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关于评估机器人图像引导小动物放射系统一致性的简单高效月度质量管理计划的提案。

Proposal for a Simple and Efficient Monthly Quality Management Program Assessing the Consistency of Robotic Image-Guided Small Animal Radiation Systems.

作者信息

Brodin N Patrik, Guha Chandan, Tomé Wolfgang A

机构信息

*Department of Radiation Oncology, Montefiore Medical Center, Bronx, NY 10461; † Institute for Onco-Physics, Albert Einstein College of Medicine, Bronx, NY 10461.

出版信息

Health Phys. 2015 Nov;109(3 Suppl 3):S190-9. doi: 10.1097/HP.0000000000000323.

DOI:10.1097/HP.0000000000000323
PMID:26425981
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4602164/
Abstract

Modern pre-clinical radiation therapy (RT) research requires high precision and accurate dosimetry to facilitate the translation of research findings into clinical practice. Several systems are available that provide precise delivery and on-board imaging capabilities, highlighting the need for a quality management program (QMP) to ensure consistent and accurate radiation dose delivery. An ongoing, simple, and efficient QMP for image-guided robotic small animal irradiators used in pre-clinical RT research is described. Protocols were developed and implemented to assess the dose output constancy (based on the AAPM TG-61 protocol), cone-beam computed tomography (CBCT) image quality and object representation accuracy (using a custom-designed imaging phantom), CBCT-guided target localization accuracy and consistency of the CBCT-based dose calculation. To facilitate an efficient read-out and limit the user dependence of the QMP data analysis, a semi-automatic image analysis and data representation program was developed using the technical computing software MATLAB. The results of the first 6-mo experience using the suggested QMP for a Small Animal Radiation Research Platform (SARRP) are presented, with data collected on a bi-monthly basis. The dosimetric output constancy was established to be within ±1 %, the consistency of the image resolution was within ±0.2 mm, the accuracy of CBCT-guided target localization was within ±0.5 mm, and dose calculation consistency was within ±2 s (±3%) per treatment beam. Based on these results, this simple quality assurance program allows for the detection of inconsistencies in dosimetric or imaging parameters that are beyond the acceptable variability for a reliable and accurate pre-clinical RT system, on a monthly or bi-monthly basis.

摘要

现代临床前放射治疗(RT)研究需要高精度和准确的剂量测定,以便将研究结果转化为临床实践。有几种系统可提供精确的照射和机载成像功能,这凸显了质量管理计划(QMP)的必要性,以确保放射剂量的输送一致且准确。本文描述了一种用于临床前RT研究中图像引导的机器人小动物辐照器的持续、简单且高效的QMP。制定并实施了相关协议,以评估剂量输出稳定性(基于AAPM TG-61协议)、锥束计算机断层扫描(CBCT)图像质量和物体再现准确性(使用定制设计的成像体模)、CBCT引导的靶区定位准确性以及基于CBCT的剂量计算的一致性。为了便于高效读取并减少QMP数据分析对用户的依赖,使用技术计算软件MATLAB开发了一个半自动图像分析和数据表示程序。本文展示了使用建议的QMP对小动物辐射研究平台(SARRP)进行的前6个月的经验结果,数据每两个月收集一次。剂量测定输出稳定性确定在±1%以内,图像分辨率的一致性在±0.2毫米以内,CBCT引导的靶区定位准确性在±0.5毫米以内,每次治疗束的剂量计算一致性在±2秒(±3%)以内。基于这些结果,这个简单的质量保证程序能够每月或每两个月检测出剂量测定或成像参数中的不一致性,这些不一致性超出了可靠且准确的临床前RT系统可接受的变异性范围。

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本文引用的文献

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Modality comparison for small animal radiotherapy: a simulation study.小动物放射治疗的模态比较:一项模拟研究。
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A multipurpose quality assurance phantom for the small animal radiation research platform (SARRP).小动物辐照研究平台(SARRP)多用型质量保证体模。
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