Analysis of setup error based on CTVision for nasopharyngeal carcinoma during IGRT

基于CTVision的鼻咽癌IGRT治疗中摆位误差分析

阅读:2

Abstract

The aim of the present study was to investigate the role of CTVision in interfractional setup errors during intensity-modulated radiation therapy (IMRT) in 12 nasopharyngeal carcinoma (NPC) patients. The trend of setup errors as a function of time during a fractionated radiotherapy course was investigated, and the influence of reconstructive thickness on image reconstruction for setup errors was analyzed. The appropriate planning target volume (PTV) margin and planning risk volume (PRV) margin were defined to provide a reference for the design of IMRT for NPC. Based on CTVision, online CT was performed weekly for each patient. Setup errors were measured by registration between the CT reconstructed image and reference image. Mean of setup errors, estimated population systematic (Σ), and population random (σ) errors were calculated using SPSS (v15.0). Optimum PTV and PRV margins were calculated. In the clinical data, for the LR (left-right), SI (superior-inferior), and AP (anterior-posterior) directions, Σ was 0.8, 0.8, and 1.0 mm, respectively, and σ was 1.0, 1.3, and 0.8 mm, respectively. In the LR, SI, and AP directions, PTV margins were at least 2.7, 2.9, and 3.0 mm, respectively, and PRV margins were at least 1.5, 1.7, and 1.7 mm, respectively. No significant differences in setup errors were observed during the fractionated radiotherapy course (p > 0.05). However, CT image reconstruction with different thicknesses affected the accuracy of measurements for setup errors, particularly in the SI direction. The application of CTVision to correct setup errors is important and can provide reasonable margins to guarantee the coverage of PTVs and spare organs at risk. A thickness of 3 mm in the reconstructed image is appropriate for the measurement of setup errors by image registration.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。