DOI: 10.57760/sciencedb.07866
title: Dose reconstruction with Compton camera during proton therapy via subset-driven origin ensemble and double evolutionary algorithm
title: Dose reconstruction with Compton camera during proton therapy via subset-driven origin ensemble and double evolutionary algorithm

description: This data includes key parameters, source codes, and original data from the published paper.Compton camera-based prompt gamma (PG) imaging has been proposed for range verification during proton therapy. However, a deviation between the PG distribution and the dose distribution, as well as the difference between the reconstructed PG and the exact values limit the effectiveness of the approach in accurate range monitoring during clinical applications. The aim of the study is to realize a PG-based dose reconstruction with a Compton camera, further improving the prediction accuracy of in-vivo range verification and providing a novel method for beam monitoring during proton therapy. In this paper, we present an approach based on a subset-driven origin ensemble with resolution recovery (SD-OE-RR) and a double evolutionary algorithm (DEA) to reconstruct the dose depth profile (DDP) from the gamma events obtained by a Cadmium−Zinc−Telluride (CZT) Compton camera with limited position and energy resolution. The simulations of proton pencil beam with clinical particle rate irradiating phantoms made of different materials and the CT-based thoracic phantom were used to evaluate the feasibility of the proposed method. The results show that for the monoenergetic proton pencil beam irradiating homogeneous-material box phantom, the accuracy of reconstructed DDP was within 0.3 mm for range prediction and within 5.2% in terms of dose prediction. In particular, for a 1.6 Gy irradiation in the thoracic tumors therapy simulation, the range deviation of the reconstructed spread-out Bragg peak was within 0.8 mm, and the relative dose deviation in the peak area was less than 7% compared to the exact values. The results demonstrate the potential and feasibility of the proposed method in future Compton-based accurate dose reconstruction and range verification during proton therapy.
description: This data includes key parameters, source codes, and original data from the published paper.Compton camera-based prompt gamma (PG) imaging has been proposed for range verification during proton therapy. However, a deviation between the PG distribution and the dose distribution, as well as the difference between the reconstructed PG and the exact values limit the effectiveness of the approach in accurate range monitoring during clinical applications. The aim of the study is to realize a PG-based dose reconstruction with a Compton camera, further improving the prediction accuracy of in-vivo range verification and providing a novel method for beam monitoring during proton therapy. In this paper, we present an approach based on a subset-driven origin ensemble with resolution recovery (SD-OE-RR) and a double evolutionary algorithm (DEA) to reconstruct the dose depth profile (DDP) from the gamma events obtained by a Cadmium−Zinc−Telluride (CZT) Compton camera with limited position and energy resolution. The simulations of proton pencil beam with clinical particle rate irradiating phantoms made of different materials and the CT-based thoracic phantom were used to evaluate the feasibility of the proposed method. The results show that for the monoenergetic proton pencil beam irradiating homogeneous-material box phantom, the accuracy of reconstructed DDP was within 0.3 mm for range prediction and within 5.2% in terms of dose prediction. In particular, for a 1.6 Gy irradiation in the thoracic tumors therapy simulation, the range deviation of the reconstructed spread-out Bragg peak was within 0.8 mm, and the relative dose deviation in the peak area was less than 7% compared to the exact values. The results demonstrate the potential and feasibility of the proposed method in future Compton-based accurate dose reconstruction and range verification during proton therapy.