Heikal A A, Wachowicz K, Fallone B G
University of Alberta, Department of Physics.
University of Alberta, Department of Oncology.
Med Phys. 2012 Jul;39(7Part2):4623. doi: 10.1118/1.4740103.
Compressed Sensing MRSI (CS-MRSI) offers the ability to accelerate MRSI sequences while suffering minimal artifacts compared to conventional fast MRSI techniques. CS-MRSI exploits the inherent sparsity of MRSI images and incoherent artifacts of pseudo-random sub-Nyquist sampling of k-space combined with non-linear reconstruction to produces MRSI images. CS-MRSI can be used as an acceleration tool to decrease the scan time while maintaining acceptable spatial definition or to enable the acquisition of higher resolution scans while minimizing the associated time penalty. In this work we adopt the compressed sensing technique to accelerate a clinically relevant 2-D point resolved spectroscopy sequence. However, the process of weighing the cost and benefit of applying such a fast imaging technique is complicated due to the unique non-linear nature of the reconstruction process and has largely relied on qualitative assessments. Moreover, pseudo-random sub-Nyquist sampling of k-space can have unwanted effects on the modulation transfer function. In this work we set out to quantify the loss in image quality associated with CS-MRSI. We used simulations of a phantom based method to investigate the MTF behaviour of CS-MRSI with regard to different k-space sampling patterns. As expected, the k-space sampling patterns tested were found to have a direct effect on the MTFs. Moreover, limiting the deviation of the resulting k-space sampling pattern from the prescribed probability distribution function had a positive effect on the MTF overall. Not only was low-resolution response improved, but we also noticed an improvement of ∼ 26% in resolution at 0.1 MTF.
压缩感知磁共振波谱成像（CS-MRSI）能够加速磁共振波谱成像序列，与传统的快速磁共振波谱成像技术相比，其伪影最少。CS-MRSI利用磁共振波谱成像图像的固有稀疏性以及k空间伪随机亚奈奎斯特采样的非相干伪影，并结合非线性重建来生成磁共振波谱成像图像。CS-MRSI可用作加速工具，以减少扫描时间，同时保持可接受的空间分辨率，或者在最小化相关时间代价的同时实现更高分辨率扫描的采集。在这项工作中，我们采用压缩感知技术来加速临床相关的二维点分辨波谱序列。然而，由于重建过程独特的非线性性质，权衡应用这种快速成像技术的成本和效益的过程很复杂，并且很大程度上依赖于定性评估。此外，k空间的伪随机亚奈奎斯特采样可能会对调制传递函数产生不良影响。在这项工作中，我们着手量化与CS-MRSI相关的图像质量损失。我们使用基于体模的模拟方法来研究CS-MRSI在不同k空间采样模式下的调制传递函数行为。正如预期的那样，测试的k空间采样模式对调制传递函数有直接影响。此外，限制所得k空间采样模式与规定概率分布函数的偏差对整体调制传递函数有积极影响。不仅低分辨率响应得到改善，而且我们还注意到在0.1调制传递函数时分辨率提高了约26%。
