发表机构
Stanford University; Siemens Medical Solutions USA, Inc.（斯坦福大学; 西门子医疗美国公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对MRF运动校正时间分辨率低的问题，提出集成紧凑螺旋导航器与定量侦察的框架，实现0.5秒亚秒级运动估计，显著降低重建误差并提升图像质量。
AI 中文摘要
磁共振指纹成像（MRF）中的运动校正有助于保持定量图谱的准确性；然而，现有方法仅每7-8秒提供一次运动更新。我们提出了一种导航框架，将紧凑的k空间导航器集成到整个MRF采集过程中，以极小的序列开销实现亚秒级运动估计。在3D螺旋投影MRF序列中，每隔0.5秒插入三个正交螺旋导航器，通过将导航信号与定量侦察（Q-Scout）数据（即具有匹配对比度演变的无运动低分辨率k空间）进行比较来实现运动估计。Q-Scout通过在预备期内的快速校准获得，不增加额外扫描时间。运动估计被表述为判别子空间中的字典匹配，并进行优化细化。该方法在仿真和体内实验中针对3T下1mm各向同性脑部3D MRF进行了评估。在35次有运动伪影且有无运动参考的采集中，所提出的运动校正使MRF重建的归一化均方根误差（NRMSE）降低了7.1%，结构相似性指数（SSIM）提高了0.085。运动估计与8秒时间分辨率的基于图像导航的结果一致（平均绝对差为0.15毫米和0.23度），而所提出的方法提供了更高的时间分辨率和改进的运动校正。所提出的框架能够在0.5秒时间分辨率下实现MRF中的稳健运动导航，且序列开销极小。通过使用对比度一致的建模和高效推理，它提高了在快速、不可预测运动下定量MRI的可靠性。
英文摘要
Motion correction in magnetic resonance fingerprinting (MRF) helps preserve the accuracy of quantitative maps; however, existing approaches provide motion updates only every 7-8 seconds. We propose a navigation framework that integrates compact k-space navigators throughout the MRF acquisition, enabling sub-second motion estimation at minimal sequence overhead. A 3D spiral-projection MRF sequence was augmented with three orthogonal spiral navigators inserted every 0.5 seconds, enabling motion estimation by comparing navigator signals with quantitative scout (Q-Scout) data, i.e., motion-free low-resolution k-space with matching contrast evolution. The Q-Scout is obtained via a rapid calibration during the dummy preparation period, incurring no additional scan time. Motion estimation is formulated as dictionary matching in a discriminant subspace with optimization refinement. The method was evaluated in simulation and in vivo for 1 mm isotropic brain 3D MRF at 3 T. Across 35 motion-corrupted acquisitions with motion-free references available, the proposed motion correction reduced MRF reconstruction normalized root-mean-square error (NRMSE) by 7.1% and increased the structural similarity index measure (SSIM) by 0.085. Motion estimates aligned with 8 second temporal-rate image-based navigation (mean absolute difference of 0.15 mm and 0.23 degrees), while the proposed method provided higher temporal resolution and improved motion correction. The proposed framework enables robust motion navigation in MRF at 0.5 second temporal resolution with minimal sequence overhead. By using contrast-consistent modeling and efficient inference, it improves the reliability of quantitative MRI under rapid, unpredictable motion.
