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Development of a portal dose image prediction algorithm for arbitrary detector systems.

机译:开发用于任意探测器系统的门禁剂量图像预测算法。

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摘要

Portal imaging was originally developed for geometric treatment verification of photon beams used in cancer radiotherapy. More recently, portal imaging systems have been successfully used in dosimetric treatment verification applications. Many of the proposed dosimetric applications involve the accurate calculation of a predicted portal dose image, including both primary and scatter dose components emerging from the patient. This thesis presents the development of a two step model that predicts dose deposition in arbitrary portal image detectors. The algorithm requires patient computed tomographic data, source-detector distance, and knowledge of the incident photon beam fluence. The first step predicts the photon fluence entering a portal imaging detector located behind the patient. Primary fluence is obtained through simple ray tracing techniques, while scatter fluence prediction requires a library of scatter fluence kernels generated by Monte Carlo simulation. These kernels allow prediction of basic radiation transport parameters characterizing the scattered photons, including fluence and energy. The second step of the algorithm involves a superposition of Monte Carlo-generated pencil beam kernels, describing dose deposition in a specific detector, with the predicted incident fluence of primary and scattered photons. This process is performed separately for primary and scatter fluence at high and low spatial resolutions respectively, and yields a predicted planar dose image.; This algorithm is tested on a variety of phantoms including simple slab phantoms and anthropomorphic phantoms. Other clinical parameters were varied over a wide range of interest, including 6, 18, 23 MV photon beam spectra and 10–80 cm air gap between phantom and portal imaging detector. Both low and high atomic number detectors were used to verify the algorithm, including a linear array of fluid ionization chambers and a solid state, amorphous silicon detector. Agreement between predicted and measured portal dose is better than 5% in areas of low dose gradient (30%/cm) and better than 5 mm in areas of high dose gradient (>30%/cm) for the variety of situations tested here. It is concluded that this portal dose prediction algorithm is fast, accurate, allows separation of primary and scatter dose, and can model dose image formation in arbitrary detector systems.
机译:Portal成像最初是为对癌症放射治疗中使用的光子束进行几何处理验证而开发的。最近,门户成像系统已成功地用于剂量治疗验证应用中。许多建议的剂量学应用涉及对预测的门诊剂量图像的准确计算,包括从患者身上出现的主要剂量和散射剂量成分。本文提出了一个两步模型的开发,该模型可预测任意门户图像探测器中的剂量沉积。该算法需要患者计算的断层扫描数据,源-探测器距离以及对入射光子束通量的了解。第一步是预测光子通量进入位于患者身后的门成像仪。通过简单的射线跟踪技术即可获得主要能量密度,而散射能量密度预测则需要一个由蒙特卡洛模拟生成的散射能量密度内核库。这些内核可以预测表征散射光子的基本辐射传输参数,包括能量密度和能量。该算法的第二步涉及由蒙特卡洛生成的笔形束核的叠加,描述特定探测器中的剂量沉积,并预测初级和散射光子的入射通量。该过程分别在高和低空间分辨率下分别针对主能量密度和散射能量密度执行,并产生预测的平面剂量图像。该算法已在多种幻像上进行了测试,包括简单的平板幻像和拟人幻像。其他临床参数在广泛的关注范围内变化,包括6、18、23 MV光子束光谱以及体模和门成像探测器之间的10–80 cm气隙。低原子序数探测器和高原子序数探测器均用于验证算法,包括流体电离室的线性阵列和固态非晶硅探测器。对于此处测试的各种情况,在低剂量梯度(<30%/ cm)的区域中,预测和测量的门静脉剂量之间的一致性好于5%,在高剂量梯度(> 30%/ cm)的区域中好于5 mm 。结论是,该门禁剂量预测算法快速,准确,可以分离主要剂量和分散剂量,并且可以在任意检测器系统中模拟剂量图像的形成。

著录项

  • 作者单位

    The University of Manitoba (Canada).;

  • 授予单位 The University of Manitoba (Canada).;
  • 学科 Physics Radiation.
  • 学位 Ph.D.
  • 年度 2001
  • 页码 272 p.
  • 总页数 272
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 原子核物理学、高能物理学;
  • 关键词

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