ZAP-X治疗时间的回归建模
Michael Chaga1, Akil Anthony2, Timothy Chen1
1Radiation Oncology, Jersey Shore University Medical Center, Neptune, USA.
Cureus
|July 28, 2025
概括
准确的立体射线手术 (SRS) 治疗时间预测至关重要. 对于ZAP-X系统而言,新的Ridge回归模型显著改善了ZAP-X治疗时间估计,有助于临床工作流程和调度.
科学领域:
- 神经外科 神经外科
- 医学物理 医学物理
- 放射治疗技术 放射治疗技术
背景情况:
- 准确的立体射线手术 (SRS) 治疗时间预测对于有效的患者安排和工作流程管理至关重要.
- ZAP-X系统是一个新的骨SRS平台,提供内部治疗时间估计,经常低估实际程序持续时间.
- 这种差异需要开发更可靠的预测模型来优化SRS操作.
研究的目的:
- 开发和验证ZAP-X SRS治疗时间的强大预测模型.
- 与系统内置计算相比,提高治疗时间估计的准确性和可靠性.
- 确定影响ZAP-X治疗持续时间的关键因素,以改善操作规划.
主要方法:
- 分析了200名ZAP-X SRS患者的前性数据,包括时间指标,计划变量和临床因素.
- 使用随机森林回归来确定影响治疗时间的关键变量.
- 开发并通过10倍交叉验证验证Ridge回归模型来预测治疗持续时间.
主要成果:
- 随机森林分析强调了设置时间和门架时间作为ZAP-X治疗持续时间的主要决定因素.
- 其他重要因素包括光束数量,同心,剂量和目标数量.
- 回归模型实现了高预测精度 (R2 = 0.984,MAE = 1.94分钟,RMSE = 2.49分钟),超过了ZAP-X内部估计.
结论:
- 斜坡回归模型提供了一个非常准确和可解释的方法来预测ZAP-X SRS治疗时间.
- 该模型能够考虑程序变化,特别是设置时间,这有助于其卓越的性能.
- 这种预测工具有着即时的临床应用,用于优化SRS中心的患者安排和资源管理.
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