Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
Magn Reson Med. 2010 Sep;64(3):767-76. doi: 10.1002/mrm.22463.
First-pass cardiac perfusion MRI is a natural candidate for compressed sensing acceleration since its representation in the combined temporal Fourier and spatial domain is sparse and the required incoherence can be effectively accomplished by k-t random undersampling. However, the required number of samples in practice (three to five times the number of sparse coefficients) limits the acceleration for compressed sensing alone. Parallel imaging may also be used to accelerate cardiac perfusion MRI, with acceleration factors ultimately limited by noise amplification. In this work, compressed sensing and parallel imaging are combined by merging the k-t SPARSE technique with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging. We also present a new theoretical framework for understanding the combination of k-t SPARSE with SENSE based on distributed compressed sensing theory. This framework, which identifies parallel imaging as a distributed multisensor implementation of compressed sensing, enables an estimate of feasible acceleration for the combined approach. We demonstrate feasibility of 8-fold acceleration in vivo with whole-heart coverage and high spatial and temporal resolution using standard coil arrays. The method is relatively insensitive to respiratory motion artifacts and presents similar temporal fidelity and image quality when compared to Generalized autocalibrating partially parallel acquisitions (GRAPPA) with 2-fold acceleration.
首过心脏灌注 MRI 是压缩感知加速的理想候选者，因为它在时间傅里叶和空间域的表示是稀疏的，并且所需的不相关性可以通过 k-t 随机欠采样有效地实现。然而，实际所需的样本数量（稀疏系数的三到五倍）限制了压缩感知的加速。并行成像也可用于加速心脏灌注 MRI，其加速因子最终受噪声放大的限制。在这项工作中，通过将 k-t SPARSE 技术与灵敏度编码（SENSE）重建合并，将压缩感知和并行成像相结合，可大大提高灌注成像的加速率。我们还提出了一种新的理论框架，用于基于分布式压缩感知理论理解 k-t SPARSE 与 SENSE 的结合。该框架将并行成像识别为压缩感知的分布式多传感器实现，可对组合方法的可行加速进行估计。我们使用标准线圈阵列在体内演示了 8 倍的全心脏覆盖和高时空分辨率的加速的可行性。该方法对呼吸运动伪影相对不敏感，并且与具有 2 倍加速的广义自校准部分并行采集（GRAPPA）相比，具有相似的时间保真度和图像质量。
