呼吸运动对两种子野分割算法剂量影响研究

发布时间：2018-06-16 12:26

本文选题：呼吸运动幅度 + Smartsequence　；参考：《中华肿瘤防治杂志》2017年09期

【摘要】：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,P0.001。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,P0.05。呼吸幅度6mm时,两种计划通过率差异无统计学意义,P0.05;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。
[Abstract]:Objective Respiratory motion affects the actual dose of irradiation in patients. The sensitivity of different multi-leaf collimator (MLCC) motion patterns to dose deviation caused by respiratory movement is different. The purpose of this study was to quantitatively analyze the dose deviation of the two-seed field segmentation algorithm affected by respiratory amplitude. Methods Ten patients with lung cancer admitted to Hefei Oncology Hospital, Chinese Academy of Sciences, 2013-06-10-2015-04-15, 10 patients with two types of radiotherapy were selected. The respiratory motif drives the QA motif sinusoidal motion to simulate the respiratory movement of the patient with different respiration amplitude in the head and foot direction and collects the dose of isocentric level respectively. The radiation pass rate and dose distribution of the collected data were analyzed by Verisoft. Results the number of subfields produced by Slidingwnd and Smart sequence subfields in 10 patients with lung cancer were 40 卤5.2 and 20 卤7.7, respectively, and the number of machine hops were 388 卤56.6) and 346 卤60.4 respectively. With the increase of respiratory amplitude, the passing rates of Smartsequence and Slidingwnd were 85.27 卤4.57% and 87.26 卤5.25 5% respectively at the amplitude of 8 mm, and the passing rates of passing through the field were 74.95 卤5.98% and 79.13 卤5.11% at the amplitude of 10mm, respectively, and the passing rate was 90000 when the respiratory amplitude was 6mm, respectively, and the passage rate of Sliwnd was lower than that of Sliwnd at the amplitude of 8 mm, and the rate of passing through the field was lower than that of Sliwnd when the amplitude of respiration was 6mm, the rate of passing through was 74.95 卤5.98% and 79.13 卤5.11% respectively, and the passing rate of Sliwnd was lower than that of Sliwnd at the amplitude of 8mm. The pass rates of the two plans were 91.81 卤3.65% and 92.67 卤4.55%, respectively. The difference was not statistically significant (P 0.05). There was no significant difference in the pass rate between the two plans when the respiratory amplitude was 6mm (P 0.05), and the pass rate was 90%, which met the requirement of clinical dose verification. Conclusion Smartsequence field segmentation algorithm is sensitive to dose deviation caused by respiratory movement, so Slidingwnd subfield segmentation method is recommended.
【作者单位】：中国科学院合肥物质科学研究院医学物理与技术中心·中国科学院合肥肿瘤医院放疗中心;中国解放军第一零五医院肿瘤诊疗中心;
【基金】：中国科学院合肥物质科学研究院院长基金(YZJJ201325)
【分类号】：R730.55;R734.2

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