Magnetic resonance in medicine · 2025
Real-time fetal brain and placental T2* mapping at 0.55T MRI.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Aviles Verdera Jordina, Neves Silva Sara, Payette Kelly M, Tomi-Tricot Raphael, Hall Megan, Story Lisa, Malik Shaihan J, Hajnal Joseph V, Rutherford Mary A, Hutter Jana
Аннотация
PURPOSE: To provide real-time, organ-specific quantitative information - specifically placental and fetal brain T2 * - to optimize and personalize fetal MRI examinations.
METHODS: A low-latency setup enables real-time processing, including segmentation, T2* fitting, and centile calculation. Two nnU-Nets were trained on 2 989 fetal brains, and 540 placental datasets for automatic segmentation. Normative T2* curves over gestation were derived from 88 healthy cases. Prospective testing included 50 fetal MRI scans: A validation cohort (10 exams with three intra-scan repetitions) and an evaluation cohort (40 participants). Validation was performed with Bland-Altman assessments and Dice coefficients between repetitions, manual/automatic segmentations, and online/offline quantification.
RESULTS: T2* maps and centiles for the fetal brain and placenta were available in under one minute for all cases. The validation cohort showed robust reproducibility, with intra-scan mean T2* differences of 1.04, -3.17, and 5.07 ms for the fetal brain and -3.15, 4.74, and 2.45 ms for the placenta. Mean T2* differences between online and offline processing were 1.63 ms and 0.16 ms for the fetal brain and placenta, respectively. Dice coefficients were 0 . 84 ± 0 . 02 $$ 0.84\pm 0.02 $$ for the placenta and 0 . 96 ± 0 . 01 $$ 0.96\pm 0.01 $$ for the fetal brain.
CONCLUSIONS: Real-time quantitative imaging supports personalized MR exams, optimizing sequence selection and working towards reducing recall rates. The ability to assess T2*, a potential biomarker for pregnancy complications, in real-time opens new clinical possibilities. Future research will apply this pipeline to pregnancies affected by preeclampsia and growth restriction and explore MR-guided fetal interventions.
METHODS: A low-latency setup enables real-time processing, including segmentation, T2* fitting, and centile calculation. Two nnU-Nets were trained on 2 989 fetal brains, and 540 placental datasets for automatic segmentation. Normative T2* curves over gestation were derived from 88 healthy cases. Prospective testing included 50 fetal MRI scans: A validation cohort (10 exams with three intra-scan repetitions) and an evaluation cohort (40 participants). Validation was performed with Bland-Altman assessments and Dice coefficients between repetitions, manual/automatic segmentations, and online/offline quantification.
RESULTS: T2* maps and centiles for the fetal brain and placenta were available in under one minute for all cases. The validation cohort showed robust reproducibility, with intra-scan mean T2* differences of 1.04, -3.17, and 5.07 ms for the fetal brain and -3.15, 4.74, and 2.45 ms for the placenta. Mean T2* differences between online and offline processing were 1.63 ms and 0.16 ms for the fetal brain and placenta, respectively. Dice coefficients were 0 . 84 ± 0 . 02 $$ 0.84\pm 0.02 $$ for the placenta and 0 . 96 ± 0 . 01 $$ 0.96\pm 0.01 $$ for the fetal brain.
CONCLUSIONS: Real-time quantitative imaging supports personalized MR exams, optimizing sequence selection and working towards reducing recall rates. The ability to assess T2*, a potential biomarker for pregnancy complications, in real-time opens new clinical possibilities. Future research will apply this pipeline to pregnancies affected by preeclampsia and growth restriction and explore MR-guided fetal interventions.