School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Magn Reson Med. 2022 Nov;88(5):2198-2207. doi: 10.1002/mrm.29386. Epub 2022 Jul 17.
To obtain high-quality maps of brain tissues from water-unsuppressed magnetic resonance spectroscopic imaging (MRSI) and turbo spin-echo (TSE) data.
mapping can be achieved using mapping from water-unsuppressed MRSI data and mapping from TSE data. However, mapping often suffers from signal dephasing and distortions caused by field inhomogeneity; measurements may be biased due to system imperfections, especially for -weighted image with small number of TEs. In this work, we corrected the field inhomogeneity effect on mapping using a subspace model-based method, incorporating pre-learned spectral basis functions of the water signals. estimation bias was corrected using a TE-adjustment method, which modeled the deviation between measured and reference decays as TE shifts.
In vivo experiments were performed to evaluate the performance of the proposed method. High-quality maps were obtained in the presence of large field inhomogeneity in the prefrontal cortex. Bias in measurements obtained from TSE data was effectively reduced. Based on the and measurements produced by the proposed method, high-quality maps were obtained, along with neurometabolite maps, from MRSI and TSE data that were acquired in about 9 min. The results obtained from acute stroke and glioma patients demonstrated the feasibility of the proposed method in the clinical setting.
High-quality maps can be obtained from water-unsuppressed H-MRSI and TSE data using the proposed method. With further development, this method may lay a foundation for simultaneously imaging oxygenation and neurometabolic alterations of brain disorders.
从未水抑制的磁共振波谱成像（MRSI）和涡轮自旋回波（TSE）数据中获取高质量的脑组织图谱。
可以使用来自未水抑制 MRSI 数据的图谱和来自 TSE 数据的图谱进行映射。然而，图谱通常会受到磁场不均匀性引起的信号去相位和失真的影响；由于系统不完善，尤其是对于 TE 数量较少的 -加权图像，测量可能会存在偏差。在这项工作中，我们使用基于子空间模型的方法校正了图谱上磁场不均匀性的影响，该方法整合了水信号的预学习光谱基函数。使用 TE 调整方法校正了估计偏差，该方法将测量和参考衰减之间的偏差建模为 TE 偏移。
进行了体内实验以评估所提出方法的性能。在前额皮质存在大磁场不均匀性的情况下，获得了高质量的图谱。从 TSE 数据获得的图谱测量中的偏差得到了有效降低。基于所提出方法产生的和图谱测量值，从大约 9 分钟采集的 MRSI 和 TSE 数据中获得了高质量的图谱，以及神经代谢物图谱。来自急性中风和脑肿瘤患者的结果证明了该方法在临床环境中的可行性。
使用所提出的方法可以从未水抑制的 1 H-MRSI 和 TSE 数据中获得高质量的图谱。随着进一步的发展，该方法可能为同时成像脑疾病的氧合和神经代谢改变奠定基础。
