Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A feasibility study on a machine-learning-based quality assurance tool for spot-scanning proton therapy using delivery log files and treatment plans.

Physics and imaging in radiation oncology·2026
Same author

Quantitative phantom-based comparison of commercial CT metal artifact reduction algorithms.

Journal of applied clinical medical physics·2026
Same author

Dissolved inorganic phosphorus enrichment in groundwater of phosphate mining areas driven by multiple biogenic pathways.

Water research·2026
Same author

Flow as the mediating mechanism in marathon events: connecting event quality, motivation, and self-efficacy to perceived value and performance.

Frontiers in sports and active living·2026
Same author

An overlooked source of skin dose perturbation: Commercial tattoo inks in radiotherapy.

PloS one·2026
Same author

Clinical Outcomes of Ablative MR-Guided Adaptive SBRT for Pancreatic Lesions.

Pancreas·2026

相关实验视频

Updated: Jan 17, 2026

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.8K

用深度强化学习学习为局部高级宫癌进行间歇性HDR支臂治疗的自动化治疗规划.

Mohammadamin Moradi1, Runyu Jiang1,2, Yingzi Liu1

  • 1Department of Radiation & Cellular Oncology, University of Chicago, Chicago, IL, USA.

ArXiv
|September 22, 2025
PubMed
概括

本研究引入了使用强化学习 (RL) 进行高剂量率 (HDR) 支臂治疗在宫癌中的计划的自动化框架,提高了计划质量和效率,而不是手动方法.

更多相关视频

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
08:17

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy

Published on: June 7, 2015

16.2K
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.9K

相关实验视频

Last Updated: Jan 17, 2026

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant
05:18

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

Published on: October 6, 2023

1.8K
Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
08:17

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy

Published on: June 7, 2015

16.2K
Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
08:25

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System

Published on: April 11, 2018

15.9K

科学领域:

  • 医学物理 医学物理
  • 辐射瘤学 辐射瘤学
  • 人工智能在医学中的应用

背景情况:

  • 高剂量率 (HDR) 支臂治疗对于局部晚期宫癌治疗至关重要.
  • 目前的HDR支臂疗法规划严重依赖于人工专业知识,导致变化和低效率.
  • 自动化治疗计划可以提高HDR支臂疗法的一致性和效率.

研究的目的:

  • 开发一个全自动化的HDR支臂疗法规划框架.
  • 整合强化学习 (RL) 和基于剂量的优化,以改善治疗计划.
  • 为了实现临床上可接受的计划,提高一致性和效率.

主要方法:

  • 一个分层的两阶段自动规划框架,结合了基于深度Q网络 (DQN) 的RL和基于Adam的优化.
  • RL代理人反复选择治疗计划参数 (TPPs),平衡目标覆盖率和风险器官 (OAR) 节省.
  • 剂量-体积组图 (DVH) 度量和临床剂量目标指导RL代理和优化器.

主要成果:

  • 自动化框架成功地学习了跨不同解剖学的临床上有意义的TPP调整.
  • 基于RL的自动化计划实现了较高的平均得分 (93.89%) 与手动临床计划 (91.86%) 相比,对于未见过的患者.
  • 在大多数情况下,完整的目标覆盖率和减少CTV热点的改善得到了维持.

结论:

  • 拟议的自动化HDR支臂疗法规划框架显示了比手动规划更高的性能.
  • 这种人工智能驱动的方法为宫癌的一致和高效的治疗规划提供了有希望的解决方案.
  • 进一步的验证可以将该框架作为临床实践中的标准.