Hamilton Jesse I, Cruz Gastao, Truesdell William, Agarwal Prachi, Rashid Imran, Seiberlich Nicole
Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
NMR Biomed. 2025 Sep;38(9):e70114. doi: 10.1002/nbm.70114.
The aim of this study is to enable high temporal resolution functional cardiac imaging without breathholds or electrocardiogram (ECG) gating. Real-time MRI is essential for assessing heart function in patients with limited breathhold capacity or arrhythmias that preclude breathheld ECG-gated cine scans. The Time-Dependent Deep Image Prior (Time-DIP) method is a promising reconstruction for dynamic MRI, combining a nonlinear manifold with zero-shot deep learning. However, while Time-DIP has been demonstrated for breathheld cine imaging, it employs a helical manifold that assumes quasi-periodic motion and thus may not be suitable for free-breathing real-time scans, particularly in arrhythmia patients. This study proposes a Multifrequency Time-DIP technique to extend this framework to free-breathing real-time cardiac imaging. First, a "multifrequency manifold" is introduced that parameterizes time using multiple sinusoids spanning various frequencies, enabling dynamic imaging without assuming motion periodicity. Second, joint estimation of coil sensitivities using zero-shot deep learning is used to improve the reconstruction of multichannel data. Simulations and scans of healthy subjects and patients, including those with arrhythmias, were performed using a 2D free-breathing ungated golden angle spiral bSSFP sequence. Image quality and left ventricular (LV) functional measurements were compared to real-time scans reconstructed with compressed sensing and the original Time-DIP implementation, as well as conventional breathheld ECG-gated cine scans. Multifrequency Time-DIP outperformed other real-time techniques in simulations of various motion scenarios. In vivo scans using Multifrequency Time-DIP exhibited reduced aliasing artifacts, achieving temporal resolutions as high as a single TR (4.2 ms/frame), with no significant differences in LV functional measurements compared to conventional scans. While conventional scans had better edge sharpness and image contrast scores, Multifrequency Time-DIP exhibited overall higher image quality metrics among real-time scans. In conclusion, a generalized Time-DIP reconstruction was shown to enable high temporal resolution free-breathing real-time cardiac imaging in healthy subjects and patients, including those with arrhythmias.
本研究的目的是实现无需屏气或心电图（ECG）门控的高时间分辨率心脏功能成像。实时磁共振成像（MRI）对于评估屏气能力有限或存在心律失常而无法进行屏气ECG门控电影扫描的患者的心脏功能至关重要。时间相关深度图像先验（Time-DIP）方法是一种很有前景的动态MRI重建方法，它将非线性流形与零样本深度学习相结合。然而，虽然Time-DIP已被证明可用于屏气电影成像，但它采用了一种假设准周期性运动的螺旋流形，因此可能不适用于自由呼吸实时扫描，特别是在心律失常患者中。本研究提出了一种多频Time-DIP技术，将该框架扩展到自由呼吸实时心脏成像。首先，引入了一个“多频流形”，它使用跨越不同频率的多个正弦波对时间进行参数化，从而在不假设运动周期性的情况下实现动态成像。其次，使用零样本深度学习对线圈灵敏度进行联合估计，以改善多通道数据的重建。使用二维自由呼吸非门控黄金角螺旋平衡稳态自由进动（bSSFP）序列对健康受试者和患者（包括心律失常患者）进行了模拟和扫描。将图像质量和左心室（LV）功能测量结果与使用压缩感知重建的实时扫描、原始Time-DIP实现以及传统屏气ECG门控电影扫描进行了比较。在各种运动场景的模拟中，多频Time-DIP优于其他实时技术。使用多频Time-DIP进行的体内扫描显示混叠伪影减少，实现了高达单个重复时间（TR）（4.2毫秒/帧）的时间分辨率，与传统扫描相比，LV功能测量无显著差异。虽然传统扫描具有更好的边缘清晰度和图像对比度评分，但在实时扫描中，多频Time-DIP总体上具有更高的图像质量指标。总之，一种广义的Time-DIP重建方法被证明能够在健康受试者和患者（包括心律失常患者）中实现高时间分辨率的自由呼吸实时心脏成像。
