Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Ave., Boston, MA, 02215, USA.
Case Western Reserve University, Cleveland, OH, USA.
J Cardiovasc Magn Reson. 2023 Oct 2;25(1):56. doi: 10.1186/s12968-023-00961-w.
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 mm 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.
运动心血管磁共振(Ex-CMR)心肌标记技术可用于量化运动后的心肌变形。然而,目前的心电图(ECG)分段序列在 Ex-CMR 中受到限制。
我们开发了一种适用于 3T 的高度加速平衡稳态自由进动实时标记技术。通过非相干六倍随机笛卡尔采样、两倍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。在一项 27 例因临床需要行 CMR 检查的患者和 19 例健康受试者的静息研究中,在 2 腔和短轴视图中采集了一套用于比较的 ECG 分段和两套用于重复性评估的实时标记图像,空间和时间分辨率为 2.0×2.0mm 和 29ms。在一项 26 例已知或疑似心脏病患者和 23 例健康受试者的 Ex-CMR 研究中,在运动前后采集实时图像。使用短轴整体周向应变(GCS)的测量值来量化变形。两位有经验的 CMR 读者使用 4 分李克特量表(1-优秀;2-良好;3-中等;4-差)和伪影水平(1-无;2-轻微;3-中等;4-显著)对来自两项研究的所有实时数据的图像质量进行评估。统计评估包括 Pearson 相关系数(r)、组内相关系数(ICC)和变异系数(CoV)。
在静息研究中,90%的病例成功量化了变形。ECG 分段和实时 GCS 测量值之间存在良好的相关性(r=0.71),重复性良好至优秀(ICC=0.86[0.71,0.94]),CoV 为 4.7%。在 Ex-CMR 研究中,运动前 96%的受试者和运动后 84%的受试者成功量化了变形。静息时短轴和 2 腔标记线质量分别为 1.6±0.7 和 1.9±0.8,运动后分别为 1.9±0.7 和 2.5±0.8。静息时短轴和 2 腔伪影水平分别为 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,并证明了其在 Ex-CMR 量化心肌变形中的潜力。需要进一步的研究来评估我们技术的临床实用性。