WE-EF-303-06: Feasibility of PET Image-Based On-Line Proton Beam-Range Verification with Simulated Uniform Phantom and Human Brain Studies

Authors


Abstract

Purpose:

To study the feasibility of clinical on-line proton beam range verification with PET imaging

Methods:

We simulated a 179.2-MeV proton beam with 5-mm diameter irradiating a PMMA phantom of human brain size, which was then imaged by a brain PET with 300*300*100-mm^3 FOV and different system sensitivities and spatial resolutions. We calculated the mean and standard deviation of positron activity range (AR) from reconstructed PET images, with respect to different data acquisition times (from 5 sec to 300 sec with 5-sec step). We also developed a technique, “Smoothed Maximum Value (SMV)”, to improve AR measurement under a given dose. Furthermore, we simulated a human brain irradiated by a 110-MeV proton beam of 50-mm diameter with 0.3-Gy dose at Bragg peak and imaged by the above PET system with 40% system sensitivity at the center of FOV and 1.7-mm spatial resolution.

Results:

MC Simulations on the PMMA phantom showed that, regardless of PET system sensitivities and spatial resolutions, the accuracy and precision of AR were proportional to the reciprocal of the square root of image count if image smoothing was not applied. With image smoothing or SMV method, the accuracy and precision could be substantially improved. For a cylindrical PMMA phantom (200 mm diameter and 290 mm long), the accuracy and precision of AR measurement could reach 1.0 and 1.7 mm, with 100-sec data acquired by the brain PET. The study with a human brain showed it was feasible to achieve sub-millimeter accuracy and precision of AR measurement with acquisition time within 60 sec.

Conclusion:

This study established the relationship between count statistics and the accuracy and precision of activity-range verification. It showed the feasibility of clinical on-line BR verification with high-performance PET systems and improved AR measurement techniques.

Cancer Prevention and Research Institute of Texas grant RP120326, NIH grant R21CA187717, The Cancer Center Support (Core) Grant CA016672 to MD Anderson Cancer Center

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