De Kerf Geert, Barragán-Montero Ana, Brouwer Charlotte L, Pisciotta Pietro, Biston Marie-Claude, Fusella Marco, Herbin Geoffroy, Kneepkens Esther, Marrazzo Livia, Mason Joshua, Nielsen Camila Panduro, Snijders Koen, Tanadini-Lang Stephanie, Vaandering Aude, Janssen Tomas M
Department of Radiation Oncology, Iridium Netwerk, Wilrijk (Antwerp), Belgium.
Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium.
Phys Imaging Radiat Oncol. 2025 Apr 6;34:100765. doi: 10.1016/j.phro.2025.100765. eCollection 2025 Apr.
Fully automated workflows (FAWs) for radiotherapy treatment preparation are feasible, but remain underutilized in clinical settings. A multicentre prospective risk analysis was conducted to support centres in managing FAW-related risks and to identify workflow steps needing improvement.
Eight European radiotherapy centres performed a failure mode and effect analysis (FMEA) on a hypothetical FAW, with a manual review step at the end. Centres assessed occurrence, severity and detectability of provided, or newly added, failure modes to obtain a risk score. Quantitative analysis was performed on curated data, while qualitative analysis summarized free text comments.
Manual review and auto-segmentation were identified as the highest-risk steps and the highest scoring failure modes were associated with inadequate manual review (high detectability and severity score), incorrect (i.e. outside of intended use) application of the FAW (high severity score) and protocol violations during patient preparation (high occurrence score). The qualitative analysis highlighted amongst others the risk of deviation from protocol and the difficulty for manual review to recognize automation errors. The risk associated with the technical parts of the workflow was considered low.
The FMEA analysis highlighted that points where people interact with the FAW were considered higher risk than lack of trust in the FAW itself. Major concerns were the ability of people to correctly judge output in case of low generalizability and increasing skill degradation. Consequently, educational programs and interpretative tools are essential prerequisites for widespread clinical application of FAWs.
用于放射治疗准备的全自动化工作流程（FAWs）是可行的，但在临床环境中的利用率仍然较低。开展了一项多中心前瞻性风险分析，以帮助各中心管理与全自动化工作流程相关的风险，并确定需要改进的工作流程步骤。
八个欧洲放射治疗中心对一个假设的全自动化工作流程进行了失效模式与效应分析（FMEA），最后有一个人工审核步骤。各中心评估了所提供或新增加的失效模式的发生、严重程度和可检测性，以获得风险评分。对整理后的数据进行定量分析，而定性分析则总结了自由文本评论。
人工审核和自动分割被确定为最高风险步骤，得分最高的失效模式与人工审核不足（高可检测性和严重程度评分）、全自动化工作流程的不正确（即超出预期用途）应用（高严重程度评分）以及患者准备过程中的违反方案情况（高发生率评分）相关。定性分析特别强调了偏离方案的风险以及人工审核难以识别自动化错误的问题。与工作流程技术部分相关的风险被认为较低。
失效模式与效应分析突出表明，人们与全自动化工作流程交互的环节被认为风险高于对全自动化工作流程本身缺乏信任。主要担忧的是，在普遍性较低且技能退化加剧的情况下，人们正确判断输出的能力。因此，教育项目和解释工具是全自动化工作流程广泛临床应用的必要前提条件。
