Automated quantification of bioluminescence images

Area of Science:

• Biomedical Imaging
• Quantitative Biology
• Animal Models

Background:

• Accurate in vivo biodistribution analysis is crucial for preclinical research and disease modeling.
• Existing methods for analyzing bioluminescent reporters in small animals can be operator-dependent and lack data congruency across subjects.
• Quantitative, reproducible, and automated analysis tools are needed to advance research throughput.

Purpose of the Study:

• To develop a computer-aided analysis tool for quantitative determination of bioluminescent reporter distributions in small animals.
• To enhance data congruency and reproducibility in in vivo imaging studies.
• To accelerate human disease modeling in mice through improved biodistribution analysis.

Main Methods:

• Development of a body-fitting animal shuttle and a statistical mouse atlas, spatially aligned and scaled by animal weight.
• Integration of multispectral bioluminescence tomography with the shuttle's spatial framework for rapid biodistribution calculation.
• Validation of the tool by monitoring bacterial infection and comparing bacterial organ burden to serial-plating methods.

Main Results:

• Demonstrated quantitative monitoring of bacterial infection, with bacterial organ burden determined and validated against the serial-plating method.
• Validated the statistical mouse atlas against existing anatomical reference techniques.
• Achieved operator-independent and computer-driven data analysis for in vivo biodistribution.

Conclusions:

• The developed tool significantly increases data throughput and reproducibility in small animal imaging.
• The system enables rapid and accurate in vivo biodistribution calculations, accelerating disease modeling.
• This approach provides a robust platform for quantitative analysis of bioluminescent reporters in preclinical research.