INTRODUCTION

Ultra high magnetic field strengths offer certain advantages for structural imaging such as a high SNR and resolution¹. However, there is still a problem with long scan time, as for traditional MRI scans, and consequently a high sensitivity to motion artifacts. In this study, prospective motion correction (PMC) with an optical tracking system was used to acquire structural images for diverse range of contrasts and resolutions. The main goal of this work was to investigated the stability and robustness of the optical tracking system for PMC in MRI on multiple recruited subjects. For this purpose, the image quality of the corrected and uncorrected images was assessed qualitatively and quantitatively.

METHODS

After written consent, 21 healthy subjects were scanned using a 7T MRI system (Siemens, Erlangen, Germany) with a 32-channel head coil (Nova Medical, Wilmington, USA) and were asked not to move during examination. For tracking rigid head motion, a single in-bore camera tracked position of a marker (MT384ib, Metria Innovation Inc., Milwaukee, WI,USA), which was rigidly attached to the subject’s upper jaw with an individually manufactured mouthpiece². During scanning of each subject, every sequence was repeated twice, with and without PMC, and the order of acquisition PMC ON - PMC OFF was completely randomized. The following sequences were acquired: a 3D-MPRAGE sequence, T1-weighted (T1-w) images, full brain acquisition, 0.45x0.45x0.45 mm³, TR/TE/TI 2820/2.82/1050 ms, FA 5°; a 2D-TSE sequence, T2-weighted (T2-w) and PD-weighted (PD-w) images, TR/TE_T2-w / TE_PD-w, 6000/59/9.9 ms, FA 130°, voxel size 0.28x0.28x1.0 mm³; a 2D-GRE sequence, T2*-weighted (T2*-w) images, with 3 different in-plane resolutions, 0.5x0.5/0.35x0.35/0.25x0.25 mm², slice thickness 1.5 mm, TR/TE₀₅/TE0₃₅/TE0₂₅, 680/16.6/15.1/16.6 ms, FA 30°. Totally, 252 volumes were acquired and all the motion patterns were recorded. The subjective image quality assessment (IQA) was performed by 2 MRI experts, who scored the overall image quality (scale 1-10, worst-best quality) and the presence of motion artifacts (scale 1-10, image completely corrupted by motion artifacts - image without motion artifacts). Finally, an objective IQA was performed, several focus metrics (GLLV - Gray Level Local Variance, GLVN- Normalized GLV and TENV - Tenengrad Variance)³ were considered to compare images acquired without and with PMC.

RESULTS

Tab.1 summarizes the motion quantification per subject. Exemplary, corrected and uncorrected images with the corresponding motion patterns are shown in the Fig.1. In the Fig.2 an additional example where the images acquired with the PMC are corrupted by motion artifacts is shown. Fig. 3 presents the subjective evaluation for all the images acquired, and Fig.4 the results of the objective IQA.

DISCUSSION

From Tab.1 is evident that, in general, there were not large movements. The subjective IQA (Fig. 3) demonstrated a slightly better quality for the images acquired with PMC. Similar results were obtained with the objective IQA, except for the images acquired with the 3D-MPRAGE sequence, where the values of the prospectively motion corrected images were slightly lower than without motion correction. In this study (one of the largest PMC cohorts until today), subjective and objective IQA indicate that PMC improves the image quality. In this manner, PMC shows a great potential for numerous MRI applications in neuroscience and will be tested even further on patients in future work.

Acknowledgements

This work was supported by the Initial Training Network, HiMR, funded by the FP7 Marie Curie Actions of the European Commission, grant number FP7-PEOPLE-2012-ITN-316716, and by the NIH, grant number 1R01-DA021146.