Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Freeman Hospital, United Kingdom.
Northern Centre for Cancer Care, Newcastle upon Tyne Hospitals NHS Foundation Trust, Cumberland Infirmary, United Kingdom.
Phys Med Biol. 2024 Apr 24;69(9). doi: 10.1088/1361-6560/ad387e.
. To use automation to facilitate the monitoring of each treatment fraction using an electronic portal imaging device (EPID) baseddosimetry (IVD) system, allowing optimisation of breast radiotherapy delivery for individual patients and cohorts.. A suite of in-house software was developed to reduce the number of manual interactions with the commercial IVD system, dosimetry check. An EPID specific pixel sensitivity map facilitated use of the EPID panel away from the central axis. Point dose difference and the change in standard deviation in dose were identified as useful dose metrics, with standard deviation used in preference to gamma in the presence of a systematic dose offset. Automated IVD was completed for 3261 fractions across 704 patients receiving breast radiotherapy.. Multiple opportunities for treatment optimisation were identified for individual patients and across patient cohorts as a result of successful implementation of automated IVD. 5.1% of analysed fractions were out of tolerance with 27.1% of these considered true positives. True positive results were obtained on any fraction of treatment and if IVD had only been completed on the first fraction, 84.4% of true positive results would have been missed. This was made possible due to the automation that saved over 800 h of manual intervention and stored data in an accessible database.. An improved EPID calibration to allow off-axis measurement maximises the number of patients eligible for IVD (36.8% of patients in this study). We also demonstrate the importance in selecting context-specific assessment metrics and how these can lead to a managable false positive rate. We have shown that the use of fully automated IVD facilitates use on every fraction of treatment. This leads to identification of areas for treatment improvement for both individuals and across a patient cohort, expanding the uses of IVD from simply gross error detection towards treatment optimisation.
. 利用自动化技术，使用基于电子射野影像装置（EPID）的剂量验证（IVD）系统来监测每个治疗分次，从而优化个体患者和患者队列的乳腺癌放射治疗。我们开发了一整套内部软件，以减少与商业 IVD 系统的手动交互次数，进行剂量检查。EPID 专用像素灵敏度图可实现 EPID 面板在远离中心轴的位置使用。点剂量差和剂量标准差的变化被确定为有用的剂量指标，在存在系统剂量偏移的情况下，优先使用标准差而不是伽马。为 704 名接受乳腺癌放疗的患者的 3261 个分次完成了自动化 IVD。通过成功实施自动化 IVD，为个体患者和患者队列发现了多种治疗优化机会。分析的分次中有 5.1%超出了容限，其中 27.1%被认为是真正的阳性。在任何分次的治疗中都可以获得真正的阳性结果，如果仅在第一分次完成 IVD，则会错过 84.4%的真正阳性结果。这是因为自动化技术节省了超过 800 小时的手动干预时间，并将数据存储在可访问的数据库中，从而实现了这一目标。改进 EPID 校准以允许离轴测量可使更多的患者有资格接受 IVD（本研究中有 36.8%的患者）。我们还证明了选择特定于上下文的评估指标的重要性，以及这些指标如何导致可管理的假阳性率。我们已经表明，使用完全自动化的 IVD 可以方便地在每次治疗分次中使用。这导致了个体患者和患者队列中治疗改进领域的识别，将 IVD 的用途从简单的总误差检测扩展到治疗优化。
