HDR prostate brachytherapy plan robustness and its effect on in-vivo source tracking error thresholds: A multi-institutional study

MEDICAL PHYSICS(2022)

引用 6|浏览18
暂无评分
摘要
Purpose The purpose of this study was to examine the effect of departmental planning techniques on appropriate in-vivo source tracking error thresholds for high dose rate (HDR) prostate brachytherapy (BT) treatments, and to determine if a single in-vivo source tracking error threshold would be appropriate for the same patient anatomy. Methods The prostate, rectum, and urethra were contoured on a single patient transrectal ultrasound (TRUS) dataset. Anonymized DICOM files were disseminated to 16 departments who created an HDR prostate BT treatment plan on the dataset with a prescription dose of 15 Gy in a single fraction. Departments were asked to follow their own local treatment planning guidelines. Source positioning errors were then simulated in the 16 treatment plans and the effect on dose-volume histogram (DVH) indices calculated. Change in DVH indices were used to determine appropriate in-vivo source tracking error thresholds. Plans were considered to require intervention if the following DVH conditions occurred: prostate V100% < 90%, urethra D0.1cc > 118%, and rectumtt Dmax > 80%. Results There was wide variation in appropriate in-vivo source tracking error thresholds among the 16 participating departments, ranging from 1 to 6 mm. Appropriate in-vivo source tracking error thresholds were also found to depend on the direction of the source positioning error and the endpoint. A robustness parameter was derived, and found to correlate with the sensitivity of plans to source positioning errors. Conclusions A single HDR prostate BT in-vivo source tracking error threshold cannot be applied across multiple departments, even for the same patient anatomy. The burden on in-vivo source tracking devices may be eased through improving HDR prostate BT plan robustness during the plan optimisation phase.
更多
查看译文
关键词
brachytherapy, HDR, in-vivo, prostate, robustness, source tracking
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要