MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis

Mass spectrometry imaging (MSI) combines spatial and spectral data to reveal detailed molecular compositions within biological samples. Despite their immense potential, MSI workflows are hindered by the complexity and high dimensionality of the data, making their analysis computationally intensive and often requiring expertise in coding. Existing tools frequently lack the integration needed for seamless, scalable, and end-to-end workflows, forcing researchers to rely on local solutions or multiple platforms, which hinders efficiency and accessibility. We introduce MassVision, a comprehensive software platform for MSI analysis. Built on the 3D Slicer ecosystem, MassVision integrates MSI-specific functionalities while addressing general user requirements for accessibility and usability. Its intuitive interface lowers barriers for researchers with varying levels of computational expertise, while its scalability supports high-throughput studies and multislide data sets. Key functionalities include visualization, segmentation, colocalization, data set curation, data set merging, spectral and spatial preprocessing, statistical analysis, AI model training, and AI deployment on full MSI data. We detail the workflow and functionalities of MassVision and demonstrate its effectiveness through different experimental use cases such as exploratory data analysis, ion identification, and tissue-type classification on in-house and publicly available data from different MSI modalities. These use cases underscore MassVision's ability to seamlessly integrate MSI data handling steps into a single platform and highlight its potential to reveal new insights and structures when examining biological samples. By combining cutting-edge functionality with user-centric design, MassVision addresses longstanding challenges in MSI data analysis and provides a robust tool for advancing the user's ability to achieve biologically meaningful insights from MSI data. MassVision is freely available via 3D Slicer (documentation: https://SlicerMassVision.readthedocs.io/). The in-house MSI data have been made publicly available in MetaboLights with the identifier MTBLS12868.

Authors

Institutions

Publication Details

Journal
Analytical Chemistry
Published
2025-09-18
DOI
https://doi.org/10.1021/acs.analchem.5c04018
Citations
1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis

Amoon Jamzad, Parvin Mousavi, David Hurlbut, Christopher J.B. Nicol et al.
1 citations
Analytical Chemistry
Metabolomics and Mass Spectrometry Studies
0.81
article

MassVision: An Open-Source End-to-End Platform for AI-Driven Mass Spectrometry Imaging Analysis

Amoon Jamzad, Parvin Mousavi, David Hurlbut, Christopher J.B. Nicol, Ayesha Syeda, Gábor Fichtinger, Martin Kaufmann, Sonal Varma, Kevin Ren, John F. Rudan, Jade Warren, Natasha Iaboni
article en
1 citations

Abstract

Mass spectrometry imaging (MSI) combines spatial and spectral data to reveal detailed molecular compositions within biological samples. Despite their immense potential, MSI workflows are hindered by the complexity and high dimensionality of the data, making their analysis computationally intensive and often requiring expertise in coding. Existing tools frequently lack the integration needed for seamless, scalable, and end-to-end workflows, forcing researchers to rely on local solutions or multiple platforms, which hinders efficiency and accessibility. We introduce MassVision, a comprehensive software platform for MSI analysis. Built on the 3D Slicer ecosystem, MassVision integrates MSI-specific functionalities while addressing general user requirements for accessibility and usability. Its intuitive interface lowers barriers for researchers with varying levels of computational expertise, while its scalability supports high-throughput studies and multislide data sets. Key functionalities include visualization, segmentation, colocalization, data set curation, data set merging, spectral and spatial preprocessing, statistical analysis, AI model training, and AI deployment on full MSI data. We detail the workflow and functionalities of MassVision and demonstrate its effectiveness through different experimental use cases such as exploratory data analysis, ion identification, and tissue-type classification on in-house and publicly available data from different MSI modalities. These use cases underscore MassVision's ability to seamlessly integrate MSI data handling steps into a single platform and highlight its potential to reveal new insights and structures when examining biological samples. By combining cutting-edge functionality with user-centric design, MassVision addresses longstanding challenges in MSI data analysis and provides a robust tool for advancing the user's ability to achieve biologically meaningful insights from MSI data. MassVision is freely available via 3D Slicer (documentation: https://SlicerMassVision.readthedocs.io/). The in-house MSI data have been made publicly available in MetaboLights with the identifier MTBLS12868.

Analytical ChemistryVol. 97(39)
Queen's University (CA), Sinclair Pharma (GB), Cancer Genetics (United States) (US)
Openalex Percentile: Top 23%
Metabolomics and Mass Spectrometry Studies
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.