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research article

A graphical pipeline platform for MRS data processing and analysis: MRSpecLAB

Xiao, Ying  
•
Kaiser, Antonia  
•
Kockisch, Matthias  
Show more
2025
Frontiers in Neuroimaging

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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Type
research article
DOI
10.3389/fnimg.2025.1610658
Scopus ID

2-s2.0-105012369887

PubMed ID

40757147

Author(s)
Xiao, Ying  

École Polytechnique Fédérale de Lausanne

Kaiser, Antonia  

École Polytechnique Fédérale de Lausanne

Kockisch, Matthias  

École Polytechnique Fédérale de Lausanne

Back, Alex

The Royal Institute of Technology (KTH)

Carlet, Robin  

École Polytechnique Fédérale de Lausanne

Liu, Xinyu  

École Polytechnique Fédérale de Lausanne

Huang, Zhiwei  

École Polytechnique Fédérale de Lausanne

Döring, André  

École Polytechnique Fédérale de Lausanne

Widmaier, Mark  

École Polytechnique Fédérale de Lausanne

Xin, Lijing  

École Polytechnique Fédérale de Lausanne

Date Issued

2025

Published in
Frontiers in Neuroimaging
Volume

4

Article Number

1610658

Subjects

1H

•

data processing

•

fMRS

•

MRS/MRSI

•

software tool

•

spectroscopy

•

visualization

•

X-nuclei

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LIFMET  
CIBM-MRI  
CREATE-LAB  
FunderFunding(s)Grant NumberGrant URL

Swiss National Science Foundation

213769,320030_189064

Available on Infoscience
August 20, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/253227
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