Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, MI, USA.
Department of Radiation Oncology, Stony Brook University, NY, USA.
Comput Methods Programs Biomed. 2018 Feb;154:1-8. doi: 10.1016/j.cmpb.2017.11.001. Epub 2017 Nov 2.
The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART.
Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools.
The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement.
An efficient and convenient dose tracking system for ART in the clinical setting is presented. The software and automated processes were rigorously evaluated and validated using patient image datasets. Automation of the various procedures has improved efficiency significantly, allowing for the routine clinical application of ART for improving radiation therapy effectiveness.
自适应放疗（ART）在常规临床实践中的实施具有技术挑战性，需要大量资源来执行和验证每个过程步骤。本报告的目的是确定 ART 的关键组成部分，说明特定自动化程序如何提高效率，并促进 ART 的常规临床应用。
从临床数据库中导出并转换为点剂量跟踪和累积的中间格式的患者图像中使用数据。该过程使用内部开发的软件自动化完成，该软件包含三个模块化组件：ART 引擎、用户交互工具和集成工具。ART 引擎使用以下模块执行计算任务：数据导入、图像预处理、剂量映射、剂量累积和报告。此外，开发了定制图形用户界面（GUI）以允许用户与选择过程（例如变形图像配准（DIR））进行交互。使用商业脚本应用程序编程接口将自动化剂量计算纳入常规治疗计划中。每个模块都被视为一个独立的程序，使用 C++或 C#编写，在分布式 Windows 环境中运行，由集成工具调度和监控。
在机构审查委员会（IRB）批准下，对 20 例前列腺癌患者和 96 例头颈部癌症患者进行了回顾性评估自动化跟踪系统。此外，还对头颈部癌症患者前瞻性地评估了该系统。总共处理了 780 个前列腺剂量分数和 2586 个头颈部癌症剂量分数，包括 DIR 和剂量映射。平均而言，每天的累积剂量在 3 小时内计算，手工工作限于每个病例 13 分钟，大约 10%的病例需要额外的 10 分钟来完善图像配准。
提出了一种用于临床环境中的 ART 的高效便捷的剂量跟踪系统。使用患者图像数据集对软件和自动化过程进行了严格的评估和验证。各种过程的自动化大大提高了效率，允许常规临床应用 ART 以提高放射治疗效果。
