Computationally efficient x-ray simulation framework using parameterized material attenuation models in anatomically...

Area of Science:

• Medical Imaging
• Computational Physics
• Radiological Sciences

Background:

• Virtual clinical trials offer an efficient alternative for evaluating imaging technologies.
• X-ray simulations face computational challenges with complex and heterogeneous digital phantoms.
• Parameterization models can represent material properties using fewer coefficients.

Purpose of the Study:

• To develop and validate an x-ray simulation framework using parameterization models for material attenuation.
• To reduce computational costs in x-ray simulations while maintaining accuracy.
• To enhance the efficiency of virtual clinical trials.

Main Methods:

• Material attenuation modeled using a five-coefficient parameterization derived from physical cross-section data.
• Proposed method projects five parameter maps, independent of phantom complexity, unlike conventional ray-tracing.
• Framework validated using breast and whole-body phantoms, assessing errors in attenuation coefficients, sinograms, and reconstructed images.

Main Results:

• Maximum attenuation coefficient error was 0.007%, well below biological variability.
• Projection and reconstruction errors were within ±0.006%, significantly lower than projector model differences (±0.5%).
• Simulation times were significantly reduced, scaling linearly with the number of materials.

Conclusions:

• The framework provides accurate and efficient simulation of material attenuation in x-ray imaging, especially for complex anatomies.
• Validated in breast and whole-body imaging, it's a robust alternative to conventional methods.
• Supports advancements in virtual clinical trials and spectral imaging research.