谷歌浏览器插件
订阅小程序
在清言上使用

Innovative Approaches to Enhance High-Let D Tumor Targeting in Carbon Ion Radiotherapy

Health and technology(2024)

引用 0|浏览7
暂无评分
摘要
Purpose To present novel approaches in particle therapy that could result in an improvement of patient outcome. Methods Technological/planning and biological innovations could bring particle therapy into a new area of precision medicine. However, several hurdles have to be overcome in order to transform these R&D opportunities into clinical advantages. In this contribution, we summarize the potential advantages of novel tumor targeting, through high-LET d boosting strategies with carbon ions, over standard IMPT: LET d -optimization for IMPT plan, IMPT LET , and spot-scanning hadron arc (SHArc) therapy. Two patient cases are presented to showcase the benefit: a pancreatic cancer patient (PATA) and a recurrent glioblastoma patient (PATB). Results For both patients, the prescription dose and target/organs at risk (OARs) optimization goals were reached for the three techniques. In standard IMPT, the maximum LET d is placed outside of the target volume and extends into normal tissues. For the gross target volume (GTV), mean LET d values were, on average, around ∼40–60 keV/µm. IMPT LET allowed an increase in the GTV minimum LET d from 38.4 keV/µm to 48.6 keV/µm, and from 55.1 to 87.1 keV/µm, for PATA and PATB, respectively. SHArc led to an enhancement of the maximum LET d in the GTV up to at least 125 keV/µm, while the minimum GTV LET d were 47.2 keV/µm and 46.1 keV/µm, respectively. For PATA, SHArc lowers the maximum LET d in the gastrointestinal tract to 47.5 keV/µm compared to 88.0 keV/µm and 83.0 keV/µm found for the IMPT and IMPT LET plans, respectively. Conclusions Many technological and biological innovations could enhance our current clinical approach. Following the current success of the IMPT LET introduction in clinic, SHARc will represent an interesting clinical option in carbon ion therapy.
更多
查看译文
关键词
Particle therapy,LETd-boosting strategies,SHArc
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