Department of Physics and Astronomy, Louisiana State University and Agricultural and Mechanical College, Baton Rouge, LA 70803-4001, United States of America.
Phys Med Biol. 2018 Jan 5;63(1):015035. doi: 10.1088/1361-6560/aa9a30.
The overlap volume histogram (OVH) is an anatomical metric commonly used to quantify the geometric relationship between an organ at risk (OAR) and target volume when predicting expected dose-volumes in knowledge-based planning (KBP). This work investigated the influence of additional variables contributing to variations in the assumed linear DVH-OVH correlation for the bladder and rectum in VMAT plans of prostate patients, with the goal of increasing prediction accuracy and achievability of knowledge-based planning methods. VMAT plans were retrospectively generated for 124 prostate patients using multi-criteria optimization. DVHs quantified patient dosimetric data while OVHs quantified patient anatomical information. The DVH-OVH correlations were calculated for fractional bladder and rectum volumes of 30, 50, 65, and 80%. Correlations between potential influencing factors and dose were quantified using the Pearson product-moment correlation coefficient (R). Factors analyzed included the derivative of the OVH, prescribed dose, PTV volume, bladder volume, rectum volume, and in-field OAR volume. Out of the selected factors, only the in-field bladder volume (mean R = 0.86) showed a strong correlation with bladder doses. Similarly, only the in-field rectal volume (mean R = 0.76) showed a strong correlation with rectal doses. Therefore, an OVH formalism accounting for in-field OAR volumes was developed to determine the extent to which it improved the DVH-OVH correlation. Including the in-field factor improved the DVH-OVH correlation, with the mean R values over the fractional volumes studied improving from -0.79 to -0.85 and -0.82 to -0.86 for the bladder and rectum, respectively. A re-planning study was performed on 31 randomly selected database patients to verify the increased accuracy of KBP dose predictions by accounting for bladder and rectum volume within treatment fields. The in-field OVH led to significantly more precise and fewer unachievable KBP predictions, especially for lower bladder and rectum dose-volumes.
重叠体积直方图（OVH）是一种常用的解剖学指标，用于在基于知识的计划（KBP）中预测靶区和危及器官（OAR）的预计剂量体积时，量化器官与靶区之间的几何关系。本研究旨在探讨在 VMAT 计划中，除了线性剂量-体积直方图-OVH 相关性外，其他变量对膀胱和直肠的影响，以提高预测准确性和实现基于知识的计划方法。采用多标准优化方法对 124 例前列腺患者进行 VMAT 计划的回顾性生成。DVH 量化患者剂量学数据，OVH 量化患者解剖学信息。计算了 30%、50%、65%和 80%的膀胱和直肠的 OVH 分数。采用皮尔逊积矩相关系数（R）定量分析潜在影响因素与剂量之间的相关性。分析的因素包括 OVH 的导数、规定剂量、PTV 体积、膀胱体积、直肠体积和场内 OAR 体积。在所选择的因素中，只有场内膀胱体积（平均 R=0.86）与膀胱剂量呈强相关性。同样，只有场内直肠体积（平均 R=0.76）与直肠剂量呈强相关性。因此，开发了一种考虑场内 OAR 体积的 OVH 公式，以确定其对改善 DVH-OVH 相关性的程度。包括场内因素可改善 DVH-OVH 相关性，研究的分数体积的平均 R 值从-0.79 提高到-0.85，从-0.82 提高到-0.86，分别为膀胱和直肠。对 31 例随机数据库患者进行了重新计划研究，以验证通过考虑治疗场内的膀胱和直肠体积来提高 KBP 剂量预测的准确性。场内 OVH 导致 KBP 预测更加精确，难以实现的预测更少，尤其是对于较低的膀胱和直肠剂量体积。
