Xiao Ying, Kaiser Antonia, Kockisch Matthias, Back Alex, Carlet Robin, Liu Xinyu, Huang Zhiwei, Döring André, Widmaier Mark, Xin Lijing
CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Front Neuroimaging. 2025 Jul 18;4:1610658. doi: 10.3389/fnimg.2025.1610658. eCollection 2025.
Magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI), are non-invasive techniques used to quantify biochemical compounds in tissue, such as choline, creatine, glutamate, glutamine, -aminobutyric acid, N-acetylaspartate, etc. However, reliable quantification of MRS and MRSI data is challenging due to the complex processing steps involved, often requiring advanced expertise. Existing data processing software solutions often demand MRS expertise or coding knowledge, presenting a steep learning curve for novel users. Mastering these tools typically requires a long training time, which can be a barrier for users with limited technical backgrounds. To address these challenges and create a tool that serves researchers using MRS/MRSI with a broad range of backgrounds, we developed MRSpecLAB-an open-access, user-friendly software platform for MRS and MRSI data analysis. MRSpecLAB is designed for easy installation and features an intuitive graphical pipeline editor that supports both predefined and customizable workflows. It also serves as a platform offering standardized pipelines while allowing users to integrate in-house functions for additional flexibility. Importantly, MRSpecLAB is envisioned as an open platform beyond the MRS community, bridging the gap between technical experts and practitioners. It facilitates contributions, collaboration, and the sharing of data workflows and processing methodologies for diverse MRS/MRSI applications, supporting reproducibility practices.
磁共振波谱(MRS)和磁共振波谱成像(MRSI)是用于定量组织中生化化合物的非侵入性技术,如胆碱、肌酸、谷氨酸、谷氨酰胺、γ-氨基丁酸、N-乙酰天门冬氨酸等。然而,由于涉及复杂的处理步骤,MRS和MRSI数据的可靠定量具有挑战性,通常需要专业知识。现有的数据处理软件解决方案通常需要MRS专业知识或编码知识,这对新用户来说学习曲线较陡。掌握这些工具通常需要很长的训练时间,这可能成为技术背景有限的用户的障碍。为应对这些挑战并创建一个能为具有广泛背景的使用MRS/MRSI的研究人员服务的工具,我们开发了MRSpecLAB——一个用于MRS和MRSI数据分析的开放获取、用户友好的软件平台。MRSpecLAB设计易于安装,具有直观的图形化流程编辑器,支持预定义和可定制的工作流程。它还作为一个提供标准化流程的平台,同时允许用户集成内部功能以增加灵活性。重要的是,MRSpecLAB被设想为一个超越MRS社区的开放平台,弥合技术专家和从业者之间的差距。它促进了各种MRS/MRSI应用的数据工作流程和处理方法的贡献、协作与共享,支持可重复性实践。