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Updated: May 16, 2025

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
Published on: September 11, 2011
Experimental investigation of discrete range modulation proton radiography with a focus on edge-blurring improvement
I-Chun Cho1, Yu-Hsin Cheng2, Yi-Ting Liu3
1Research Center for Radiation Medicine, Chang Gung University, Taoyuan City 333, Taiwan; Radiation Research Core Laboratory, Chang Gung Memorial Hospital Linkou Branch, Taoyuan City 333, Taiwan.
Purpose:
Proton radiography's reliability in range verification is hindered by image quality due to multiple Coulomb scattering. This study evaluated the feasibility of using discrete range modulation (DRM) proton radiography for proton range estimation with Monte Carlo simulations and experimental approaches.
Methods:
The PTSim Monte Carlo code analyzed the image resolution of the DRM method for various checkerboard phantom configurations and identified the source of edge-blurring using the geometric trigger feature. Additionally, an in-house MATLAB code was developed to deconvolute the energy dose curve and reduce edge-blurring effects in DRM images caused by multiple Coulomb scattering (MCS). In the experimental part, a CIRS phantom and a human-like Alderson Radiation Therapy phantom were used to acquire the first DRM image and apply a commercial 2D detector under clinical conditions.
Results:
The simulation results from the checkerboard phantom revealed that the image resolution of the DRM image can reach 1 mm in both 5 cm and 9 cm phantom. The geometric trigger feature in the simulation helped remove the edge-blurring effect caused by MCS from the DRM image. Experiments with the CIRS phantom showed a maximum water-equivalent path length (WEPL) prediction error of approximately 1 mm for various materials. The experiment with the human-like phantom demonstrated that DRM can image complex structures, including soft tissue and skeletal regions.
Conclusions:
In conclusion, the DRM method showed potential for clinical use, producing high-quality images, providing accurate WEPL prediction, correcting edge-blurring caused by MCS, and imaging complex structures.

