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高加速自由呼吸实时心肌标记用于运动心血管磁共振。

Highly accelerated free-breathing real-time myocardial tagging for exercise cardiovascular magnetic resonance.

机构信息

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.

出版信息

J Cardiovasc Magn Reson. 2023 Oct 2;25(1):56. doi: 10.1186/s12968-023-00961-w.

Abstract

BACKGROUND

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.

METHODS

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).

RESULTS

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.

CONCLUSION

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.

摘要

背景

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。

方法

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)。

结果

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。

结论

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0764/10544487/44dec4dfcc91/12968_2023_961_Fig1_HTML.jpg

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