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Boron neutron capture therapy applied to advanced breast cancers: Engineering simulation and feasibility study of the radiation treatment protocol.

机译:硼中子捕获疗法在晚期乳腺癌中的应用:放射治疗方案的工程模拟和可行性研究。

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摘要

This dissertation describes a novel Boron Neutron Capture Therapy (BNCT) application for the treatment of human epidermal growth factor receptor type 2 positive (HER2+) breast cancers. The original contribution of the dissertation is the development of the engineering simulation and the feasibility study of the radiation treatment protocol for this novel combination of BNCT and HER2+ breast cancer treatment.;This new concept of BNCT, representing a radiation binary targeted treatment, consists of the combination of two approaches never used in a synergism before. This combination may offer realistic hope for relapsed and/or metastasized breast cancers. This treatment assumes that the boronated anti-HER2 monoclonal antibodies (MABs) are administrated to the patient and accumulate preferentially in the tumor. Then the tumor is destroyed when is exposed to neutron irradiation. Since the use of anti-HER2 MABs yields good and promising results, the proposed concept is expected to amplify the known effect and be considered as a possible additional treatment approach to the most severe breast cancers for patients with metastasized cancer for which the current protocol is not successful and for patients refusing to have the standard treatment protocol.;This dissertation makes an original contribution with an integral numerical approach and proves feasible the combination of the aforementioned therapy and disease. With these goals, the dissertation describes the theoretical analysis of the proposed concept providing an integral engineering simulation study of the treatment protocol. An extensive analysis of the potential limitations, capabilities and optimization factors are well studied using simplified models, models based on real CT patients' images, cellular models, and Monte Carlo (MCNP5/X) transport codes. One of the outcomes of the integral dosimetry assessment originally developed for the proposed treatment of advanced breast cancers is the implementation of BNCT for HER2+ breast cancers for deep seated tumors using MITRII-FCB facility with an 8 cm diameter beam (port closest-to-tumor position), with boron concentrations in the tumor higher than 32 mug/g, and for a tumor-to-healthy tissue boron concentration ratio of 8:1. The therapeutic ratios for the proposed treatment would be higher than five for skin and adipose tissue and higher than three for tumor surrounding fibroglandular tissue. The microdosimetry study shows potential improvements in the therapeutic ratios based on the expected sub-cellular boron biodistributions. The engineering simulation study of clinical cases shows the advantages of using BNCT for HER+ breast cancers. Assuming an assured high efficiency of the boron agent delivery, the proposed concept can be considered for stage IV HER2+ breast cancers in treating the metastasized tumors in brain, head and neck, and lungs.
机译:本文介绍了一种新型的硼中子俘获疗法(BNCT),用于治疗人类表皮生长因子受体2型阳性(HER2 +)乳腺癌。论文的最初贡献是对这种新型BNCT和HER2 +乳腺癌联合治疗的放射学治疗方案的工程仿真开发和可行性研究。BNCT的这一新概念代表了一种放射二元靶向治疗,包括:以前从未在协同中使用过的两种方法的组合。这种组合可能为复发和/或转移的乳腺癌提供现实的希望。该治疗假定向患者施用硼化抗HER2单克隆抗体(MAB),并优先在肿瘤中蓄积。然后当暴露于中子辐射时肿瘤被破坏。由于抗HER2 MAB的使用产生了良好且有希望的结果,因此,所提出的概念有望扩大已知的效果,并被认为是针对当前转移方案为转移性癌症患者的最严重乳腺癌的一种可能的其他治疗方法。并不成功,对于拒绝接受标准治疗方案的患者。本论文以积分数值方法做出了独创的贡献,并证明了上述疗法与疾病的结合是可行的。基于这些目标,本文描述了所提出概念的理论分析,为治疗方案提供了完整的工程仿真研究。使用简化模型,基于实际CT患者图像的模型,细胞模型和蒙特卡洛(MCNP5 / X)传输代码,可以对潜在限制,功能和优化因素进行广泛的分析。最初为晚期乳腺癌的拟议治疗而开发的整体剂量学评估的结果之一是,使用MITRII-FCB装置(直径为8厘米)(对于肿瘤最接近的端口)对深部肿瘤的HER2 +乳腺癌实施BNCT位置),肿瘤中的硼浓度高于32杯/克,并且肿瘤与健康组织的硼浓度比为8:1。对于皮肤和脂肪组织,所提出的治疗的治疗比率将高于五,对于围绕纤维腺腺组织的肿瘤,治疗比率将高于三。微量剂量研究表明,基于预期的亚细胞硼生物分布,治疗率有潜在的提高。工程案例的工程仿真研究表明,使用BNCT治疗HER +乳腺癌具有优势。假设硼剂的递送效率高,可以考虑将IV期HER2 +乳腺癌用于治疗脑,头,颈和肺部转移性肿瘤。

著录项

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Nuclear.;Physics Radiation.;Health Sciences Radiology.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 247 p.
  • 总页数 247
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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