Compactly Supported Radial Basis Function-Based Meshless Method for Photon Propagation Model of Fluorescence...

Area of Science:

• Biomedical Imaging
• Medical Physics
• Computational Biology

Background:

• Fluorescence Molecular Tomography (FMT) is crucial for cancer research, enabling quantitative, noninvasive imaging of fluorescent probes in tissues.
• Current FMT photon propagation modeling using the Finite Element Method (FEM) faces limitations including long computation times, discretization errors, and mesh generation challenges, impacting imaging accuracy.

Purpose of the Study:

• To introduce and validate a novel meshless method (MM) based on compactly supported radial basis functions (CSRBFs) for improved accuracy in FMT's photon propagation modeling.
• To overcome the inherent limitations of FEM in FMT applications.

Main Methods:

• Developed a meshless method (MM) interpolating the photon propagation model (PPM) using independent nodes and continuous CSRBFs, eliminating the need for complex mesh generation.
• Validated the MM through numerical simulations of heterogeneous mouse models to assess surface fluorescence measurements.
• Conducted in vivo experiments to evaluate tomographic reconstruction accuracy.

Main Results:

• The proposed MM demonstrated surface fluorescence measurements closely matching the Monte Carlo (MC) method, a recognized gold standard.
• In vivo experiments showed that the MM achieved more accurate tomographic reconstruction results compared to conventional methods.
• The MM successfully avoided complex mesh generation, simplifying the implementation of the PPM for FMT.

Conclusions:

• The novel CSRBFs-based meshless method offers a significant advancement for photon propagation modeling in FMT.
• This improved accuracy in FMT has direct implications for enhancing cancer diagnosis, treatment monitoring, and drug discovery research.
• The meshless approach provides a more efficient and accurate alternative to FEM for FMT applications.