确定辐射瘤学家对细分质量的人口因素的作用:使用贝叶斯估计的群众源挑战的见解
Kareem A Wahid1,2, Onur Sahin1, Suprateek Kundu3
1Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
medRxiv : the preprint server for health sciences
|September 11, 2023
概括
这项研究发现,瘤类别在放射治疗中显著影响自我细分质量,但常见的观察者人口统计数据无法可靠地预测性能. 需要进一步的研究来了解细分的质量因素.
科学领域:
- 辐射疗法 辐射疗法
- 医疗成像医学成像
- 计算生物学 计算生物学
背景情况:
- 放射治疗中的自动细分对于工作流效率至关重要.
- 从临床医生那里获得的自细分培训数据的质量至关重要.
- 影响临床医师细分质量的因素仍然不太清楚.
研究的目的:
- 调查观察者人口学变量对定量细分绩效的影响.
- 确定影响临床医生衍生的放射治疗细分质量的关键因素.
主要方法:
- 利用了来自Contouring Collaborative for Consensus in Radiation Oncology数据集的五个疾病部位的细分.
- 使用子相似系数 (DSC) 对专家黄金标准进行分段质量的评估.
- 采用贝叶斯回归来分析人口变量和细分质量指标之间的关联.
主要成果:
- 瘤类别对多个疾病部位 (乳腺,肉瘤,H&N,GI) 的细分质量产生了显著的负面影响.
- 在细分质量和常见的人口变量之间没有发现一致的关系.
- 一个很高的百分比的观察超过了风险器官 (55%) 和瘤体积 (31%) 的专家推导的观察者间可变性截止值.
结论:
- 关于影响细分质量的人口因素的传统假设需要重新评估.
- 关于决定细分质量的因素存在重大不确定性.
- 未来的研究应该探索额外的人口变量,多样化的患者队列,成像模式和替代质量指标.
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