Spectrally resolved bioluminescence tomography with adaptive finite element analysis: methodology and simulation

Area of Science:

• Biomedical Imaging
• Molecular Imaging
• Optical Imaging

Background:

• Bioluminescence tomography (BLT) is a sensitive in vivo molecular imaging technique for small animals.
• Deeply located bioluminescent sources are challenging to localize due to photon transport and noisy boundary data.
• Previous work utilized achromatic/monochromatic measurements and a priori source region strategies.

Purpose of the Study:

• To develop a novel spectrally solved tomographic algorithm for improved BLT reconstruction.
• To enhance the localization accuracy of bioluminescent sources, especially those in deeper tissue.
• To address the ill-posed nature and non-uniqueness inherent in BLT.

Main Methods:

• Implemented multispectral measurements combined with anatomical and optical information.
• Employed a posteriori permissible source region selection and adaptive mesh refinement.
• Utilized an optimized reconstruction method with modifications for efficiency and robustness.
• Incorporated computational burden reduction techniques.

Main Results:

• The proposed algorithm accurately reconstructs bioluminescent sources in deeper positions within a virtual mouse phantom.
• Demonstrated improved reconstruction quality by mitigating ill-posedness and avoiding dimensional disaster.
• Showcased enhanced robustness and efficiency in source reconstruction.
• Validated unique predominance in BLT reconstruction concerning optical property errors and deep source discernment.

Conclusions:

• The spectrally solved tomographic BLT algorithm significantly improves the reconstruction of deep bioluminescent sources.
• This advancement offers superior performance in molecular and cellular imaging applications in vivo.
• The method provides a robust and efficient solution for overcoming key limitations in current BLT techniques.