Toward fluorescence digital twins: multi-parameter experimental validation of fluorescence Monte Carlo simulations...

Area of Science:

• Biomedical Optics
• Computational Modeling
• Medical Imaging

Background:

• Fluorescence-guided surgery (FGS) requires accurate computational models for tissue fluorescence.
• Existing Monte Carlo simulations for fluorescence have limited experimental validation.
• Need for robust models to support clinical adoption of FGS.

Purpose of the Study:

• To develop and experimentally validate a GPU-accelerated Monte Carlo fluorescence framework (MCX-ExEm).
• To model varying fluorophore concentrations, optical properties, and complex 3D geometries.
• To establish a foundation for fluorescence digital twins.

Main Methods:

• Developed a two-step, GPU-accelerated, voxel-based Monte Carlo framework (MCX-ExEm).
• Used commercial and custom 3D-printed phantoms for experimental validation.
• Compared simulations against experimental imaging across various parameters (absorption, scattering, concentration, geometry).

Main Results:

• Strong agreement between simulated and experimental fluorescence across tested parameters.
• MCX-ExEm accurately models nonlinear quenching, scattering/absorption effects, and depth-dependent attenuation.
• Minor deviations noted in low-scattering/absorption regimes due to optical characterization uncertainties.

Conclusions:

• Experimentally validated MCX-ExEm framework provides a foundation for fluorescence digital twins.
• Enables faster, systemic testing of fluorescence imaging systems.
• Accelerates design and optimization of FGS and other fluorescence-based biomedical applications.