Highly accelerated free-breathing real-time myocardial tagging for exercise cardiovascular magnetic resonance.
Highly accelerated free-breathing real-time myocardial tagging for exercise cardiovascular magnetic resonance.
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DOI：
10.1186/s12968-023-00961-w
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发表时间：
2023-10-02
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运动心血管磁共振（Ex-CMR）心肌标记可以量化运动后的心肌变形。然而，目前的心电图（ECG）分段序列是有限的前CMR。我们开发了一种高度加速的平衡稳态自由进动实时标记技术，用于3 T。使用非相干六重随机笛卡尔采样，双重截断外相位编码和深度学习分辨率增强模型实现了12倍的加速。该技术在两项前瞻性研究中进行了测试。在27例临床CMR患者和19例健康受试者的休息研究中，在时空分辨率为2.0 × 2.0 mm 2和29 ms的双腔和短轴视图中收集了一组ECG分段图像用于比较，并收集了两组实时标记图像用于重复性评估。在26名已知或疑似心脏病患者和23名健康受试者的Ex-CMR研究中，采集了运动前后的实时图像。使用短轴整体周向应变（GCS）的措施来量化变形。两名经验丰富的CMR阅片员使用4分制Likert量表评价了两项研究汇总的所有实时数据的图像质量，包括标签质量（1-极好; 2-良好; 3-中等; 4-差）和伪影水平（1-无; 2-极轻微; 3-中等; 4-显著）。统计学评价包括Pearson相关系数（r）、组内相关系数（ICC）和变异系数（CoV）。在其余研究中，90%的病例成功量化了变形。ECG分段和GCS实时测量之间具有良好的相关性（r = 0.71），重复性为良好至极好（ICC = 0.86 [0.71，0.94]），CoV为4.7%。在Ex-CMR研究中，96%的受试者在运动前和84%的受试者在运动后成功量化了变形。短轴和双腔标记线质量在静息时分别为1.6 ± 0.7和1.9 ± 0.8，运动后分别为1.9 ± 0.7和2.5 ± 0.8。短轴和双腔伪影水平在静息时分别为1.2 ± 0.5和1.4 ± 0.7，运动后分别为1.3 ± 0.6和1.5 ± 0.8。我们开发了一种高度加速的实时标记技术，并证明了其潜在的心肌变形的前CMR量化。需要进一步的研究来评估我们的技术的临床实用性。在线版本包含补充材料，可通过10.1186/s12968-023-00961-w获得。
Exercise cardiovascular magnetic resonance (Ex-CMR) myocardial tagging would enable quantification of myocardial deformation after exercise. However, current electrocardiogram (ECG)-segmented sequences are limited for Ex-CMR. We developed a highly accelerated balanced steady-state free-precession real-time tagging technique for 3 T. A 12-fold acceleration was achieved using incoherent sixfold random Cartesian sampling, twofold truncated outer phase encoding, and a deep learning resolution enhancement model. The technique was tested in two prospective studies. In a rest study of 27 patients referred for clinical CMR and 19 healthy subjects, a set of ECG-segmented for comparison and two sets of real-time tagging images for repeatability assessment were collected in 2-chamber and short-axis views with spatiotemporal resolution 2.0 × 2.0 mm2 and 29 ms. In an Ex-CMR study of 26 patients with known or suspected cardiac disease and 23 healthy subjects, real-time images were collected before and after exercise. Deformation was quantified using measures of short-axis global circumferential strain (GCS). Two experienced CMR readers evaluated the image quality of all real-time data pooled from both studies using a 4-point Likert scale for tagline quality (1-excellent; 2-good; 3-moderate; 4-poor) and artifact level (1-none; 2-minimal; 3-moderate; 4-significant). Statistical evaluation included Pearson correlation coefficient (r), intraclass correlation coefficient (ICC), and coefficient of variation (CoV). In the rest study, deformation was successfully quantified in 90% of cases. There was a good correlation (r = 0.71) between ECG-segmented and real-time measures of GCS, and repeatability was good to excellent (ICC = 0.86 [0.71, 0.94]) with a CoV of 4.7%. In the Ex-CMR study, deformation was successfully quantified in 96% of subjects pre-exercise and 84% of subjects post-exercise. Short-axis and 2-chamber tagline quality were 1.6 ± 0.7 and 1.9 ± 0.8 at rest and 1.9 ± 0.7 and 2.5 ± 0.8 after exercise, respectively. Short-axis and 2-chamber artifact level was 1.2 ± 0.5 and 1.4 ± 0.7 at rest and 1.3 ± 0.6 and 1.5 ± 0.8 post-exercise, respectively. We developed a highly accelerated real-time tagging technique and demonstrated its potential for Ex-CMR quantification of myocardial deformation. Further studies are needed to assess the clinical utility of our technique. The online version contains supplementary material available at 10.1186/s12968-023-00961-w.
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