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如何利用肿瘤组织学的肿瘤范围和复发模式数据来制定实体恶性肿瘤的放疗靶区。

How Histopathologic Tumor Extent and Patterns of Recurrence Data Inform the Development of Radiation Therapy Treatment Volumes in Solid Malignancies.

机构信息

Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD.

Department of Radiation Oncology, Rush University, Chicago, IL.

出版信息

Semin Radiat Oncol. 2018 Jun;28(3):218-237. doi: 10.1016/j.semradonc.2018.02.007.

Abstract

The ability to deliver highly conformal radiation therapy using intensity-modulated radiation therapy and particle therapy provides for new opportunities to improve patient outcomes by reducing treatment-related morbidities following radiation therapy. By reducing the volume of normal tissue exposed to radiation therapy (RT), while also allowing for the opportunity to escalate the dose of RT delivered to the tumor, use of conformal RT delivery should also provide the possibility of expanding the therapeutic index of radiotherapy. However, the ability to safely and confidently deliver conformal RT is largely dependent on our ability to clearly define the clinical target volume for radiation therapy, which requires an in-depth knowledge of histopathologic extent of different tumor types, as well as patterns of recurrence data. In this article, we provide a comprehensive review of the histopathologic and radiographic data that provide the basis for evidence-based guidelines for clinical tumor volume delineation.

摘要

使用调强放疗和粒子治疗来提供高度适形的放射治疗的能力为通过降低放射治疗相关的发病率来改善患者预后提供了新的机会。通过减少正常组织受到放射治疗(RT)照射的体积,同时也允许增加给予肿瘤的 RT 剂量,使用适形 RT 输送还应该为扩大放射治疗的治疗指数提供可能性。然而,安全且有信心地提供适形 RT 的能力在很大程度上取决于我们清楚地定义放射治疗的临床靶体积的能力,这需要深入了解不同肿瘤类型的组织病理学范围以及复发数据模式。在本文中,我们提供了对组织病理学和影像学数据的全面回顾,这些数据为临床肿瘤体积描绘的循证指南提供了依据。

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