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REPAIRit:在心律失常期间改善 3D 导航门控晚期钆增强成像的心肌伪影。

REPAIRit: Improving Myocardial Nulling and Ghosting Artifacts of 3D Navigator-Gated Late Gadolinium Enhancement Imaging During Arrhythmia.

机构信息

Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA.

Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.

出版信息

J Magn Reson Imaging. 2019 Mar;49(3):688-699. doi: 10.1002/jmri.26284. Epub 2018 Sep 25.

Abstract

BACKGROUND

Cardiac 3D navigator-gated late gadolinium enhancement (LGE) imaging is important for assessment of left atrial fibrosis, but the image quality is often degraded due to arrhythmia.

PURPOSE

To investigate a novel 3D LGE sequence with improved myocardial nulling and reduced ghosting artifacts during arrhythmia.

STUDY TYPE

Prospective.

POPULATION

Arrhythmia patients (n = 14).

SEQUENCE

The proposed technique, REPAIRit (Regrowth Equalization Pulse for Arrhythmias in Inversion Recovery with automatic inversion time calculation), inserts a saturation pulse with a dynamic flip angle into the 3D LGE sequence to minimize arrhythmia-induced signal fluctuations. Using ShMOLLI (shortened modified Look-Locker imaging) to estimate myocardial T , REPAIRit automatically calculates the optimal inversion time (TI) based on Bloch equations.

ASSESSMENT

REPAIRit LGE and the standard LGE were compared with simulations, phantom imaging, and patient studies. Patient images were assessed quantitatively, based on ghost-to-noise ratio (GNR), blood signal-to-noise ratio (SNRb), myocardial signal-to-noise ratio (SNRm), and blood-to-myocardium contrast-to-noise ratio (CNR), and qualitatively on a 4-point scale. Patients were subgrouped based on the presence of arrhythmia to assess the image quality difference.

STATISTICAL TESTS

The two LGE sequences were compared by Student's t-test and Wilcoxon signed-rank test. The two patient-subgroups were compared using Welch's t-test and Wilcoxon rank-sum test.

RESULTS

In 14 analyzed patients, REPAIRit LGE significantly lowered GNR (1.25 ± 0.41 vs. 1.42 ± 0.42, P = 0.04), reduced SNRm (1.90 ± 0.60 vs. 3.16 ± 1.66, P = 0.01), improved ghosting artifact scores (2.5 ± 0.6 vs. 2.2 ± 0.9, P = 0.03), myocardial nulling scores (2.7 ± 0.5 vs. 2.3 ± 0.7, P = 0.02), and atrial quality scores (2.8 ± 0.3 vs. 2.4 ± 0.8, P = 0.03) compared with the standard LGE. Comparing patients with arrhythmia (n = 6) to those without (n = 8) during the scan, the former had lower left ventricular (LV) myocardial T s (430 ± 26 msec vs. 469 ± 39 msec, P = 0.06) but similar blood T s (318 ± 55 msec vs. 316 ± 27 msec, P = 0.96), and significantly lower blood SNR (5.2 ± 1.8 vs. 9.2 ± 3.0, P = 0.01) and significantly worse image quality (P = 0.01 for REPAIRit and P = 0.03 for standard).

DATA CONCLUSION

REPAIRit improves myocardial nulling and reduces ghosting artifacts of 3D LGE under arrhythmia.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:688-699.

摘要

背景

心脏 3D 导航门控晚期钆增强(LGE)成像对于评估左心房纤维化非常重要,但由于心律失常,图像质量通常会下降。

目的

研究一种新的 3D LGE 序列,该序列具有改善的心肌消除功能,并减少心律失常时的伪影。

研究类型

前瞻性。

人群

心律失常患者(n=14)。

序列

所提出的技术,REPAIRit(使用自动反转时间计算的反转恢复中的再生长均衡脉冲),在 3D LGE 序列中插入具有动态翻转角的饱和脉冲,以最小化心律失常引起的信号波动。使用 ShMOLLI(缩短的改良 Look-Locker 成像)估计心肌 T ,REPAIRit 根据 Bloch 方程自动计算最佳反转时间(TI)。

评估

REPAIRit LGE 与标准 LGE 进行了比较,包括模拟、体模成像和患者研究。根据鬼影噪声比(GNR)、血液信号噪声比(SNRb)、心肌信号噪声比(SNRm)和血液与心肌对比噪声比(CNR)对患者图像进行定量评估,并使用 4 分制进行定性评估。根据心律失常的存在将患者分组,以评估图像质量差异。

统计检验

使用学生 t 检验和 Wilcoxon 符号秩检验比较两种 LGE 序列。使用 Welch t 检验和 Wilcoxon 秩和检验比较两个患者亚组。

结果

在 14 名分析患者中,REPAIRit LGE 显著降低了 GNR(1.25±0.41 对 1.42±0.42,P=0.04),降低了 SNR m(1.90±0.60 对 3.16±1.66,P=0.01),改善了鬼影伪影评分(2.5±0.6 对 2.2±0.9,P=0.03)、心肌消除评分(2.7±0.5 对 2.3±0.7,P=0.02)和心房质量评分(2.8±0.3 对 2.4±0.8,P=0.03)与标准 LGE 相比。与扫描时无心律失常的患者(n=8)相比,有心律失常的患者(n=6)的左心室(LV)心肌 T s 更低(430±26 msec 对 469±39 msec,P=0.06),但血液 T s 相似(318±55 msec 对 316±27 msec,P=0.96),血液 SNR 明显更低(5.2±1.8 对 9.2±3.0,P=0.01),图像质量明显更差(REPAIRit 为 P=0.01,标准为 P=0.03)。

数据结论

REPAIRit 在心律失常下改善了 3D LGE 的心肌消除和减少了鬼影伪影。

证据水平

2 技术功效:第 1 阶段 J. Magn. Reson. Imaging 2019;49:688-699.

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