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Updated: May 22, 2026
Analysis of Multidimensional Microscopy Data Using Cell-ACDC
Published on: November 7, 2025
A deep-learning framework reveals whole-body perturbations at cell level
Doris Kaltenecker1,2,3, Izabela Horvath4,5, Rami Al-Maskari4,5,6
1Institute for Diabetes and Cancer (IDC), Helmholtz Munich, German Research Center for Environmental Health, Neuherberg, Germany.
Abstract:
Many diseases, including obesity, have systemic effects that perturb multiple organ systems throughout the body1,2. However, tools for comprehensive, high-resolution analysis of disease-associated changes at the whole-body scale have been lacking. Here we developed MouseMapper, a suite of foundation-model-based deep-learning algorithms enabling multi-system analysis of disease across the entire mouse body. MouseMapper enables whole-body quantitative analysis of nerves and immune cells, resolving fine axonal branches and immune-cell clusters while automatically segmenting 31 organs and tissues. We used MouseMapper to study diet-induced obesity, and identified structural alterations of the infraorbital branch of the trigeminal ganglia. This structural impairment in infraorbital nerves was associated with functional sensory deficits in whisker sensing. Furthermore, we identified proteomic changes in the trigeminal ganglion affecting axon remodelling and complement pathways both in mice and humans. MouseMapper also generated detailed three-dimensional inflammation maps by characterizing immune cell cluster compositions across tissues. The MouseMapper framework demonstrates robust generalizability across different imaging resolutions and datasets. Our study provides a powerful, scalable approach for identifying and quantifying systemic pathologies, bridging molecular insights from animal models to human conditions.
Insights
Researchers developed MouseMapper, a deep learning tool for whole-body disease analysis in mice. This technology reveals systemic changes in nerves and immune cells, linking obesity to sensory deficits and identifying conserved molecular pathways.
Area of Science:
- Biomedical imaging
- Computational biology
- Systems biology
Background:
- Diseases like obesity cause widespread systemic effects impacting multiple organ systems.
- Existing tools lack the comprehensive, high-resolution analysis needed for whole-body disease pathology.
- A need exists for advanced methods to quantify multi-system changes across an entire organism.
Purpose of the Study:
- To introduce MouseMapper, a novel deep learning framework for multi-system disease analysis at the whole-body scale.
- To enable quantitative, high-resolution analysis of anatomical and cellular changes across 31 organs and tissues.
- To apply MouseMapper to study diet-induced obesity and its systemic consequences.
Main Methods:
- Development of foundation-model-based deep learning algorithms for automated segmentation and analysis.
- Quantitative whole-body analysis of neural and immune cell structures.
- Integration of imaging data with proteomic analysis for molecular insights.
Main Results:
- MouseMapper successfully segmented 31 organs and tissues, enabling whole-body quantitative analysis of nerves and immune cells.
- Diet-induced obesity led to structural alterations in trigeminal ganglia nerves, correlating with whisker sensory deficits.
- Proteomic analysis revealed conserved pathways (axon remodeling, complement) affected in both mice and humans.
- Generated 3D inflammation maps by characterizing immune cell composition across tissues.
Conclusions:
- MouseMapper provides a powerful and scalable approach for identifying and quantifying systemic pathologies.
- The framework demonstrates generalizability across different imaging resolutions and datasets.
- This study bridges molecular insights from animal models to human conditions, offering a new paradigm for disease research.
