Prospective motion correction for 3D pseudo-continuous arterial spin labeling using an external optical tracking system

Arterial spin labeling MRI using spiral acquisitions and concurrent field monitoring

Perfusion MRI based on arterial spin labeling (ASL) has intrinsically very low signal-to-noise ratio (SNR). Signal acquisition at shorter echo times (TE) is necessary to boost the SNR of the ASL images. Spiral trajectories provide substantially shorter TE yielding increased SNR and are among the fastest k-space sampling schemes to encode a given field of view and resolution. Moreover, they provide approximately isotropic point-spread functions and inherent refocusing of motion- and flow-induced phase errors. However, the efficiency of the spiral acquisitions in ASL-MRI has been limited because these advantages are counterbalanced by practical technical challenges. This is because spiral acquisitions are highly sensitive to encoding deficiencies such as static off-resonance in the main magnetic field manifested as blurring artifacts in the image. Moreover, deviation of the gradient fields from the nominal waveforms due to the imperfection of the employed hardware critically limits the practical utilization of spiral trajectories. In this work, I provide single- and multiple-shot spiral ASL images that are robust against typical spiral encoding drawbacks enabled by deploying a comprehensive signal model involving static off-resonance and coil sensitivity maps and actual B0 and gradient field dynamics up to third order in space. The spiral ASL signal acquisition was concurrently monitored using a 3rd order dynamic field camera based on NMR field probes. The reconstructed ASL images at 3 mm and 2 mm in-plane resolution associating with the monitored field dynamics and the static off-resonances exhibited strongly reduced blurring- and aliasing artifacts and distortion. Concurrent field monitoring also enables to account for quasi-static B0 drifts by encompassing the parametric input data with consistent encoding geometry and physiological field fluctuations. In conclusion, concurrent field monitoring in spiral ASL acquisition largely overcomes traditional vulnerability of spiral trajectories in practice providing high quality ASL images with increased SNR, speed and motion robustness.

Quantifying MR Head Motion in the Rhineland Study - A Robust Method for Population Cohorts

Head motion during MR acquisition reduces image quality and has been shown to bias neuromorphometric analysis. The quantification of head motion, therefore, has both neuroscientific as well as clinical applications, for example, to control for motion in statistical analyses of brain morphology, or as a variable of interest in neurological studies. The accuracy of markerless optical head tracking, however, is largely unexplored. Furthermore, no quantitative analysis of head motion in a general, mostly healthy population cohort exists thus far. In this work, we present a robust registration method for the alignment of depth camera data that sensitively estimates even small head movements of compliant participants. Our method outperforms the vendor-supplied method in three validation experiments: 1. similarity to fMRI motion traces as a low-frequency reference, 2. recovery of the independently acquired breathing signal as a high-frequency reference, and 3. correlation with image-based quality metrics in structural T1-weighted MRI. In addition to the core algorithm, we establish an analysis pipeline that computes average motion scores per time interval or per sequence for inclusion in downstream analyses. We apply the pipeline in the Rhineland Study, a large population cohort study, where we replicate age and body mass index (BMI) as motion correlates and show that head motion significantly increases over the duration of the scan session. We observe weak, yet significant interactions between this within-session increase and age, BMI, and sex. High correlations between fMRI and camera-based motion scores of proceeding sequences further suggest that fMRI motion estimates can be used as a surrogate score in the absence of better measures to control for motion in statistical analyses.

Robust single-shot acquisition of high resolution whole brain ASL images by combining time-dependent 2D CAPIRINHA sampling with spatio-temporal TGV reconstruction

For ASL perfusion imaging in clinical settings the current guidelines recommends pseudo-continuous arterial spin labeling with segmented 3D readout. This combination achieves the best signal to noise ratio with reasonable resolution but is prone to motion artifacts due to the segmented readout. Motion robust single-shot 3D acquisitions suffer from image blurring due to the T2 decay of the sampled signals during the long readout. To tackle this problem, we propose an accelerated 3D-GRASE sequence with a time-dependent 2D-CAIPIRINHA sampling pattern. This has several advantages: First, the single-shot echo trains are shortened by the acceleration factor; Second, the temporal incoherence between measurements is increased; And third, the coil sensitivity maps can be estimated directly from the averaged k-space data. To obtain improved perfusion images from the undersampled time series, we developed a variational image reconstruction approach employing spatio-temporal total-generalized-variation (TGV) regularization. The proposed ASL-TGV method reduced the total acquisition time, improved the motion robustness of 3D ASL data, and the image quality of the cerebral blood flow (CBF) maps compared to those by a standard segmented approach. An evaluation was performed on 5 healthy subjects including intentional movement for 2 subjects. Single-shot whole brain CBF-maps with high resolution3.1 × 3.1 × 3 mm and image quality can be acquired in 1min 46sec. Additionally high quality CBF- and arterial transit time (ATT) -maps from single-shot multi-post-labeling delay (PLD) data can be gained with the proposed method. This method may improve the robustness of 3D ASL in clinical settings, and may be applied for perfusion fMRI.

Rigid Motion Correction for Brain PET/MR Imaging using Optical Tracking

A significant challenge during high-resolution PET brain imaging on PET/MR scanners is patient head motion. This challenge is particularly significant for clinical patient populations who struggle to remain motionless in the scanner for long periods of time. Head motion also affects the MR scan data. An optical motion tracking technique, which has already been demonstrated to perform MR motion correction during acquisition, is used with a list-mode PET reconstruction algorithm to correct the motion for each recorded event and produce a corrected reconstruction. The technique is demonstrated on real Alzheimer's disease patient data for the GE SIGNA PET/MR scanner.

Markerless motion tracking and correction for PET, MRI, and simultaneous PET/MRI

OBJECTIVE

We demonstrate and evaluate the first markerless motion tracker compatible with PET, MRI, and simultaneous PET/MRI systems for motion correction (MC) of brain imaging.

METHODS

PET and MRI compatibility is achieved by careful positioning of in-bore vision extenders and by placing all electronic components out-of-bore. The motion tracker is demonstrated in a clinical setup during a pediatric PET/MRI study including 94 pediatric patient scans. PET MC is presented for two of these scans using a customized version of the Multiple Acquisition Frame method. Prospective MC of MRI acquisition of two healthy subjects is demonstrated using a motion-aware MRI sequence. Real-time motion estimates are accompanied with a tracking validity parameter to improve tracking reliability.

RESULTS

For both modalities, MC shows that motion induced artifacts are noticeably reduced and that motion estimates are sufficiently accurate to capture motion ranging from small respiratory motion to large intentional motion. In the PET/MRI study, a time-activity curve analysis shows image improvements for a patient performing head movements corresponding to a tumor motion of ±5-10 mm with a 19% maximal difference in standardized uptake value before and after MC.

CONCLUSION

The first markerless motion tracker is successfully demonstrated for prospective MC in MRI and MC in PET with good tracking validity.

SIGNIFICANCE

As simultaneous PET/MRI systems have become available for clinical use, an increasing demand for accurate motion tracking and MC in PET/MRI scans has emerged. The presented markerless motion tracker facilitate this demand.

Markerless high-frequency prospective motion correction for neuroanatomical MRI

PURPOSE

To integrate markerless head motion tracking with prospectively corrected neuroanatomical MRI sequences and to investigate high-frequency motion correction during imaging echo trains.

METHODS

A commercial 3D surface tracking system, which estimates head motion by registering point cloud reconstructions of the face, was used to adapt the imaging FOV based on head movement during MPRAGE and T₂ SPACE (3D variable flip-angle turbo spin-echo) sequences. The FOV position and orientation were updated every 6 lines of k-space (< 50 ms) to enable "within-echo-train" prospective motion correction (PMC). Comparisons were made with scans using "before-echo-train" PMC, in which the FOV was updated only once per TR, before the start of each echo train (ET). Continuous-motion experiments with phantoms and in vivo were used to compare these high-frequency and low-frequency correction strategies. MPRAGE images were processed with FreeSurfer to compare estimates of brain structure volumes and cortical thickness in scans with different PMC.

RESULTS

The median absolute pose differences between markerless tracking and MR image registration were 0.07/0.26/0.15 mm for x/y/z translation and 0.06º/0.02º/0.12° for rotation about x/y/z. The PMC with markerless tracking substantially reduced motion artifacts. The continuous-motion experiments showed that within-ET PMC, which minimizes FOV encoding errors during ETs that last over 1 second, reduces artifacts compared with before-ET PMC. T₂ SPACE was found to be more sensitive to motion during ETs than MPRAGE. FreeSurfer morphometry estimates from within-ET PMC MPRAGE images were the most accurate.

CONCLUSION

Markerless head tracking can be used for PMC, and high-frequency within-ET PMC can reduce sensitivity to motion during long imaging ETs.

Prospective motion correction with NMR markers using only native sequence elements

PURPOSE

To develop a method of tracking active NMR markers that requires no alterations of common imaging sequences and can be used for prospective motion correction (PMC) in brain MRI.

METHODS

Localization of NMR markers is achieved by acquiring short signal snippets in rapid succession and evaluating them jointly. To spatially encode the markers, snippets are timed such that signal phase is accrued during sequence intervals with suitably diverse gradient actuation. For motion tracking and PMC in brain imaging, the markers are mounted on a lightweight headset. PMC is then demonstrated with high-resolution T₂ *- and T₁ -weighted imaging sequences in the presence of instructed as well as residual unintentional head motion.

RESULTS

With both unaltered sequences, motion tracking was achieved with precisions on the order of 10 µm and 0.01° and temporal resolution of 48 and 39 ms, respectively. On this basis, PMC improved image quality significantly throughout.

CONCLUSION

The proposed approach permits high-precision motion tracking and PMC with standard imaging sequences. It does so without altering sequence design and thus overcomes a key hindrance to routine motion tracking with NMR markers. Magn Reson Med 79:2046-2057, 2018. © 2017 International Society for Magnetic Resonance in Medicine.