International journal of radiation oncology, biology, physics · 2025
NRG Oncology Assessment of Artificial Intelligence for Automatic Treatment Planning in Radiation Therapy Clinical Trials: Present and Future.
СтатьяПоддержка NIH: внешняя программаНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Jia Xun, Rong Yi, Wu Qingrong, Cardenas Carlos E, Court Laurence E, Hrinivich William T, Kang Hyejoo, Kovalchuk Nataliya, Whitaker Thomas J, Xiao Ying, Zhang Pengpeng, Chen Quan
Аннотация
PURPOSE: Recent advances in artificial intelligence (AI) have showcased the potential of automatic treatment planning for clinical trials involving radiation therapy. This paper offers an overview of the current landscape of AI-based treatment planning, emphasizing its ability to improve plan quality and streamline the planning process.
METHODS AND MATERIALS: Acknowledging the increasing clinical utilization and promise of these technologies, the NRG Oncology Medical Physcis Subcommittee established a working group to assess the status of AI-based automatic treatment planning for clinical trials, along with its challenges and future directions.
RESULTS: We describe its critical roles within radiation therapy clinical trials and discuss the challenges of integrating AI into such settings. We further outline short-term actions for enhancing AI-based automatic treatment planning for radiation therapy clinical trials and explore future directions for the field, such as the development of personalized algorithms, the integration of AI into routine clinical practice, and the need for support in this direction.
CONCLUSIONS: This assessment provides insights into the present state and prospects of AI in radiation therapy clinical trials to facilitate enhanced treatment planning and patient care.
METHODS AND MATERIALS: Acknowledging the increasing clinical utilization and promise of these technologies, the NRG Oncology Medical Physcis Subcommittee established a working group to assess the status of AI-based automatic treatment planning for clinical trials, along with its challenges and future directions.
RESULTS: We describe its critical roles within radiation therapy clinical trials and discuss the challenges of integrating AI into such settings. We further outline short-term actions for enhancing AI-based automatic treatment planning for radiation therapy clinical trials and explore future directions for the field, such as the development of personalized algorithms, the integration of AI into routine clinical practice, and the need for support in this direction.
CONCLUSIONS: This assessment provides insights into the present state and prospects of AI in radiation therapy clinical trials to facilitate enhanced treatment planning and patient care.