基于医学图像分析技术的肺癌放射治疗的优化

Radiotherapy Optimization for Lung Cancer Based on Medical Image Analysis Technique

目的通过利用医学图像分析技术,对肺癌放射治疗的计划靶区进行个体化设计并每周进行自适应调整以达到在确保肿瘤控制效果的条件下适当减小正常肺组织的受照剂量,从而实现放射治疗的优化。方法针对23例肺癌病人,获取病人的CT影像和不同体位的动态透视数据,采用医学图像分析技术自动或交互式勾画出初始肿瘤体积(GTV)体积,分别确定其运动范围,制定出相应的治疗计划,并在放疗过程中分阶段地进行比较以确定肿瘤体积的变化以及正常组织所受剂量大小。结果通过对23例病人的6313张影像数据以及78组动态透视数据进行分析,运用医学图像分析技术可以根据患者本人的影像数据特点进行个体化放疗计划的设计,使得在放疗过程中能有效减小肿瘤GTV体积70%～80%,从而有效降低同侧正常肺组织的受照剂量。结论基于医学图像分析技术的放射治疗可以有效运用到放疗的定位以及GTV和临床治疗区(CTV)的确定,以使得放疗计划的设计实现个体化并可在放疗过程中及时自适应调整放疗计划,从而在保证肿瘤治疗效果的同时减少正常组织的受照剂量。

Objective To evaluate the feasibility of using medical image analysis for adaptive radiotherapy of lung cancer by drawing the individual contours automatically or interactively and adjusting the planning target volume weekly for reducing the volume of the excessive irradiated normal lung tissue. Methods Many CT images of the GTV and dynamic X - ray fluoroscope data of 23 patients were acquired and all the data were used for working out the tumor radiotherapy plan （TPS） and positioning the patient and to measure reduction in GTV volume. A planning study was conducted to determine the amount of lung - sparing that could have been achieved if adaptive therapy had been used. Treatment plans were created in which the target volumes were reduced after tumor reduction was measured. Results A total of 6313 CT imaging sessions and 78 groups of X - ray dynamic fluoroscope data were performed on 23 lung patients. The GTV was reduced by 70% - 80% during the course of treatment. Based on these treatment planning studies, the dose of ipsilateral lung can be reduced significantly by adapting the treatment delivery. Conclusion Medical image analysis can be used to position the GTV and CTV of the tumors. This technology can help to work out the individual TPS and adjust the radiotherapy treatment plan adaptively during the course of treatment and reduce the dose of normal tissues as well as insure the effect of tumor treatment.