Liu Chunbo, Beltran Chris J, Shen Jiajian, Zhang Niles, Pi Yifei, Bues Martin, Park Justin, Lu Bo, Yaddanapudi Sridhar, Tan Jun, Furutani Keith M, Liang Xiaoying
Department of Radiation Oncology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Radiation Oncology, Mayo Clinic, Jacksonville, Florida, USA.
Int J Part Ther. 2025 Aug 5;17:101199. doi: 10.1016/j.ijpt.2025.101199. eCollection 2025 Sep.
Robustness evaluation is routinely used in clinics to ensure the intended dose delivery for intensity-modulated proton therapy (IMPT). Various methods have been proposed, but there is no consensus on which method should be adopted in clinical practice. This study examined various methods within the widely used worst-case approach to provide insights into IMPT plan evaluation.
We evaluated the robustness of 20 clinical IMPT plans (10 prostate and 10 head and neck). Five robustness evaluation methods were assessed: error-bar dose distribution (ebDD), root-mean-square error dose (RMSED) distribution, voxel-wise worst-case, physical scenario worst-case, and dose-volume histogram (DVH) band. Correlations between these methods were analyzed. Each method was reviewed for their quantitative and qualitative capabilities to identify potential underdosing or overdosing.
Strong correlations were found between ebDD and RMSED, and between voxel-wise worst-case and physical scenario worst-case. The DVH band method provides a straightforward way to assess whether the worst DVH meets plan criteria and to illustrate dose variations but lacks spatial detail to pinpoint areas of potential underdosing or overdosing. The voxel-wise worst-case captures the worst dose distribution across all evaluation metrics, allowing spatial identification of areas of concern within a single distribution. The physical scenario worst-case also pinpoints specific areas of concern but requires individual assessment for each region of interest and evaluation metric, which can be cumbersome. A 3D visualization with ebDD and RMSED highlights regions of dose variation but does not necessarily indicate clinically meaningful impact.
Different robustness evaluation methods offer different types of information. Our study provides valuable insights to help identify an effective and practical approach for clinical practice. Based on our findings, we propose a potential evaluation strategy: use the DVH band derived from physical uncertainty scenarios to assess whether the worst boundary values meet plan evaluation criteria, and, when concerns arise, apply the voxel-wise worst-case dose distribution to localize areas of potential risk.
稳健性评估在临床上常用于确保调强质子治疗（IMPT）的预期剂量传递。已经提出了各种方法，但对于在临床实践中应采用哪种方法尚无共识。本研究在广泛使用的最坏情况方法中检验了各种方法，以深入了解IMPT计划评估。
我们评估了20个临床IMPT计划（10个前列腺癌和10个头颈癌）的稳健性。评估了五种稳健性评估方法：误差条剂量分布（ebDD）、均方根误差剂量（RMSED）分布、体素级最坏情况、物理场景最坏情况和剂量体积直方图（DVH）带。分析了这些方法之间的相关性。对每种方法的定量和定性能力进行了审查，以识别潜在的剂量不足或过量。
发现ebDD与RMSED之间以及体素级最坏情况与物理场景最坏情况之间存在强相关性。DVH带方法提供了一种直接的方式来评估最坏的DVH是否符合计划标准并说明剂量变化，但缺乏空间细节来精确确定潜在剂量不足或过量的区域。体素级最坏情况捕获了所有评估指标中的最坏剂量分布，允许在单个分布中对关注区域进行空间识别。物理场景最坏情况也能精确确定特定的关注区域，但需要对每个感兴趣区域和评估指标进行单独评估，这可能很麻烦。使用ebDD和RMSED进行的三维可视化突出了剂量变化区域，但不一定表明具有临床意义的影响。
不同的稳健性评估方法提供不同类型的信息。我们的研究提供了有价值的见解，有助于确定一种有效且实用的临床实践方法。基于我们的发现，我们提出了一种潜在的评估策略：使用从物理不确定性场景导出的DVH带评估最坏边界值是否符合计划评估标准，当出现问题时，应用体素级最坏情况剂量分布来定位潜在风险区域。
