Room: Exhibi Hall | Forum 6
Purpose: To determine the effects of age-related breathing patterns on scan time and image quality of the state-of-the-art 4D MRI method based on prospective sorting in comparison with conventional retrospective sorting.
Methods: Prospectively sorted 4D MRIs were acquired on a motion phantom driven by real respiratory waveforms obtained from 18 pediatric patients (aged 5-24 years). The respiratory signal was analyzed to derive individual respiration rate, motion amplitude, and breathing irregularity scored by the coefficient of variation (CV) of peak-to-peak motion. The amplitude at triggering of each slice acquisition was identified to quantify sorting errors in terms of deviation from phase-wise mean. The correlations of scan time and sorting accuracy with age and the patient-specific respiratory parameters were comparatively evaluated against a counterpart set of retrospectively sorted 4D MRIs acquired with the same respiratory waveforms and scan times.
Results: The scan time (median, 5.9 min) and the sorting accuracy (95th percentile of deviation, <1.5 mm) of the prospectively sorted 4D MRI were suitable for pediatric radiotherapy planning unless breathing was severely irregular (CV>30%). Longer scan time and greater sorting error were correlated with slower respiration rate, larger motion, and irregular breathing, among which the irregularity showed the highest correlation (R=0.83, P<0.001). The age was not a significant covariate because of inter-patient variation of breathing patterns particularly in the older patient group. The prospective sorting yielded less errors than retrospective sorting for all but two patients with severe breathing irregularities and long scan times (>12 min), which indicated that a longer scan improved the retrospective sorting to a greater extent.
Conclusion: The performance of prospective sorting was associated with age-related breathing patterns and superior to retrospective sorting for most pediatric breathing patterns analyzed in this study. Characterizing individual breathing irregularity would benefit optimizing patient-specific imaging parameters and improving 4D MRI quality.