Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease
Deep artifact suppression for spiral real-time phase contrast cardiac magnetic resonance imaging in congenital heart disease
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DOI：
10.1016/j.mri.2021.08.005
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发表时间：
2021-08-24
影响因子：
2.5
通讯作者：
Muthurangu, Vivek
中科院分区：
文献类型：
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作者：
Jaubert, Olivier;Steeden, Jennifer;Muthurangu, Vivek
目的：实时螺旋相位对比MR（PCMR）能够快速评估血流的自由呼吸。目标空间和时间分辨率需要高加速率，这通常导致长的重建时间。在这里，我们提出了一个深的伪影抑制框架，快速，准确的流量quantization.Methods：使用520屏气门控螺旋PCMR主动脉数据集收集的先天性心脏病患者的U-Nets进行训练的深伪影抑制。两个螺旋轨迹（均匀和扰动）和两个损失（平均绝对误差-MAE-和平均结构相似性指数测量-SSIM-）进行了比较，在合成数据的MAE，峰值信噪比（PSNR）和SSIM。在20例患者中前瞻性采集了扰动螺旋PCMR。每搏输出量（SV），峰值平均速度和边缘锐度测量进行了比较，压缩感知（CS）和笛卡尔reference.Results：在合成数据，扰动螺旋始终优于均匀螺旋不同的图像指标。U-Net MAE显示出更好的MAE和PSNR，而U-Net SSIM显示出更高的基于SSIM的指标。在体内，任何实时重建和参考标准笛卡尔数据之间的SV均无显著差异。然而，与U-Net MAE相比，U-Net SSIM具有更好的图像清晰度和更低的峰值速度偏差。重建96帧需要类似的59秒CS和3.9秒的U-Nets.Conclusion：深伪影抑制复杂值的图像使用SSIM为基础的损失，成功地证明了在一个队列的先天性心脏病患者的快速和准确的流量量化。
Purpose: Real-time spiral phase contrast MR (PCMR) enables rapid free-breathing assessment of flow. Target spatial and temporal resolutions require high acceleration rates often leading to long reconstruction times. Here we propose a deep artifact suppression framework for fast and accurate flow quantification.Methods: U-Nets were trained for deep artifact suppression using 520 breath-hold gated spiral PCMR aortic datasets collected in congenital heart disease patients. Two spiral trajectories (uniform and perturbed) and two losses (Mean Absolute Error -MAE- and average structural similarity index measurement -SSIM-) were compared in synthetic data in terms of MAE, peak SNR (PSNR) and SSIM. Perturbed spiral PCMR was prospectively acquired in 20 patients. Stroke Volume (SV), peak mean velocity and edge sharpness measurements were compared to Compressed Sensing (CS) and Cartesian reference.Results: In synthetic data, perturbed spiral consistently outperformed uniform spiral for the different image metrics. U-Net MAE showed better MAE and PSNR while U-Net SSIM showed higher SSIM based metrics. In-vivo, there were no significant differences in SV between any of the real-time reconstructions and the reference standard Cartesian data. However, U-Net SSIM had better image sharpness and lower biases for peak velocity when compared to U-Net MAE. Reconstruction of 96 frames took similar to 59 s for CS and 3.9 s for U-Nets.Conclusion: Deep artifact suppression of complex valued images using an SSIM based loss was successfully demonstrated in a cohort of congenital heart disease patients for fast and accurate flow quantification.