Sparse-view proton computed tomography using modulated proton beams.

Area of Science:

• Medical Imaging
• Particle Physics
• Computational Imaging

Background:

• Proton imaging offers faster acquisition and simpler implementation than traditional methods.
• Challenges in proton CT include scattering, energy straggling, and patient radiation dose.
• Iterative reconstruction is explored to address limitations in sparse-view proton CT.

Purpose of the Study:

• To investigate iterative image reconstruction techniques for proton CT.
• To address challenges posed by scattering, energy straggling, and sparse data acquisition.
• To evaluate the performance of different iterative algorithms for proton CT.

Main Methods:

• Proton projection images acquired using modulated beams and EBT2 film detectors.
• Objects (soft tissue, bone) scanned at 40 views; images converted to water-equivalent thickness.
• Implemented and compared four iterative algorithms: ASD-POCS, SM-POCS, SM-EM, EM-TV, analyzing CNR and RMSE.

Main Results:

• Higher electron density objects, like bone, reconstructed with high accuracy (within 1% error).
• POCS-based algorithms demonstrated monotonic convergence, outperforming EM-based algorithms in noise and RMSE.
• ASD-POCS achieved the best contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE).

Conclusions:

• Developed and applied four iterative algorithms for proton CT image reconstruction.
• Proton CT imaging with modulated beams and sparse-view sampling is feasible.
• Further image improvement is needed for clinical treatment planning applications.