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质子治疗的体内剂量测定:钆在整个治疗过程中的光谱响应的蒙特卡罗研究。

In vivo dosimetry for proton therapy: A Monte Carlo study of the Gadolinium spectral response throughout the course of treatment.

作者信息

Brás Mariana, Freitas Hugo, Gonçalves Patrícia, Seco João

机构信息

German Cancer Research Centre, Heidelberg, Germany.

Laboratório de Intrumentação e Física Experimental de Partículas, Lisbon, Portugal.

出版信息

Med Phys. 2025 Apr;52(4):2412-2424. doi: 10.1002/mp.17625. Epub 2025 Jan 21.

DOI:10.1002/mp.17625
PMID:39838583
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11972047/
Abstract

BACKGROUND

In proton radiotherapy, the steep dose deposition profile near the end of the proton's track, the Bragg peak, ensures a more conformed deposition of dose to the tumor region when compared with conventional radiotherapy while reducing the probability of normal tissue complications. However, uncertainties, as in the proton range, patient geometry, and positioning pose challenges to the precise and secure delivery of the treatment plan (TP). In vivo range determination and dose distribution are pivotal for mitigation of uncertainties, opening the possibility to reduce uncertainty margins and for adaptation of the TP.

PURPOSE

This study aims to explore the feasibility of utilizing gadolinium (Gd), a highly used contrast agent in MRI, as a surrogate for in vivo dosimetry during the course of scanning proton therapy, tracking the delivery of a TP and the impact of uncertainties intra- and inter-fraction in the course of treatment.

METHODS

Monte Carlo simulations (Geant4 11.1.1) were performed, where a Gd-filled volume was placed within a water phantom and underwent treatment with a scanning proton TP delivering 4 Gy. The secondary photons emitted upon proton-Gd interaction were recorded and assessed for various tumor displacements. The spectral response of Gd to each pencil beam irradiation is therefore used as a surrogate for dose measurements during treatment.

RESULTS

Results show that the deposited dose at the target volume can be tracked for each TP scanning point by correlating it with the recorded Gd signal. The analyzed Gd spectral line corresponded to the characteristic X-ray line at 43 keV. Displacements from the planned geometry could be distinguished by observing changes in the Gd signal induced by each pencil beam. Moreover, the total 43 keV signal recorded subsequently to the full TP delivery reflected deviations from the planned integral dose to the target.

CONCLUSIONS

The study suggests that the spectral response of a Gd-based contrast agent can be used for in vivo dosimetry, providing insights into the TP delivery. The Gd 43 keV spectral line was correlated with the dose at the tumor, its volume, and its position. Other variables that can impact the method, such as the kinetic energy of the incident protons and Gd concentration in the target were also discussed.

摘要

背景

在质子放疗中,质子束流末端附近陡峭的剂量沉积曲线,即布拉格峰,与传统放疗相比,可确保剂量更精确地沉积在肿瘤区域,同时降低正常组织并发症的发生概率。然而,质子射程、患者几何形状和定位等不确定性因素给治疗计划(TP)的精确和安全实施带来了挑战。体内射程测定和剂量分布对于减少不确定性至关重要,这为缩小不确定性边界以及调整TP提供了可能性。

目的

本研究旨在探讨利用钆(Gd)(一种在MRI中广泛使用的造影剂)作为扫描质子治疗过程中体内剂量测定替代物的可行性,跟踪TP的实施情况以及治疗过程中分次内和分次间不确定性的影响。

方法

进行了蒙特卡罗模拟(Geant4 11.1.1),将一个充满Gd的体积放置在水模体中,并用输送4 Gy的扫描质子TP进行治疗。记录质子与Gd相互作用时发射的次级光子,并针对各种肿瘤位移进行评估。因此,Gd对每个笔形束照射的光谱响应被用作治疗期间剂量测量的替代物。

结果

结果表明,通过将靶体积处沉积的剂量与记录的Gd信号相关联,可以跟踪每个TP扫描点的剂量。分析的Gd光谱线对应于43 keV的特征X射线线。通过观察每个笔形束引起的Gd信号变化,可以区分与计划几何形状的位移。此外,在整个TP输送后记录的总43 keV信号反映了与计划靶积分剂量的偏差。

结论

该研究表明,基于Gd的造影剂的光谱响应可用于体内剂量测定,为TP的实施提供见解。Gd 43 keV光谱线与肿瘤处的剂量、其体积及其位置相关。还讨论了其他可能影响该方法的变量,如入射质子的动能和靶中Gd的浓度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/87cbd337d2e9/MP-52-2412-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/ea3d59b6dac7/MP-52-2412-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/99ea600f10c7/MP-52-2412-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/6bc1962b3197/MP-52-2412-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/9ff16d5d6cf9/MP-52-2412-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/47f2ad988760/MP-52-2412-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/975ea7de9b06/MP-52-2412-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/2e9e15b1be8d/MP-52-2412-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/87cbd337d2e9/MP-52-2412-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/ea3d59b6dac7/MP-52-2412-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/99ea600f10c7/MP-52-2412-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/6bc1962b3197/MP-52-2412-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/9ff16d5d6cf9/MP-52-2412-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/47f2ad988760/MP-52-2412-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/975ea7de9b06/MP-52-2412-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/2e9e15b1be8d/MP-52-2412-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d5b2/11972047/87cbd337d2e9/MP-52-2412-g005.jpg

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