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

化学 质谱法 质谱成像 端到端原则 开源 分析化学(期刊) 色谱法 人工智能 软件 计算机科学 程序设计语言
作者
Amoon Jamzad,Jade Warren,Ayesha Syeda,Martin Kaufmann,Natasha Iaboni,Christopher J.B. Nicol,John F. Rudan,Kevin Ren,David Hurlbut,Sonal Varma,Gábor Fichtinger,Parvin Mousavi
出处
期刊:Analytical Chemistry [American Chemical Society]
标识
DOI:10.1021/acs.analchem.5c04018
摘要

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.

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