胎儿MRI自动血流规划（OWL）
AutOmatic floW planning for fetaL MRI (OWL)
AI总结：
本文提出OWL流程，利用相继的两个深度学习网络定位胎儿胸部并检测标志点，实现二维相位对比MRI实时自动血流规划，并在前瞻性病例中验证其精度与临床推广价值。
摘要：
研究训练了两个相继的深度学习网络：一个用于定位胎儿胸部，另一个用于在冠状面全子宫平衡稳态自由进动扫描中识别一组标志点；它们分别在167个和71个胎儿数据集上训练，这些数据涵盖不同场强、采集参数和孕周，并被部署于实时环境中。随后，研究对相位对比序列进行修改，使其利用识别出的标志点进行规划。OWL流程在10个数据集中接受回顾性评估，并在7名胎儿受试者（孕周介于36+3至39+3周）中接受前瞻性评估。前瞻性病例还接受了人工规划，以便通过对规划质量评分进行定性比较，并通过比较指数化血流测量值进行定量直接比较。除1名前瞻性参与者外，OWL在所有参与者中均实现了二维相位对比扫描的实时全自动规划。胎儿身体定位的总体Dice评分为0.94±0.05；心脏标志点检测精度在降主动脉为5.77±2.91 mm，脊柱为4.32±2.44 mm，脐静脉为4.94±3.82 mm。对于前瞻性病例，自动扫描的总体规划质量为2.73/4，而人工规划为3.0/4；血流定量评估显示，比较门控自动采集与人工采集获得的指数化血流测量值，平均差异为-1.8%（范围为-14.2%至14.9%）。研究有效实现了针对胎儿脉管系统两条主要血管的二维相位对比MRI实时自动规划。尽管该方法是在0.55T上演示的，但其具有更广泛的意义，而且跨多个场强的训练使其具备泛化能力。因此，OWL代表了将这种成像方式的可及性扩展到专科中心之外的重要一步。
英文摘要：
Two subsequent deep learning networks, one localizing the fetal chest and one identifying a set of landmarks on a coronal whole-uterus balanced steady-state free precession scan, were trained on 167 and 71 fetal datasets across field strengths, acquisition parameters, and gestational ages and implemented in a real-time setup. Next, a phase-contrast sequence was modified to use the identified landmarks for planning. The OWL pipeline was evaluated retrospectively in 10 datasets and prospectively in 7 fetal subjects (gestational ages between 36+3 and 39+3 weeks). The prospective cases were additionally manually planned to enable direct comparison both qualitatively, by scoring the planning quality, and quantitatively, by comparing the indexed flow measurements. OWL enabled real-time fully automatic planning of the 2D phase-contrast scans in all but one of the prospective participants. The fetal body localization achieved an overall Dice score of 0.94+-0.05 and the cardiac landmark detection accuracy was 5.77+-2.91 mm for the descending aorta, 4.32+-2.44 mm for the spine, and 4.94+-3.82 mm for the umbilical vein. For the prospective cases, overall planning quality was 2.73/4 for the automated scans, compared to 3.0/4 for manual planning, and the flow quantitative evaluation showed a mean difference of -1.8% (range -14.2% to 14.9%) by comparing the indexed flow measurements obtained from gated automatic and manual acquisitions. Real-time automated planning of 2D phase-contrast MRI was effectively accomplished for 2 major vessels of the fetal vasculature. While demonstrated here on 0.55T, the achieved method has wider implications, and training across multiple field strengths enables generalization. OWL thereby presents an important step towards extending access to this modality beyond specialised centres.
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