Abstract

Head movements are a major source of MRI artefacts. Prospective motion correction techniques significantly improve data quality, but strong motion artefacts may remain in the data. We introduce a framework to suspend data acquisition during periods of head motion over a predefined threshold. Data was acquired with prospective motion correction and an external optical tracking system. A predictor of motion impact was introduced that accounts for the amplitude of the signal acquired at the time of the motion. From this predictor, a threshold was defined to trigger the suspension of data acquisition during periods of motion. The framework was tested on 5 subjects, 2 motion behaviors, and 2 head coils (20 and 64 channels). The best improvements in data quality were obtained for a threshold value of 0, equivalent to suspending the acquisition based on head speed alone, at the cost of a long prolongation of scan time. For threshold values ∼3.5e-4 , image quality was largely preserved, and prolongation of scan time was minimal. Artefacts occasionally remained with the 64-channel head coil for all threshold values, seemingly due to head movement in the sharp sensitivity profile of this coil. The proposed suspension strategy is more efficient than relying on head speed alone. The threshold for suspension of data acquisition governs the tradeoff between image degradation due to motion and prolonged scan time, and can be tuned by the user according to the desired image quality and participant's tolerability.

Highlights

  • Data was acquired with prospective motion correction and an external optical tracking system

  • The best improvements in data quality were obtained for a threshold value of 0, equivalent to suspending the acquisition based on head speed alone, at the cost of a long prolongation of scan time

  • The threshold for suspension of data acquisition governs the tradeoff between image degradation due to motion and prolonged scan time, and can be tuned by the user according to the desired image quality and participant’s tolerability

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Summary

Methods

Data was acquired with prospective motion correction and an external optical tracking system. Motion correction can be implemented using prospective or retrospective methods and using passive or active markers of head position.[5] Prospective motion correction (PMC) techniques act in real time during image acquisition by adjusting the MRI scanner to account for patient movements.[6] With PMC methods, the acquired MRI data is already corrected for motion effects, avoiding the need for dedicated processing steps.[7,8] In this study, we use the PMC method introduced by Zaitsev et al.,[6] based on external optical measures of brain motion using the tracking system introduced by Maclaren et al.[9] (KinetiCor, HI, Honolulu). A functional MRI study using this system has reported improvements in SNR by 30% to 40% and an increase in the numbers of significantly activated voxels by 70% to 330%.4 Improvements in the precision of relaxometry measures in the range of 11% to 24% have been reported using this PMC technique.[10]

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