Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands.
Technical Medicine, University of Twente, Enchede, The Netherlands.
Brain Behav. 2020 Dec;10(12):e01852. doi: 10.1002/brb3.1852. Epub 2020 Nov 20.
Magnetic resonance spectroscopic imaging (MRSI) has the potential to add a layer of understanding of the neurobiological mechanisms underlying brain diseases, disease progression, and treatment efficacy. Limitations related to metabolite fitting of low signal-to-noise ratios data, signal variations due to partial-volume effects, acquisition and extracranial lipid artifacts, along with clinically relevant aspects such as scan time constraints, are among the challenges associated with in vivo MRSI.
The aim of this work was to address some of these factors and to develop an acquisition, reconstruction, and postprocessing pipeline to derive lipid-suppressed metabolite values of central brain structures based on free-induction decay measurements made using a 7 T MR scanner. Anatomical images were used to perform high-resolution (1 mm ) partial-volume correction to account for gray matter, white matter (WM), and cerebral-spinal fluid signal contributions. Implementation of automatic quality control thresholds and normalization of metabolic maps from 23 subjects to the Montreal Neurological Institute (MNI) standard atlas facilitated the creation of high-resolution average metabolite maps of several clinically relevant metabolites in central brain regions, while accounting for macromolecular distributions. Partial-volume correction improved the delineation of deep brain nuclei. We report average metabolite values including glutamate + glutamine (Glx), glycerophosphocholine, choline and phosphocholine (tCho), (phospo)creatine, myo-inositol and glycine (mI-Gly), glutathione, N-acetyl-aspartyl glutamate(and glutamine), and N-acetyl-aspartate in the basal ganglia, central WM (thalamic radiation, corpus callosum) as well as insular cortex and intracalcarine sulcus.
MNI-registered average metabolite maps facilitate group-based analysis, thus offering the possibility to mitigate uncertainty in variable MRSI data.
磁共振波谱成像（MRSI）有可能为理解脑疾病的神经生物学机制、疾病进展和治疗效果增加一个层面的认识。与低信噪比数据的代谢物拟合、部分容积效应引起的信号变化、采集和颅外脂质伪影相关的限制，以及与扫描时间限制等临床相关方面有关，这些都是与体内 MRSI 相关的挑战。
本工作旨在解决其中的一些因素，并开发一种采集、重建和后处理管道，以根据 7TMR 扫描仪上进行的自由感应衰减测量，得出中央脑结构的脂质抑制代谢物值。利用解剖图像对高分辨率（1mm）部分容积进行校正，以考虑灰质、白质（WM）和脑脊液信号的贡献。实施自动质量控制阈值和将 23 个受试者的代谢图归一化为蒙特利尔神经学研究所（MNI）标准图谱，有助于创建中央脑区几个临床相关代谢物的高分辨率平均代谢图，同时考虑大分子分布。部分容积校正改善了深部脑核的描绘。我们报告了平均代谢物值，包括谷氨酸+谷氨酰胺（Glx）、甘油磷酸胆碱、胆碱和磷酸胆碱（tCho）、（磷酸）肌酸、肌醇和甘氨酸（mI-Gly）、谷胱甘肽、乙酰天门冬氨酸谷氨酸（和谷氨酰胺）以及乙酰天门冬氨酸在基底神经节、中央 WM（丘脑辐射、胼胝体）以及脑岛皮层和内纵束中的含量。
MNI 注册的平均代谢物图谱有助于基于组的分析，从而有可能减轻可变 MRSI 数据的不确定性。
