Magnetic resonance in medicine · 2025
Automatic Respiratory and Bulk Patient Motion Corrected 3D Fetal MRI.
СтатьяНазвание и аннотация: Перевод в очереди
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Ferincz Robin, Alamo Leonor, Secinaro Aurelio, Tenisch Estelle, Bustin Aurélien, Piccini Davide, Prša Milan, Yerly Jérôme, Roy Christopher W
Аннотация
PURPOSE: To develop a framework (ACROBATIC) for correcting motion in 3D radial fetal MRI.
METHODS: Data were simulated (N = 200) and acquired in utero (N = 11, gestational age: 32 ± 2 weeks). Motion due to maternal respiration was estimated by extracting a self-gating signal and applying focused navigation. Bulk motion was estimated by splitting the acquisition into sequential bins, reconstructing 3D volumes and applying rigid image registration. These combined motion estimates were used to correct k-space. Self-gating signals were compared to ground truth in simulations and an external sensor in utero. The cumulative position error (CPE) measured the accuracy of motion estimations relative to ground truth in simulations and relative sharpness measured the corresponding impact on image quality for both simulations and in utero data. An expert reviewer performed a blinded ranking of in utero images including uncorrected and corrected data.
RESULTS: Self-gating signals correlated strongly with ground truth for simulations (R = 0.97 ± 0.01) and a external sensor for in utero data (R = 0.75 ± 0.23). CPE decreased significantly using ACROBATIC (uncorrected: 13.33[12.73-14.05], corrected: 2.20[1.80-2.61]). Relative image sharpness increased with ACROBATIC for both simulated (4.51[2.89-5.79]) and in utero data (1.12[0.77-1.44]) consistent with expert ranking where ACROBATIC images were given the best rank in the majority of cases.
CONCLUSION: ACROBATIC enables motion correction in 3D radial fetal MRI. Correction of displacement due to maternal respiration and bulk motion results in improved image quality in simulations and in utero. Comparison to 2D frameworks are now warranted to establish the added diagnostic value of this approach.
METHODS: Data were simulated (N = 200) and acquired in utero (N = 11, gestational age: 32 ± 2 weeks). Motion due to maternal respiration was estimated by extracting a self-gating signal and applying focused navigation. Bulk motion was estimated by splitting the acquisition into sequential bins, reconstructing 3D volumes and applying rigid image registration. These combined motion estimates were used to correct k-space. Self-gating signals were compared to ground truth in simulations and an external sensor in utero. The cumulative position error (CPE) measured the accuracy of motion estimations relative to ground truth in simulations and relative sharpness measured the corresponding impact on image quality for both simulations and in utero data. An expert reviewer performed a blinded ranking of in utero images including uncorrected and corrected data.
RESULTS: Self-gating signals correlated strongly with ground truth for simulations (R = 0.97 ± 0.01) and a external sensor for in utero data (R = 0.75 ± 0.23). CPE decreased significantly using ACROBATIC (uncorrected: 13.33[12.73-14.05], corrected: 2.20[1.80-2.61]). Relative image sharpness increased with ACROBATIC for both simulated (4.51[2.89-5.79]) and in utero data (1.12[0.77-1.44]) consistent with expert ranking where ACROBATIC images were given the best rank in the majority of cases.
CONCLUSION: ACROBATIC enables motion correction in 3D radial fetal MRI. Correction of displacement due to maternal respiration and bulk motion results in improved image quality in simulations and in utero. Comparison to 2D frameworks are now warranted to establish the added diagnostic value of this approach.