magn Reson Imaging
(2000) - et al.
Quantification of low-velocity motion using a navigator-echo supported MR velocity-mapping techniqueapplication to intracranial dynamics in volunteers and patients with brain tumours
Magn Reson Imaging
(1997) - et al.
Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging
Magn Reson Med
(1999) - et al.
Reducing motion artefacts in diffusion-weighted MRI of the brainefficacy of navigator echo correction and pulse triggering
Neuroradiology
(2000) - et al.
Diffusion imaging of the human brain in vivo using high-speed STEAM MRI
Magn Reson Med
(1992) - et al.
Quantitative measurement of tissue perfusion and diffusion in vivo
Magn Reson Med
(1991)
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2022, NeuroImageCitation Excerpt :Approaches prior to and brought by the HCP: Traditionally, images with severe outliers were simply removed upon visual inspection, but more advanced approaches have been proposed since. Cardiac gating during acquisition has been adopted in several studies to avoid imaging during those periods of the heart cycle with the greatest motion (Nunes et al., 2005; Skare and Andersson, 2001), but at the cost of increased scan time and varying temporal gaps between slice acquisitions, which can in turn lead to e.g. different effects of signal relaxation (Mohammadi et al., 2013). Voxel-wise outliers are typically detected by using the information across DWIs in a robust fitting procedure.
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