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

Area of Science:

• Biomedical imaging
• Computational biology
• Data science

Background:

• Mass spectrometry imaging (MSI) generates rich spatial and spectral data for molecular analysis.
• MSI data analysis is computationally intensive, requiring coding expertise and often fragmented workflows.
• Current tools lack integration, hindering efficiency and accessibility for researchers.

Purpose of the Study:

• To introduce MassVision, a comprehensive and user-friendly software platform for mass spectrometry imaging data analysis.
• To address the computational and accessibility challenges in MSI data analysis.
• To provide an integrated solution for end-to-end MSI workflows.

Main Methods:

• MassVision is built on the 3D Slicer ecosystem, offering an intuitive interface.
• Key functionalities include visualization, segmentation, colocalization, data merging, preprocessing, statistical analysis, and AI model deployment.
• The platform supports high-throughput studies and multislide datasets.

Main Results:

• MassVision demonstrated effectiveness in exploratory data analysis, ion identification, and tissue-type classification.
• The platform seamlessly integrates various MSI data handling steps.
• Case studies utilized both in-house and public MSI data from different modalities.

Conclusions:

• MassVision lowers barriers for researchers with varying computational expertise in MSI analysis.
• The platform facilitates the discovery of new biological insights and structures from MSI data.
• MassVision provides a robust, integrated tool for advancing MSI data analysis and interpretation.