Abstract

Abstract Positron Emission Topography (PET) is a promising technique to verify the dose distribution from proton therapy, a precise treatment modality increasingly used in radiation oncology because its radiation pattern conforms more closely to the configuration of a tumor than does that from X-ray radiation, thereby sparing normal healthy tissue. Proton therapy produces positron-emitting isotopes along the beam’s path, allowing PET to image the distribution of therapeutic energy, viz., a form of quality assurance of the treatment. This ability is especially important when treating heterogeneous organs, such as the lungs or the head-and-neck, where calculating the expected dose distribution for treatment is complex. Here, we present the findings from our Monte Carlo simulations of the yield of positron emitters produced by proton beams of up to 250 MeV, followed by our statistically realistic Monte Carlo simulation of the images expected from a clinical PET scanner. Our emphases lay in predicting accurately the distribution of positron emitters, and in determining the quality of the PET signal near the Bragg peak that is critical to the success of PET imaging for verifying the proton beam’s location and dosimetry. We also demonstrate that the results depend strongly on the accuracy of the available nuclear reaction cross section data. Accordingly, we quantify the differences in the calculated positron-emitter yields from four different sets of such data, comparing them to the simulated distributions of positron-emitter production and absorbed proton energies.

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