Investigates proton computed tomography effectiveness in oncology, suggesting improved treatment planning.
Proton computed tomography (pCT) is a promising technique for planning the treatment of oncology patients undergoing radiation therapy. It relies on determining the proton stopping power in the patient’s tissues using tracking calorimeters. This study proposes a concept of pCT based on monolithic active silicon pixel sensors, which can record proton tracks and measure proton energy under conditions of high intensity. The paper provides a method for reconstructing proton tracks using cellular automata algorithm. Experimentally obtained pixel cluster multiplicity as a function of energy along with images of phantoms irradiated by proton beams are also presented.
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Petrov et al. (2026) studied this question.
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