Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK.
BMC Psychiatry. 2024 Apr 25;24(1):320. doi: 10.1186/s12888-024-05646-x.
H-MRS is increasingly used in basic and clinical research to explain brain function and alterations respectively. In psychosis research it is now one of the main tools to investigate imbalances in the glutamatergic system. Interestingly, however, the findings are extremely variable even within patients of similar disease states. One reason may be the variability in analysis strategies, despite suggestions for standardization. Therefore, our study aimed to investigate the extent to which the basis set configuration- which metabolites are included in the basis set used for analysis- would affect the spectral fit and estimated glutamate (Glu) concentrations in the anterior cingulate cortex (ACC), and whether any changes in levels of glutamate would be associated with psychotic-like experiences and autistic traits.
To ensure comparability, we utilized five different exemplar basis sets, used in research, and two different analysis tools, r-based spant applying the ABfit method and Osprey using the LCModel.
Our findings revealed that the types of metabolites included in the basis set significantly affected the glutamate concentration. We observed that three basis sets led to more consistent results across different concentration types (i.e., absolute Glu in mol/kg, Glx (glutamate + glutamine), Glu/tCr), spectral fit and quality measurements. Interestingly, all three basis sets included phosphocreatine. Importantly, our findings also revealed that glutamate levels were differently associated with both schizotypal and autistic traits depending on basis set configuration and analysis tool, with the same three basis sets showing more consistent results.
Our study highlights that scientific results may be significantly altered depending on the choices of metabolites included in the basis set, and with that emphasizes the importance of carefully selecting the configuration of the basis set to ensure accurate and consistent results, when using MR spectroscopy. Overall, our study points out the need for standardized analysis pipelines and reporting.
H-MRS 越来越多地被用于基础和临床研究，分别用于解释大脑功能和变化。在精神病学研究中，它现在是研究谷氨酸能系统失衡的主要工具之一。然而，有趣的是，即使在疾病状态相似的患者中，研究结果也非常多变。原因之一可能是分析策略的可变性，尽管有标准化的建议。因此，我们的研究旨在调查基础集配置（用于分析的代谢物包括哪些）在多大程度上会影响前扣带回皮层（ACC）的光谱拟合和估计谷氨酸（Glu）浓度，以及谷氨酸水平的任何变化是否与类精神病体验和自闭症特征有关。
为了确保可比性，我们使用了五种不同的范例基础集，研究中使用了两种不同的分析工具，基于 r 的 spant 使用 ABfit 方法和 Osprey 使用 LCModel。
我们的研究结果表明，基础集中包含的代谢物类型会显著影响谷氨酸浓度。我们发现，有三种基础集在不同浓度类型（即 mol/kg 中的绝对 Glu、Glu（谷氨酸+谷氨酰胺）、Glu/tCr）、光谱拟合和质量测量方面产生了更一致的结果。有趣的是，所有三种基础集都包含磷酸肌酸。重要的是，我们的研究结果还表明，谷氨酸水平与精神分裂型和自闭症特征的相关性取决于基础集配置和分析工具，同样的三种基础集显示出更一致的结果。
我们的研究强调，科学结果可能会因基础集中包含的代谢物选择而发生重大变化，并强调了在使用磁共振波谱时，仔细选择基础集配置以确保准确和一致结果的重要性。总的来说，我们的研究指出了需要标准化的分析流程和报告。
