The system we have presented and evaluated shares many design decisions with the previously published PROMO method [10
]: we use an image-based navigator, update the imaging coordinates during dead-time in the parent sequences, and can reacquire motion-damaged TRs at the end of the scan. These similarities make it important to also outline some of the substantial differences between our system and PROMO, which we will briefly do in this section.
The PROMO system requires 100 ms per navigate-and-register block, but must repeat this block multiple times per TR in order to achieve its high-quality motion estimate. In the published description of PROMO’s integration with neuroanatomical sequences, the block was repeated five times, giving a total navigate-and-register time of 500 ms. By comparison, we acquire and register a single vNav per TR, requiring 355 ms on current Siemens hardware. This difference can be seen as two choices along a trade-off. While the PROMO system acquires a less-informative navigator, it does so quickly and has the flexibility to acquire fewer of them if necessary. By using vNavs, we decide to spend somewhat less overall time acquiring a more-informative navigator in one block and then use all the information to register it at the end. However, our method comes at the expense of flexibility should a shorter navigator be required.
We have opted to insert our navigate-and-update block directly before the readout train in each of the three sequences described here while the PROMO system applies its navigate-and-update block following the readout train in each TR. This can be seen as a trade-off selecting the lag between the motion estimate and the parent sequence readout train, and the interactions between the navigator and the parent sequence. Note that because our navigator excites the whole imaging volume with each pulse, we do not induce a “slice shadow” in our parent volumes from placing our navigator before the parent sequence readout train. However, our placement does impose a minimum TI gap that occasionally conflicts with very high-resolution MEMPRAGE sequences as their readout trains become quite long. Conversely, placing the navigator after readout, as in PROMO, constrains the minimum TR or maximum TI.
Our selective-reacquisition system is also similar to PROMO, in that we use the estimated motion from the navigators bracketing each TR to produce a motion score. The principle differences are that, while PROMO scans have a variable time and stop when a selected maximum motion score is reached, our system fixes the total scan time and then uses the whole time to keep improving the k-space measurements. Additionally, where PROMO uses the 1-norm of the estimated rotation and translations, we produce a motion score by calculating the worst-case displacement of a point on a sphere with 64 mm radius, centered in the imaging volume.
As the system is in many concrete ways different from PROMO, we have attempted to evaluate our design decisions with a series of experiments evaluating both the accuracy of the system and its impact on the signal measured by the parent sequence.
Considering , our system produces substantially more accurate estimates at 3 T over 1.5 T, which we expect is due to the higher SNR. Additionally, we find that the 32-channel coil produces less accurate estimates than the 12-channel coil; although we are continuing to explore why this is the case, we note that in all field and coil configurations, the measured error is small enough to be useful for our morphometry protocols. The median absolute value of the motion score gives an indication of the most-displaced point inside a subject brain due to jitter; referring to we can see that this value is on the order of 0.5 mm or less, making it generally acceptable for the resolutions used in neuroanatomical imaging.
In we plot the effects the navigators, motion correction, and reacquisition each have on the parent sequences’ white and grey matter intensities. The first column of the plot shows the natural variation in voxel intensities over three runs when no navigators are present. The subsequent three columns allow us to study artifacts that a navigator-based motion-correction system might introduce:
- Local intensity changes would appear as off-diagonal islands of voxels. We used a spatially non-selective pulse in our navigator, and so we expected that any intensity changes in the image would be spatially uniform. Note that even very small islands, those that might not be apparent in mean or variance measurements, should stand out on our plots. The lack of off-diagonal islands in 4 indicates that our system has not introduced local intensity changes.
- Local changes in variability would appear as a broadening of the grey or white matter ridge around the main diagonal at a specific point. Again, if the effect were small or local enough, it might not be particularly apparent in summary statistics, but should be clear in the density plots. Since we do not see local broadening in any of the experimental conditions, our system has not introduced any local changes in variability.
- Global changes in grey/white contrast would appear as a separation of the lines of best fit for white and grey matter. Across all conditions, the largest observed contrast change was in T2SPACE FLAIR with a 1.1% effect, while MEMPRAGE showed at most a 0.1% contrast effect and T2SPACE showed at most 0.7%. For comparison, our repeated scanning without any navigators also shows a contrast variation of 0.1% for MEMPRAGE, 0.3% for T2SPACE, and 0.4% for T2SPACE FLAIR, indicating that there may be a < 1% global contrast effect attributable to our system in T2SPACE-type sequences.
- Global changes in intensity appear as the lines of best fit for white and grey matter moving away from the 1.0 ratio dashed line. In the MEMPRAGE and T2SPACE sequences, we see the slightly decreased intensity we expected due to the introduction of the navigator pulses; an effect of approximately 3%. Unexpectedly, we see a very small increase in the T2SPACE FLAIR intensity, although this effect is so small that we cannot make any significant claims about it.
In general, the scale of the observed effects and the fact that they seem to be global both spatially and across tissue types, gives us confidence that the introduction of vNavs and our motion correction system is unlikely to induce changes in tissue intensity or relative contrast that would be detrimental to either a human reader using the images diagnostically or a machine system performing automatic processing on the volumes.
In our directed motion studies, a visual inspection of the five conditions for each subject revealed that, as expected, the images reconstructed with prospective motion correction and reacquisition are more similar to the no-motion images than the volumes produced with prospective correction but no reacquisition, and these are in turn better than the scans without prospective motion correction (see ).
The results in show that for all subjects the navigators induce a very small amount of jitter-based ghosting outside the head even when the subject does not move. Interestingly, this data shows that ghosting is worse in the case of motion-correction-without-reacquisition condition than when the subject moved without any motion correction applied. We note that this may be because, during the central portion of scanning (i.e., the portion containing the most scan energy) the subject freely moved continuously and thus the motion estimates may not have been fully in line with the subject’s position, perhaps even making the misalignment worse than when the subject’s motion was simply “averaged out” in the motion-without-motion-correction condition. This also agrees with the result we see in the last row of the table, where the mean ghost intensity is greatly reduced by the inclusion of the reacquired measurements of these TRs.
The Dice coefficients in indicate that, for all subjects, there is a degradation of the FreeSurfer segmentation with subject motion. We also see that the segmentation improves with the use of motion correction, and improves almost back to the initial no-motion results when reacquisition is employed.