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Updated: Sep 20, 2025

Fabrication and Characterization of Optical Tissue Phantoms Containing Macrostructure
Published on: February 12, 2018
Toward fluorescence digital twins: multi-parameter experimental validation of fluorescence Monte Carlo simulations
Mayna H Nguyen1, Ethan P M LaRochelle1, Edwin A Robledo1
1QUEL Imaging, White River Junction, Vermont, United States.
Significance:
As fluorescence-guided surgery (FGS) gains clinical adoption, robust and experimentally validated computational models for tissue fluorescence are increasingly essential. Although there have been several developments in modeling fluorescence with Monte Carlo simulations, the scope of the experimental validation has been limited in the parameters tested and phantoms used.
Aim:
We aim to present and experimentally validate a graphics processing unit (GPU)-accelerated, voxel-based Monte Carlo fluorescence framework capable of modeling varying fluorophore concentrations, optical properties, and complex three-dimensional (3D) geometries.
Approach:
A two-step approach (MCX-ExEm) based on Monte Carlo eXtreme was developed for simulating fluorescence. Both commercial reference targets and custom 3D-printed phantoms with well-characterized optical properties were imaged for varying parameters-including absorption, scattering, fluorophore concentrations, and geometries-and compared against simulations.
Results:
Strong agreement is observed between simulated and experimental fluorescence across all tested parameters. MCX-ExEm accurately captures nonlinear quenching at high fluorophore concentrations, variations driven by scattering and absorption, intensity scaling with volume, and depth-dependent attenuation and resolution. Minor deviations occur primarily under low-scattering or low-absorption regimes, where optical characterization presents greater uncertainties.
Conclusions:
By integrating experimentally validated simulations with a broad range of solid phantoms, this framework establishes a foundation for developing fluorescence digital twins, enabling faster and more systemic testing of fluorescence imaging systems. These findings can help accelerate the design and optimization of FGS and other fluorescence-based biomedical applications.
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