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目的呼吸运动影响患者实际照射剂量,不同多页光栅(multi-leaf collimator,MLC)的运动方式对呼吸运动造成剂量偏差的敏感性不同。本研究旨在定量分析两种子野分割算法受呼吸幅度影响的剂量偏差大小。方法收集2013-06-10-2015-04-15中国科学院合肥肿瘤医院收治的肺癌患者10例,两种类型放疗计划各制定10例。呼吸运动仪带动QA模体正弦运动模拟患者头脚方向不同呼吸幅度的呼吸运动,分别采集等中心层面剂量。通过Verisoft分析采集数据的射野通过率和剂量分布。结果 10例肺癌患者Slidingwnd和Smartsequence子野分割方式产生的子野数分别为40±5.2和20±7.7,P=0.007;机器跳数分别为(388±56.6)和(346±60.4)MU,P=0.007。随着呼吸幅度的增加,射野通过率变小。Smartsequence和Slidingwnd在8 mm幅度时射野通过率分别为(85.27±4.57)%和(87.26±5.25)%,t=3.435,P=0.007;在10mm幅度时射野通过率分别为(74.95±5.98)%和(79.13±5.11)%,t=6.05,P<0.001。Smartsequence比Slidingwnd射野通过率低,且通过率<90%;呼吸幅度=6mm时,两种计划通过率为(91.81±3.65)%和(92.67±4.55)%,差异无统计学意义,P>0.05。呼吸幅度<6mm时,两种计划通过率差异无统计学意义,P>0.05;通过率>90%,满足临床剂量验证要求。结论 Smartsequence子野分割算法对呼吸运动造成的剂量偏差敏感性大,建议选择Slidingwnd子野分割方式。
Objective Respiratory exercise affects the actual radiation dose of patients, and different multi-leaf collimator (MLC) exercise patterns have different sensitivities to the dose deviation caused by respiratory motion. The purpose of this study is to quantitatively analyze the dose deviation of the two subfield splitting algorithms affected by the respiratory rate. Methods Totally 10 patients with lung cancer admitted to Hefei Cancer Hospital of Chinese Academy of Sciences were enrolled in 2013-06-10-2015-04-15. There were 10 cases of two types of radiotherapy plans. Respiratory movement instrument to drive the QA motif sinusoidal motion simulation of head and foot direction of the respiratory rate of different respiratory motion, respectively, such as the central level acquisition dose. Through the Verisoft analysis of the acquisition of data through the field rate and dose distribution. Results The number of subfields generated by Slidingwnd and Smartsequence segregation was 40 ± 5.2 and 20 ± 7.7, P = 0.007, respectively. The machine hops were (388 ± 56.6) and (346 ± 60.4) MU, P = 0.007. With the breathing rate increases, the rate of field through the smaller. The pass-through rates of the Smartsequence and Slidingwnd at the amplitude of 8 mm were (85.27 ± 4.57)% and (87.26 ± 5.25)%, respectively, t = 3.435 and P = 0.007. The pass-through rates at the amplitude of 10 mm were 74.95 ± 5.98 )% And (79.13 ± 5.11)%, t = 6.05, P <0.001. The pass rates of Smartsequence and Slidingwnd were lower than 90% and 91%, respectively (P <0.01), and the pass rates were 6% (91.81 ± 3.65)% and (92.67 ± 4.55)%, respectively. 0.05. Breathing rate <6mm, the difference between the two plans no significant difference, P> 0.05; pass rate> 90%, to meet the clinical dose verification requirements. Conclusion The Smartsequence sub-field segmentation algorithm is sensitive to the dose deviation caused by respiratory motion. It is suggested to choose the SlidingWnd sub-field segmentation method.