Detection of anatomical changes using two‐dimensional x‐ray images for head and neck adaptive radiotherapy
Detection of anatomical changes using two‐dimensional x‐ray images for head and neck adaptive radiotherapy
复制标题
使用二维 X 射线图像检测头颈适应性放射治疗的解剖变化
DOI：
10.1002/mp.15587
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发表时间：
2022
期刊：
影响因子：
3.8
通讯作者：
Sakae Takeji
中科院分区：
文献类型：
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作者：
Hirotaki Kouta;Moriya Shunsuke;Tachibana Hidenobu;Sakae Takeji
目的开发一种利用二维(2D)X线图像检测解剖结构变化的系统。方法对10例头颈部肿瘤患者的二维X线和锥束CT图像进行回顾性分析。在治疗期间每天采集2DX光图像，而每周采集CBCT图像。所开发的系统导入在初始处理日和另一天获得的2D X射线图像，然后使用转换表将其转换为水当量厚度(湿)。计算第一天和其他治疗日的湿像差(Δ湿)作为解剖变化的量化值，并进行可视化以识别解剖变化的位置。比较Δ湿度值和相应的Δ图像上的侧颈距离差值。以ΔLND作为解剖改变的基本依据。测量第一颈椎(C1)和肿瘤中心(TC)的Δ湿润度和ΔLnD。分别取C1和TC观察腮腺和肿瘤的体积变化。计算敏感度和特异度以评估2D-WEAM系统的性能。湿和LND的分界值设置为2-10 mm。此外，还为6名重新扫描CT图像的患者制定了强度调制质子治疗(IMPT)计划。利用靶区和危险器官的剂量学参数，将重新扫描的CT图像上的IMPT计划与模拟CT上的原始计划进行比较。结果ΔWET和ΔLND对C1和TC的平均差值分别为−0.62±1.66 mm和−0.93±1.28 mm(平均±1SD)。该系统中的Δ湿部与ΔLND的CBCT图像具有很好的一致性。在以2~10 mm为界值的C1和TC的敏感度和特异度结果中，所有界值的敏感度和特异度均为85%，而5~10 mm的敏感度和特异度分别为90%和90%。重新计划时Δ平均湿润12.8 mm，导致脊髓D1cc最大剂量增加8.4Gy.腮腺D50最大剂量增加26.6Gy.口腔D50最大剂量增加23.2Gy.结论我们开发了一种新的利用二维X线图像检测解剖结构变化的系统。所开发的Δ湿测量系统在C1和TC处与ΔLND的测量结果一致，平均误差小于1 mm。Δ湿法检测解剖改变具有很高的敏感性和特异性，其临界值为5-10 mm。该系统可以监测日常解剖变化，不会对患者造成高暴露，不需要任何低效的工作，可以应用于日常在线自适应质子治疗和触发自适应放射治疗。
PurposeTo develop a system for detecting anatomical changes using two‐dimensional (2D) x‐ray images.MethodsTen patients with head and neck cancer were retrospectively analyzed using 2D x‐ray and cone‐beam computed tomography (CBCT) images. The 2D x‐ray images were acquired daily, whereas the CBCT images were acquired weekly during the treatment period. The developed system imported the 2D x‐ray images obtained on the initial treatment day and on another day, and thereafter converted them into the water equivalent thickness (WET) using the conversion table. The difference between the WET images for the first and other treatment days (ΔWET) was calculated as the quantitative value for anatomical changes and visualized to recognize the anatomical change location. We compared ΔWET and the difference in the lateral neck distance (ΔLND) on the corresponding CBCT images. ΔLND was used as the ground truth for anatomical changes. ΔWET and ΔLND were measured at the first cervical vertebra (C1) and the tumor center (TC). C1 and TC were selected to observe the volume changes in the parotid gland and tumor, respectively. Sensitivity and specificity were calculated to evaluate the performance of the 2D‐WET system. The cut‐off values of WET and LND were set to 2–10 mm. Furthermore, intensity‐modulated proton therapy (IMPT) plans for six patients with rescan CT images were generated. The IMPT plans on the rescan CT images were compared to the original plans on simulation CT using the dosimetric parameters for the target and the organs at risk.ResultsThe mean differences between ΔWET and ΔLND for C1 and TC were −0.62 ± 1.66 mm and −0.93 ± 1.28 mm (mean ± 1 SD), respectively. ΔWET in the proposed system was in good agreement with ΔLND using the CBCT images. In the sensitivity and specificity results for C1 and TC with cut‐off values from 2 to 10 mm, the sensitivity was >85% for all cut‐off values, while the specificity was >90% at 5–10 mm and <90% at less than 5 mm. The average ΔWET at the time of replanning was 12.8 mm which resulted in maximum dose increase in the spinal cord D1cc by 8.4 Gy, the parotid gland D50 by 26.6 Gy, and the oral cavity D50 by 23.2 Gy.ConclusionsWe developed a new system for detecting anatomical changes using 2D x‐ray images. The developed system with ΔWET showed an agreement with ΔLND at C1 and TC with an average difference of less than 1 mm. ΔWET detected anatomical changes with high sensitivity and specificity with a cut‐off value of 5–10 mm. This system can monitor daily anatomical changes without causing high exposure to patients and requiring any inefficient work, and it can be applied to daily online adaptive proton beam therapy and triggered adaptive radiotherapy.