Yerly Jérôme, Roy Christopher W, Milani Bastien, Eyre Katerina, Raifee Mozedin Javad, Stuber Matthias
Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Vaud, Switzerland.
Center for Biomedical Imaging (CIBM), Lausanne, Vaud, Switzerland.
Magn Reson Med. 2025 Mar;93(3):975-992. doi: 10.1002/mrm.30323. Epub 2024 Oct 9.
Cardiac magnetic resonance is the gold standard for evaluating left-ventricular ejection fraction (LVEF). Standard protocols, however, can be inefficient, facing challenges due to significant operator and patient involvement. Although the free-running framework (FRF) addresses these challenges, the potential of the extensive data it collects remains underutilized. Therefore, we propose to leverage the large amount of data collected by incorporating interbin cardiac motion compensation into FRF (FRF-MC) to improve both image quality and LVEF measurement accuracy, while reducing the sensitivity to user-defined regularization parameters.
FRF-MC consists of several steps: data acquisition, self-gating signal extraction, deformation field estimations, and motion-resolved reconstruction with interbin cardiac motion compensation. FRF-MC was compared with the original 5D-FRF method using LVEF and several image-quality metrics. The cardiac regularization weight ( ) was optimized for both methods by maximizing image quality without compromising LVEF measurement accuracy. Evaluations were performed in numerical simulations and in 9 healthy participants. In vivo images were assessed by blinded expert reviewers and compared with reference standard 2D-cine images.
Both in silico and in vivo results revealed that FRF-MC outperformed FRF in terms of image quality and LVEF accuracy. FRF-MC reduced temporal blurring, preserving detailed anatomy even at higher cardiac regularization weights, and led to more accurate LVEF measurements. Optimized produced accurate LVEF for both methods compared with the 2D-cine reference (FRF-MC: 0.59% [-7.2%, 6.0%], p = 0.47; FRF: 0.86% [-8.5%, 6.7%], p = 0.36), but FRF-MC resulted in superior image quality (FRF-MC: 2.89 ± 0.58, FRF: 2.11 ± 0.47; p < 10).
Incorporating interbin cardiac motion compensation significantly improved image quality, supported higher cardiac regularization weights without compromising LVEF measurement accuracy, and reduced sensitivity to user-defined regularization parameters.
心脏磁共振成像（CMR）是评估左心室射血分数（LVEF）的金标准。然而，标准方案可能效率低下，因为它面临着操作人员和患者参与度高带来的挑战。尽管自由运行框架（FRF）解决了这些挑战，但其收集的大量数据的潜力仍未得到充分利用。因此，我们建议通过将帧间心脏运动补偿纳入FRF（FRF-MC）来利用所收集的大量数据，以提高图像质量和LVEF测量准确性，同时降低对用户定义的正则化参数的敏感性。
FRF-MC包括几个步骤：数据采集、自门控信号提取、变形场估计以及采用帧间心脏运动补偿的运动解析重建。使用LVEF和几个图像质量指标将FRF-MC与原始的5D-FRF方法进行比较。通过在不影响LVEF测量准确性的情况下最大化图像质量，对两种方法的心脏正则化权重（ ）进行了优化。在数值模拟和9名健康参与者中进行了评估。体内图像由不知情的专家评审员进行评估，并与参考标准二维电影图像进行比较。
计算机模拟和体内实验结果均显示，FRF-MC在图像质量和LVEF准确性方面均优于FRF。FRF-MC减少了时间模糊，即使在较高的心脏正则化权重下也能保留详细的解剖结构，并导致更准确的LVEF测量。与二维电影参考相比，优化后的 对两种方法均产生了准确的LVEF（FRF-MC：0.59%[-7.2%，6.0%]，p = 0.47；FRF：0.86%[-8.5%，6.7%]，p = 0.36），但FRF-MC具有更高的图像质量（FRF-MC：2.89±0.58，FRF：2.11±0.47；p < 10）。
纳入帧间心脏运动补偿可显著提高图像质量，支持更高的心脏正则化权重而不影响LVEF测量准确性，并降低对用户定义的正则化参数的敏感性。
