一个用于MRS数据处理和分析的图形化流水线平台:MRSpecLAB。

Frontiers in neuroimaging Pub Date : 2025-07-18 eCollection Date: 2025-01-01 DOI:10.3389/fnimg.2025.1610658
Ying Xiao, Antonia Kaiser, Matthias Kockisch, Alex Back, Robin Carlet, Xinyu Liu, Zhiwei Huang, André Döring, Mark Widmaier, Lijing Xin
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引用次数: 0

摘要

磁共振波谱(MRS)和磁共振波谱成像(MRSI)是一种非侵入性技术,用于定量组织中的生化化合物,如胆碱、肌酸、谷氨酸、谷氨酰胺、γ-氨基丁酸、n-乙酰天冬氨酸等。然而,MRS和MRSI数据的可靠量化是具有挑战性的,因为涉及复杂的处理步骤,通常需要先进的专业知识。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,对于新用户来说,呈现出陡峭的学习曲线。掌握这些工具通常需要很长的培训时间,这对于技术背景有限的用户来说可能是一个障碍。为了应对这些挑战,并创建一个工具,为使用MRS/MRSI具有广泛背景的研究人员提供服务,我们开发了mrspeclab -一个开放获取,用户友好的软件平台,用于MRS和MRSI数据分析。MRSpecLAB专为易于安装而设计,并具有直观的图形管道编辑器,支持预定义和可定制的工作流。它还可以作为提供标准化管道的平台,同时允许用户集成内部功能以获得额外的灵活性。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应用程序的贡献、协作和数据工作流和处理方法的共享,支持再现性实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A graphical pipeline platform for MRS data processing and analysis: MRSpecLAB.

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, γ-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.

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